Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

A multi-agent system for spine MRI report generation from multi-sequence imaging

Spinal pathology is a leading cause of pain and disability worldwide. Spine magnetic resonance imaging (MRI) is central to clinical evaluation, yet its interpretation remains complex and time-consuming, requiring integration of information across multiple imaging sequences and anatomical regions. Despite recent advances in automated MRI analysis, effectively combining multi-sequence data while preserving sequence-specific diagnostic information remains an open challenge. Here we present SpineAgent, a multi-agent framework for spine MRI report generation built upon a multi-sequence foundation model trained on routine clinical data from 32,047 patients and 453,683 MRI series, comprising a total of 13,441,191 MRI slices. To accommodate diverse modalities of sequences, we first pre-train two DINOv3-based encoders separately on T1- and T2-weighted sequences. We then introduce a continual training strategy that learns a synthesizer to embed images of other sequences using the T1 and T2 encoders, producing patient-level embedding that integrates various signals across MRI sequences. Using these embeddings, SpineAgent achieves state-of-the-art performance, with mean 10.8% AUROC improvement across 17 spinal condition-prediction tasks compared to the best competing method, and demonstrates strong generalizability under cross-manufacturer and cross-cohort evaluation. Beyond classification, SpineAgent enables pathology localization by identifying findings-relevant slices and segmenting pathological regions. It also supports multimodal image-report retrieval, providing a solid foundation for scalable and explainable MRI report generation. We further integrate these validated capabilities of SpineAgent into 37 specialized agents for condition diagnosis, pathological-region localization, and clinically-similar-cases retrieval. Finally, we incorporate their outputs as structured tokens within a Medical Report Agent trained end-to-end for report generation. Through both automated metrics and expert evaluation by five radiologists, SpineAgent achieves leading performance in spine MRI report generation. Together, SpineAgent introduces a continual training approach for multi-sequence spine MRI understanding. By decomposing report generation into clinically grounded subtasks addressed by specialized agents, the SpineAgent framework enables accurate, interpretable and generalizable spine MRI reporting across diverse imaging sequences and anatomical regions.

bioinformatics↗

bioRxiv2026

Electroadhesion of polymer networks by polycation interfacial bridging: sticky electrophoresis, ionic complexation, and chain entanglement

An e-GLUE is a polymer network containing interpenetrating polycations, which can bond the anionic network of mucosa through interfacial polycation bridging under an electric field. Such an electroadhesion involves electrophoresis of polycations, ionic complexation between polycations and the anionic network, and polycation-network entanglement, yet their quantitative understanding is lacking. Here, we formulate a theoretical model to describe electroadhesion of polymer networks by polycation interfacial bridging. We use a diffusion-drift model coupled with a Bell-like field-dependent chain friction to describe the sticky electrophoresis of polycations in an anionic sea. The formation of ionic bonds is determined by local availability of cations and anions over the penetration depth. To debond, a force must either pull polycations out from the e-GLUE network or first dissociate them from ionic complexes and then pull out from the anionic network. We model chain pullout from the bulk networks to the interface as a viscous drag against water. The adhesion strength is calculated by summing the debonding force for each polycation per unit area across all chains. Our model quantitatively links electric field strength, applied duration, polycation chain length, and cation concentration to polycation electrophoresis kinetics, ionic bond formation, and adhesion strength. We further conduct electroadhesion tests, and our model predicts well with the experimental data. Lastly, we discuss the use of the model to guide the e-GLUE design. TOC graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/730541v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@16524c6org.highwire.dtl.DTLVardef@15163aeorg.highwire.dtl.DTLVardef@673949org.highwire.dtl.DTLVardef@e207a0_HPS_FORMAT_FIGEXP M_FIG C_FIG For Table of Contents use only

bioengineering↗

bioRxiv2026

Research Process Graph: LLM-Driven Extraction and Hierarchical Organization of Research Logic

