Biology subjects

Davis, J.

Publications and source records attributed to Davis, J..

At least 19 recordsLinked to original sources

bioRxiv2026

A learned oral signal drives long-lasting thirst satiation

Drinking quenches thirst long before the ingested water has been absorbed. Here we investigate the mechanism by combining sham drinking, which uncouples water ingestion from rehydration, with recordings of thirst-promoting neurons in the brain. We show that sham drinking suppresses thirst and rapidly inhibits thirst-promoting neurons despite no water absorption. Remarkably, this suppression of thirst neurons in the absence of rehydration is proportional to the amount of water consumed and persists for tens of minutes after drinking has stopped. This sustained inhibition is triggered by passage of water through the oral cavity, but not licking or swallowing alone, and undergoes extinction with repeated sham drinking, indicating it is learned. Complementary experiments using hypertonic saline demonstrate this learning is bidirectional. These findings reveal that the experience of rapid thirst quenching is not a hard-wired response to the consumption of water, but rather a learned prediction of future bodily state.

neuroscience↗

bioRxiv2026

Bispecific GD2xB7-H3 Antibody Improves Tumor Targeting and Reduces Toxicity while Maintaining Efficacy for Neuroblastoma

The current treatment regimen for neuroblastoma involves immunotherapy, including a monoclonal antibody that recognizes disialoganglioside (GD2), expressed at high levels on neuroblastoma. GD2 is not present on most normal tissues except for nerves. Thus, anti-GD2 antibody treatment causes substantial, dose-limiting neuropathic pain. B7-H3 is overexpressed on multiple tumor types, including neuroblastoma, and is largely absent on nerves and other normal tissues. We designed a bispecific antibody (bsAb) that requires simultaneous binding of these two tumor antigens to achieve tight binding of tumor cells. Our preclinical research shows that, compared with a monospecific anti-GD2 antibody, the GD2xB7-H3 bsAb has improved tumor specificity, comparable antitumor efficacy, and reduced nerve binding and pain-associated toxicity. Since this bsAb does not bind to nerves, it may permit more tolerable and sustained treatment schedules than are currently feasible with monospecific anti-GD2 antibodies. In addition, its enhanced tumor specificity may support future development as a targeted delivery platform for antibody-drug conjugates or other payload-based therapies, potentially improving both efficacy and quality of life for patients with neuroblastoma.

cancer biology↗

bioRxiv2026

Spatial/molecular heterogeneity and treatment response in HER2+ early breast cancer: Translational analyses from the DAPHNe trial

Given the heterogeneity of HER2-positive breast cancer, reliable biomarkers to guide treatment are needed. We conducted multi-platform biomarker analyses of baseline tumor tissue from the DAPHNe trial of neoadjuvant paclitaxel/trastuzumab/pertuzumab (THP) for HER2-positive early breast cancer to characterize inter- and intra-tumor heterogeneity and to identify molecular predictors of response. A total of 98 patients with stage II-III HER2-positive breast cancer received neoadjuvant THP followed by surgery. Gene expression profiling, spatial protein profiling, and single-cell imaging (cyclic immunofluorescence) were performed on pre-treatment biopsies and a subset of residual disease specimens. Pathologic response was assessed using the residual cancer burden (RCB) score. Among HER2-positive patients included in the biomarker analysis, 34% of patients had node-positive breast cancer, and 66% had hormone receptor (HR)-positive tumors. HR-positive and HR-negative tumors differed significantly across gene expression, protein expression, and single-cell profiling. High ERBB2 gene signature, p53 gene signature, and HER2 protein expression predicted favorable response (RCB 0/1), while ESR1/PGR gene, estrogen receptor (ER) signaling gene signature, and ER alpha protein expression were associated with unfavorable response (RCB 2/3). Single-cell spatial analysis revealed that cancer cells clustered by shared HER2, ER, and PR expression, suggesting local expansion of phenotypically distinct subpopulations. ER-positive cancer cells were associated with lower HLA-A and PD-L1 expression, suggesting a less immunologically active tumor cell state. Baseline HER2 and ER expression are key predictors of response to neoadjuvant HER2-targeted therapy. Single-cell spatial profiling highlights intra-tumoral heterogeneity and suggests ER-driven immune exclusion as a potential mechanism of resistance.

cancer biology↗

bioRxiv2026

The Dilated Cardiomyopathy E525K β-Myosin Mutation Causes Hypocontractility in Cardiomyocytes Without Altering Crossbridge Cycling

The cardiac {beta}-myosin (MYH7) mutation E525K was identified in 2012 in a patient with dilated cardiomyopathy (DCM). Work using engineered constructs has shown that this mutation stabilizes the interacting heads motif (IHM) of myosin and increases the ATPase activity of mutant motor S1 heads. However, no measurements have been made in myofilaments or cardiomyocytes to determine its effect on contractile function. Here, we present force and contractile kinetics measurements from induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) engineered for heterozygous expression of E525K. Single-cell contraction for E525K hiPSC-CMs decreased by 65%, and isometric twitch force in engineered heart tissues (EHTs) decreased by 39%. In contrast, maximal Ca2+ activated isometric force in isolated myofibrils increased by 45% and sub-maximal Ca2+ activated force was similar to WT myofibrils. Structural analysis revealed reduced myofibril content (13.7% decrease) and decreased organization (increased z-disk dispersion angle) in E525K cells. We confirmed that E525K S1 myosin has higher actin affinity than WT S1 and elevated ATPase activity. However, there was no change in S1 ADP release rate. There was also no change in either the rate of force development or relaxation in myofibrils, cells, or EHTs. These findings suggest that E525K myosin crossbridge cycling is not altered during loaded contractions. To understand how twitch force of myocytes was reduced but maximal isometric force was increased, we used a spatially explicit sarcomere model. The results were explained by changing three rates: reduced recruitment from the OFF/IHM state, and increased rates of actin binding and Pi release. Additional force deficits in cells and EHTs likely result from the myofibrillar disorganization. This study demonstrates the value of multi-scale analysis and coupled, computational modeling to understand the molecular mechanisms of sarcomere mutations in cardiomyocytes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/733270v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1a64b4aorg.highwire.dtl.DTLVardef@98f053org.highwire.dtl.DTLVardef@c9f839org.highwire.dtl.DTLVardef@1c795c6_HPS_FORMAT_FIGEXP M_FIG C_FIG A model for how the E525K mutation impacts contracting myofibrils Here, we show that the E525K mutation impacts contraction in multiple ways: (1) Decreased sarcomere organization in cells and tissues drives decreased force generation. (2) Increased binding affinity of E525K myosin for actin and faster Pi release contributes to increased force generation in isolated myofibrils. (3) Increased IHM stability reduces twitch force. (4) The rate-limiting step of loaded crossbridge cycling, ADP release, is unchanged by the E525K mutation, and the rates of loaded contraction and relaxation are unchanged at all scales of contraction.