Plant biology now publishes thousands of experimental research articles each year, but their core research logic, namely what questions are being asked, with what methods, and what is being found, remains locked inside free text and invisible to systematic analysis. Here we present a structured, 20-year atlas of The Plant Cell in which every paper is converted into a typed, directed Research Process Graph (RPG) of Question (Q), Method (M) and Finding (F) nodes connected by Q[->]M and M[->]F edges. A benchmarked large language model pipeline applied to 2,633 Plant Cell research articles published 2005-2026 recovered >110,000 Q/M/F nodes and >126,000 directed Q[->]M[->]F chains with>98% precision. A second LLM pass generalises each node into a paper-independent canonical form and assigns it to one of 10 top-level (L1) and [~]90 sub-level (L2) categories for each node type, producing the first comprehensive map of plant-biology research logic at the resolution of individual research questions. The atlas reveals that Plant Cell papers fall into seven canonical paper recipes with characteristic Q[->]M[->]F sub-structures, that peripheral experimental techniques have largely turned over while a stable methodological core persisted, and that the strongest correlate of per-PI citation impact is methodological breadth, not productivity or topical breadth. We release the atlas as a public, browsable database with five complementary interfaces: paper views, an LLM-powered research assistant, expert profiles, a taxonomy browser, and a method explorer. The database, available at https://rpg.connectome.tools/, turns the literature into a queryable community resource.

plant biology↗

bioRxiv2026

AI-guided analysis of human pancreatic islet sociology reveals distinct cell compositional changes in type 1 diabetes

Human pancreatic islets exhibit greater anatomic and cellular heterogeneity than previously appreciated, raising fundamental questions about how their composition varies with age, sex, region, and islet size and how type 1 diabetes (T1D) alters these relationships. Yet these questions remained largely unresolved due to the bottleneck of manual tissue inspection. Here, we developed an integrated artificial intelligence (AI)-guided imaging, processing, and statistical pipeline enabling unbiased, high-throughput analysis of more than 2 million candidate islets from 106 non-diabetic (ND) and T1D donors. We identified age-, region-, sex-, and islet size-dependent differences in islet distribution and composition between ND and T1D donors. Profound {beta}-cell loss in T1D was accompanied by reciprocal -cell expansion, whereas {delta}-cells and pancreatic polypeptide cells were largely resilient. Cell area and pseudotime analyses uncovered regional and age-dependent trajectories of islet remodeling across T1D progression, along with distinct patterns of cytoarchitectural reorganization of the endocrine pancreas.

pathology↗

bioRxiv2026

Scene Structure Predicts Perceptual Decisions in Naturalistic Detection Tasks

The human visual system can identify objects in complex natural scenes, yet the mechanisms supporting robust perception under such variable conditions remain incompletely understood. Here, we investigate how the statistical structure of natural scenes shapes perceptual evidence formation and determines whether near-threshold stimuli are perceived correctly or incorrectly. We combine controlled psychophysics, outdoor augmented reality (AR), deep neural networks (DNNs), image-feature analysis, and EEG to examine how background context modulates perceptual decisions. Across multiple detection tasks, human performance was systematically influenced by probe-free background structure. DNNs trained on background images alone predicted correct and incorrect behavioral outcomes, with stronger effects in postcue conditions, suggesting that global scene context contributes to local perceptual decisions when spatial uncertainty is higher. AR experiments further showed that these context-driven effects persist in naturalistic viewing environments. To identify the visual information underlying these effects, we analyzed low-level image statistics. Texture entropy and edge density emerged as informative features, and conventional machine-learning models trained on these measures achieved meaningful correct/incorrect classification. Finally, EEG analyses revealed neural signatures of image-driven perceptual variability: activity during the probe-free preimage window distinguished later correct from incorrect trials, and combining EEG with image-derived features improved decoding performance. Together, these findings show that perception in natural scenes is not determined solely by the target, but is shaped by the statistical structure of the surrounding context. By linking psychophysics, AR, DNN modeling, image statistics, and EEG, this work provides a unified framework for understanding how environmental structure and neural dynamics jointly support perceptual decision-making.

neuroscience↗

bioRxiv2026

Loss of Arginase 2 Promotes Lung Metastasis in immune-competent hosts via Nitric Oxide Synthase 2-Dependent Th17 Response

Distant metastasis is the leading cause of mortality in many cancers. Although metabolic reprogramming is recognized as a hallmark of cancer, how tumor-intrinsic metabolic enzymes regulate tumor-immune crosstalk during metastatic progression remains poorly understood. Here, using a high-throughput functional CRISPR-Cas9 screen targeting metabolic genes in an orthotopic 4T1 murine mammary carcinoma model of spontaneous lung metastasis, we identify a selective enrichment of arginase 2 (ARG2)-deficient tumor cells in metastatic lungs of immunocompetent but not RAG1-deficient mice, indicating a lymphocyte-dependent mechanism. Loss of ARG2 enhances spontaneous lung metastasis without affecting primary tumor growth. Further, metastatic outgrowth in the lung is not affected when tumor cells are injected intravenously, indicating that ARG2 regulates an early stage of the metastatic cascade. Mechanistically, ARG2 deficiency upregulates nitric oxide synthase 2 (NOS2), resulting in increased nitric oxide production, accumulation of cytosolic DNA, and activation of the cGAS-STING-NF-{kappa}B pathway, leading to upregulation of inflammatory cytokines. ARG2-deficient tumors exhibit an immunosuppressive tumor microenvironment characterized by enrichment of Th17 cells and reduced anti-tumor immune populations. Functionally, Th17 cells enhance tumor cell migration in vitro and promote spontaneous lung metastasis in vivo. Genetic deletion of NOS2 attenuates cytosolic DNA accumulation, reduces STING-NF-{kappa}B activation, restores anti-tumor immunity, and suppresses ARG2 deficiency-driven metastatic burden in vivo. Collectively, these findings define a tumor cell-intrinsic ARG2-NOS2 axis that regulates inflammatory signaling and the tumor microenvironment to promote metastasis, highlighting a targetable vulnerability in metastatic breast cancer.

cancer biology↗

bioRxiv2026

Conformational changes underlying electromechanical transduction in prestin resemble a transport transition in pendrin

Prestin (SLC26A5), a membrane protein in cochlear outer hair cells, drives electromechanical transduction essential for mammalian hearing. Unlike other SLC26 anion transporters, prestin functions as a voltage-dependent molecular motor, transitioning between contracted and expanded conformations. How this transition relates to the transporter cycle of SLC26 family members remains unclear. Here, multi-microsecond molecular dynamics (MD) simulations starting from a contracted conformation reveal a rapid, spontaneous transition to an expanded state that resembles the inward-facing conformation of the anion exchanger pendrin (SLC26A4 from mouse). An accompanying transmembrane area expansion is localized to the inner membrane leaflet. In line with this observation, reduced unitary sensor charge movement accompanies neutralization of charged residues localized near the inner leaflet. Simulations uncover a previously uncharacterized contracted conformation that resembles outward-facing pendrin; the MD also predicts an extracellular anion-binding site in prestin. A 3.27-[A] resolution cryo-electron microscopy structure of prestin in the presence of thiocyanate anions confirms this site, which appears to be common in the SLC26 family, notably also in pendrin. Based on the simulations, the extracellular site in pendrin is involved in facilitating anion access to the canonical intracellular site in a conformation-dependent manner while in prestin, the intracellular site is not accessible from the extracellular side. Furthermore, like prestin, pendrin exhibits a non-linear capacitance, an indication of voltage-dependent conformational switching. Together, these findings suggest that prestin and pendrin share core structural and functional properties, notably parallels between expansion-contraction states and anion binding sites, though transition speeds and conformation-dependent ion-accessibility may differ.

biophysics↗

bioRxiv2026

The canine respiratory epithelium is a permissive ecosystem for influenza interspecies transmission and emergence

The outcome of virus spillover ranges from dead-end infections to pandemics and is underpinned by host-pathogen interactions as well as evolutionary and epidemiological processes. The emergence of novel influenza A viruses (IAVs) has been associated with reassortment events involving multiple species, highlighting the importance of reservoir and intermediate hosts in viral emergence. Highly pathogenic H5N1 IAVs of the 2.3.4.4b genotype have caused a panzootic affecting a broad range of mammals. The role of dogs--arguably the most popular companion animal and a natural host of IAVs--in the ecology of IAVs under this new zooepidemiological scenario is unknown. To address this, we characterised the glycome of the dog respiratory epithelium, infected canine tracheal explants with multiple IAVs (including canine H3N2 and H3N8, equine H3N8, avian H3N8 and H5N1, swine H1N1, human H1N1 and H3N2, and bovine H5N1 viruses), and determined their cellular tropism. We show that the respiratory tract of dogs presents abundant sialylated glycans known to act as IAV receptors. Further, most IAVs (including 2.3.4.4b viruses) infected and replicated in dog tracheas, targeting mainly ciliated cells. Serological testing showed evidence of influenza spillover infections in dogs from the UK. Overall, our results show that the canine respiratory tract can provide a suitable environment for the generation of new IAVs. Given the multi-host contact networks of dogs in nature, they could act as recipients, bridging hosts, and/or mixing vessels for multiple IAV lineages, playing a central role in the ecology of influenza emergence.

microbiology↗

bioRxiv2026

Inhibition of Soluble Epoxide Hydrolase Rescues Cognitive Deficits by Preserving Neurovascular Integrity and Attenuating Glial- and Neuropathology in Diabetic-Related Dementia

Diabetes mellitus (DM) is a major risk factor contributing to the development of Alzheimers disease-related dementias (ADRD). While one of the early symptoms of both Alzheimers disease (AD) and DM-related ADRD is a reduction in cerebral blood flow, the underlying biological mechanisms driving this decline remain to be fully elucidated. Genome-wide association studies have linked AD/ADRD to single-nucleotide polymorphisms in the gene encoding soluble epoxide hydrolase (sEH), an enzyme we previously reported to be upregulated in the brains of an AD rat model. Our previous work also demonstrated that chronic inhibition of sEH with 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU) preserves hippocampal-dependent spatial learning and memory and improves cerebral hemodynamics in both AD and DM-ADRD models. In the present study, we found that chronic TPPU treatment (1 mg/kg/day for 9 weeks) reduced brain sEH expression, improved cortical-based long-term non-spatial recognition memory involving both cortical and hippocampal networks, and reduced anxiety in DM-ADRD rats. TPPU improved brain perfusion and normalized impaired whisker-evoked functional hyperemia, an effect linked to upregulation of Kir2.1 expression in cerebral capillaries. Furthermore, TPPU restored tight junction proteins (ZO-1 and OCLN), mitigated capillary rarefaction, and suppressed astrocyte and microglial activation. At the cellular level, TPPU attenuated hippocampal neurodegeneration, restored the expression of synaptic proteins (PSD95 and SY38), and reduced levels of key pro-inflammatory chemokines, including MCP-1, RANTES, and MIP-1, in DM-ADRD. In conclusion, TPPU preserves cognitive function in DM-ADRD by mitigating cerebrovascular dysfunction, neuroinflammation, and gliosis while protecting synaptic integrity and neuronal survival, representing a promising therapeutic strategy for DM-ADRD.

neuroscience↗

bioRxiv2026

High-accuracy hierarchical rRNA operon profiling resolves genomovar-level taxonomy and microdiversity using Nanopore sequencing.

Genomovar-level and intragenomic diversity cannot be resolved by conventional amplicon sequencing due to the limitation of fragment lengths and read accuracy, while the application of metagenomic profiling to a large number of samples can be resource intensive. Here, we report UltraRes-rrn, an integrated wet-lab and computational workflow for high-accuracy rrn (i.e., 16S- ITS-23S rRNA) operon profiling using Nanopore sequencing. By integrating ultra-long DNA recovery, long-read amplicon sequencing, and unique molecular identifiers (UMI)-based consensus correction, UltraRes-rrn obtains full-length 16S-ITS-23S rRNA operon consensus sequences with mean accuracies exceeding 99.98%. To achieve higher resolution, we propose a hierarchical rRNA operon profiling strategy in which concatenated 16S+23S rRNA genes (16S23S) serve as a primary and the internal transcribed spacer (ITS) provides a secondary marker. The 16S23S marker achieved discrimination at the genomovar level compared to either 16S or 23S rRNA genes alone, which mitigates the ITS-driven over-splitting observed with the full-length rrn operon and allows for larger proportion of data being classified at higher confidence thresholds. Further, ITS variation was strongly structured by tRNA occurrence patterns, suggesting that ITS can capture taxon microdiversity missed by either 16S or 23S rRNA gene sequences alone. The UltraRes-rrn workflow was applied to full-scale nitrogen removal reactors, revealing intraspecies diversity variation driven by different carbon regimes, which would not have been possible with a shorter gene sequence. In summary, UltraRes-rrn enables cost-effective community profiling at genomovar-level resolution in complex ecosystems.

microbiology↗

bioRxiv2026

TEX15 safeguards neuronal diversity in the mouse olfactory system

Animals detect diverse chemicals using hundreds of chemoreceptor proteins. In many organisms, sensory chemoreceptors obey a one-receptor-type-per-cell rule, which organizes information gathered by sensory neurons. A key question remains how receptor expression gets diversified so that hundreds of chemoreceptors get expressed across the population of sensory neurons. Here we show that diverse odorant receptor (OR) expression in mice requires testis expressed gene 15 (Tex15). We find that Tex15 regulates OR expression in neuronal precursor cells. In Tex15 deficient (Tex15-/-) mice, OR transcript levels are increased in precursors, a handful of early-transcribed OR genes get expressed at abnormally high levels, and these ORs come to dominate the olfactory sensory neuron population. This results in a profound reduction in the diversity of OR gene choice as well as disrupted spatial patterning of the olfactory epithelium, without disrupting the one-receptor-type-per-cell rule. Tex15 encodes a transcriptional repressor, and we show that Tex15-/- mice have reduced heterochromatin-associated H3K9me3 on OR genes. Thus, we propose that Tex15 directs a heterochromatin-based transcriptional repression mechanism that prevents uneven transcriptional onset from skewing OR choice. This mechanism safeguards the cellular diversity that is essential for broadly tuned chemosensation.

genomics↗

bioRxiv2026

The Function of LncRNA DRIR in Freezing Tolerance by Promoting Autophagic Degradation of CP29A and CP29B to Alter Alternative Splicing Patterns of Pre-mRNAs

O_LIResearch on the functions and molecular mechanisms of long non-coding RNAs (lncRNAs) involved in regulating plant freezing tolerance is still in its infancy. Our previous research work identified that lncRNA DROUGHT INDUCED LNCRNA (DRIR) regulates gene expressions in Arabidopsis. However, the underlying molecular mechanism is still unknown. C_LIO_LIThis study demonstrates that lncRNA DRIR regulates plant freezing tolerance by affecting alternative splicing patterns of pre-mRNAs. C_LIO_LIThrough chromatin isolation by RNA purification followed by mass spectrometry (ChIRP-MS), we identified two DRIR interacting proteins: CP29A and CP29B. We showed that the drirD mutant, which exhibits elevated DRIR expression and DRIR overexpression lines showed increased sensitivity to freezing stress, whereas DRIR RNAi lines were more tolerant to the stress. CP29A and CP29B bind to nuclear transcripts and, together with DRIR, regulate pre-mRNA alternative splicing under freezing stress. Notably, DRIR induces the relocalization of CP29A and CP29B to autophagosomes, leading to autophagy-mediated protein degradation. C_LIO_LICollectively, our findings elucidate the molecular mechanism by which DRIR influences the autophagy-based degradation of its binding proteins CP29A and CP29B, thereby regulating plant freezing tolerance by altering the alternative splicing patterns of pre-mRNAs, providing novel insights into the functions and mechanisms of lncRNAs in plants adapting to freezing environments. C_LI

plant biology↗

bioRxiv2026

Integrated optimization of experimental and computational workflows improves genome recovery in long-read gut metagenomics

Short-read metagenomic sequencing has been widely applied in microbial research due to its high quality and decreasing cost. However, short reads are inherently fragmented, which limits assembly contiguity and the recovery of complete microbial genomes. In contrast, long-read sequencing, with significantly longer read lengths, helps overcome these limitations. Achieving complete and accurate genome recovery is the core goal of metagenomics. To address this challenge, we systematically evaluated and optimized the long-read metagenomic workflow, from sample processing to computational assembly, using the CycloneSEQ platform.

bioinformatics↗

bioRxiv2026

TKI-Tolerant Persisters Emerge from a PKCα-Dependent and Highly Plastic Subpopulation of Stem-Like Cells in NSCLC

Reversible drug-tolerant persister states are emerging as key drivers of limited therapeutic durability, offering a complementary non-genetic perspective distinct from traditional models of acquired resistance. This is of particular interest in lung adenocarcinoma where EGFR tyrosine kinase inhibitors (TKIs) elicit dramatic responses, yet residual surviving cells persist and ultimately seed relapse. To define mechanisms that enable survival during this earliest residual-disease phase, we focused on the drug-tolerant persister population that remains after EGFR TKI exposure and can later give rise to outgrowth. Initial observations of elevated transcript levels of PRKCA, which encodes PKC, in established TKI-resistant models, together with markedly delayed tumor relapse following PKC suppression in vivo, nominated PKC as a candidate regulator of the persister-to-relapse transition. Genetic ablation of PRKCA or its inhibition with enzastaurin reduced residual survival and outgrowth after TKI exposure, indicating that PKC functions as an early dependency of drug-tolerant persisters rather than as a general mediator of acquired resistance. Mechanistically, PKC was required for persister-associated EMT, migratory capacity, and robust induction of ALDH1A1, the latter constraining oxidative stress and enhancing persister survival. Functionally, PKC was specifically necessary for survival of a rare, pre-existing CD44High stem-like subpopulation that exhibited marked plasticity and ultimately seeded persistence. Together, these data identify a PKC-dependent EMT/stemness/ROS pathway as a critical survival program in EGFR TKI-tolerant persister cells and support therapeutic strategies aimed at eliminating residual disease to prolong clinical responses.

cancer biology↗

bioRxiv2026

A Synthetic Platform for Antibody Junctional Diversification Beyond Natural Constraints

Antibody junctional diversity in jawed vertebrates arose from RAG transposon domestication, generating CDR3-focused V(D)J recombination with lymphocyte specificity--a constrained system limiting engineered antibody diversity. To overcome these limitations, we developed ARESEC (Antibody Reprogram and Expression System in Engineered Cells), a synthetic platform that enables programmable V(D)J recombination in non-lymphoid HEK293T cells. Through engineered recombination signal sequences (RSS) and optimized RAG1/2 expression, ARESEC enables RSS-guided DNA recombination across all three complementarity-determining regions (CDR1/2/3). Co-expression of terminal deoxynucleotidyl transferase (TdT) enhanced junctional sequence diversity by 41.5-86.3% across 3 CDRs. The platform enables native IgG production by coupling mammalian surface display with FACS-based functional screening. Using clinical-grade antibodies (Nivolumab and Durvalumab) as high-affinity starting scaffolds, we achieved further efficient affinity maturation through focused CDR diversification (library complexity >103). From these diversification libraries, we identified optimized variants including the anti-PD-L1 Dur1 with 2.01-fold enhanced binding, demonstrating the systems capacity for rapid antibody optimization from minimal diversity sampling. Collectively, ARESEC establishes a synthetic paradigm that transcends natural V(D)J constraints, generating multi-CDR diversification in non-lymphoid cells to enable rapid discovery of affinity-matured antibodies, effectively bridging immune evolution with modern antibody engineering demands.

synthetic biology↗

bioRxiv2026

A Comprehensive Computational Model of the Human head for Designing and Optimizing Visual Brain-Machine Interfaces

Brain-machine interfaces (BMIs) for vision restoration require models that accurately simulate the anatomy and electrical properties of visual pathways. However, current models focus only on isolated structures, such as the retina or brain, and overlook surrounding tissues. Here, we present a comprehensive computational model of the human head, incorporating the entire visual pathway--including the eye, optic nerve, and brain--along with critical neighboring tissues such as the orbit, paranasal sinuses, enabling precise simulations. Validation using human and large animal data demonstrated a strong correlation between the simulated and measured electrical potentials. Component elimination analysis revealed that the optimized comprehensive model outperformed simplified versions. The models utility was demonstrated through multiple applications: (1) comparative analysis of electrical neuromodulation technologies for optic neuropathy, revealing the filed intensity limitations of noninvasive approaches and the safety concerns of invasive intraorbital approach; (2) identification of optimal stimulation site, revealing that transnasal stimulation at the optic chiasm outperformed traditional approaches; and (3) in silico design of electrode arrays for optic nerve prosthetics, demonstrating theoretical advantages in invasiveness and visual field coverage compared to existing retinal and cortical prosthetics. This validated and versatile computational resource supports the development of neuromodulation strategies and visual BMI technologies.

bioengineering↗

bioRxiv2026

The P3018S disease variant reveals how dynein's trailing motor sets ensemble velocity.

Mutations in the cytoplasmic dynein heavy chain (DYNC1H1) underlie a range of neurodevelopmental disorders yet how individual variants perturb dynein function remains poorly understood. We characterize the disease-associated P3018S mutation, located in the AAA4 module and within the Lis1-interacting region of the motor. Dynein-dynactin-BicD2 (DDB) complexes containing P3018S dynein move at half the wild-type velocity and generate reduced stall forces but retain the ability to assume the inhibitory phi conformation that Lis1 suppresses, respond to Lis1, and assemble into higher-order force-generating states. Several Schizosaccharomyces species, which lack Lis1, naturally encode a serine at this position, suggesting evolutionary relevance for dynein activation. Using mixed wild-type-mutant assemblies, we find that the dynein occupying the trailing position on dynactin dictates ensemble velocity, and that the leading dyneins LIC enhances trailing-motor velocity by [~]130%, revealing a mechanism for leading-to-trailing motor stimulation within multi-dynein assemblies.

biophysics↗

bioRxiv2026

Large-Scale Assessment of NF1 Single Amino Acid Variants as HLA Class I Neoantigens

Neoantigens are cancer-specific antigens arising from genomic alterations. Single Amino Acid Variants (SAAVs) represent a primary class of these neoantigens. To evaluate the therapeutic potential of Neurofibromin 1 (NF1)-derived SAAVs - given that NF1 is frequently mutated in malignant brain tumors - we prioritized the 40 NF1 SAAVs determined to be HLA-A*02:01 binders using computational prediction coupled with experimental validation. To validate these predicted neoepitopes, we employed a two-tiered experimental approach in HLA-A*02:01 homozygous U87-MG cells. We first synthesized minigene constructs encoding the predicted neoepitopes, introduced them via lentiviral transfection and confirmed their expression by mass spectrometry (MS). Subsequently, we performed endogenous validation using pan-HLA immunoprecipitation mass spectrometry (IP-MS), confirming 4 (10 neoepitopes) of the 40 candidate SAAVs. We observed a discrepancy between in silico predictions and the observed sequences. Our endogenous peptidomics further revealed conserved peptide motifs and demonstrated that peptide selection for HLA presentation is transient. While our study substantiates the therapeutic feasibility of T-cell immunotherapies targeting NF1 mutations, these results underscore a limitation in current computational prediction. Our study highlights the necessity of experimental validation to refine neoantigen prioritization strategies.

immunology↗