biophysics↗

bioRxiv2026

Nitrogen adaptation and phenotypic transitions from wild to improved sorghum

Crop domestication and subsequent improvement under modern agronomic conditions have altered the nitrogen (N) regimes experienced by crops, yet how selection has reshaped the genetic architecture of phenotypic responses to N availability remains poorly understood. Here, we integrated population genomic analyses of n = 289 sorghum accessions spanning multiple stages of domestication and improvement with N-response (NR) trait-associated variants identified through genome-wide association studies (GWAS) of phenotypic data collected under two contrasting N conditions in n = 347 diverse sorghum accessions. Unlike maize and sunflower, sorghum showed a reduced deleterious burden both genome-wide and within historically balanced and recently selected regions following domestication and improvement. Additionally, we identified 470 trait-associated loci (TALs), including 273 associated with NR traits. The effects of these NR-associated loci showed no apparent bias toward derived alleles, suggesting that selection on NR traits in sorghum has not been sufficiently strong or directional to consistently overcome genetic drift. Together, these results reveal distinct patterns of selection in sorghum and provide promising genetic targets for improving N-use efficiency in sustainable agricultural systems.

genomics↗

bioRxiv2026

Mouse models with human antibody repertoires for inducing multiple lineages of HIV-1 broadly neutralizing antibodies

The complementarity determining region (CDR) 1, 2 and 3 of antibodies are the principal antigen contact sites. The heavy chain CDR3 (CDR H3) is highly variable, because it includes random nucleotide additions by the terminal deoxynucleotidyl transferase (TdT). Some broadly neutralizing antibodies (bnAbs) against the human immunodeficiency virus-1 (HIV-1) rely heavily on CDR H3 to recognize conserved epitopes on HIV-1 Envelope (Env) protein. Elicitation of comparable bnAbs is a prime goal of HIV-1 vaccine development, but the shortage of precursor antibodies with suitable CDR H3s in human repertoire is a major challenge for immunogen design. To aid this effort, we generated six mouse models for inducing bnAbs against major HIV-1 Env epitopes. In each mouse model, the immunoglobulin heavy and light chain loci were engineered to predominantly rearrange the germline V, D and J segments of a bnAb lineage. Owing to CDR3 diversity, only a small subset of the V(D)J recombination products may encode variable regions that can engage bnAb epitopes with sufficient affinity to initiate immune response. Therefore, these mouse models can be used to test and optimize immunization strategies to induce bnAbs from rare and diverse precursors in complex antibody repertoires.

immunology↗

bioRxiv2026

Maturation of HIV-1 neutralizing antibodies in a germinal center conditional expression mouse model

In germinal centers, activated B cells modify their antigen receptors through somatic hypermutation (SHM), followed by antigenic selection that favors expansion of high affinity B cells. The affinity maturation process is critical for development of broadly neutralizing antibodies (bnAbs) against the human immunodeficiency virus-1 (HIV-1). BnAbs have been isolated from some people living with HIV-1. Because these antibodies target conserved epitopes of the HIV-1 Envelope (Env) protein, they inhibit a broad spectrum of viruses. Eliciting bnAbs by vaccination is a top priority for HIV-1 prevention, but reproducing the lengthy maturation of bnAbs is a major challenge. The problem is typified by VRC01 class antibodies, which recognize the CD4 binding site of HIV-1 Env protein. To reach the CD4 binding site, antibodies need to navigate through adjacent glycans. Accommodating the glycans requires multiple SHMs in germinal center (GC) B cells, including infrequent events. For this reason, VRC01 vaccine development often stalls at this point. We have generated a mouse model aimed at providing a potential solution for navigating this vaccine design impediment. To this end, we made a mouse model that expresses a stalled VRC01 intermediate conditionally in GC B cells. This system has three advantages: 1) direct expression of the intermediate obviates prior immunization steps, thereby shortening the immunization scheme; 2) the conditional expression system bypasses tolerance control checkpoints that sometimes delete B cells expressing bnAbs; 3) the intermediate responds to immunization in GCs, the physiological site of affinity maturation. With this model, we established an immunization method to mature the VRC01 intermediate into heterologous neutralizing antibodies against viruses with a native glycan shield. Since high mutation load is common among bnAbs, the germinal center conditional expression system could provide a general tool for boost immunogen design to overcome roadblocks in the maturation pathway. Author summaryIn response to antigenic stimulation, cognate B cells become activated and form germinal centers in lymphoid tissues. Germinal center B cells modify their antigen receptors through somatic hypermutation (SHM) of immunoglobulin variable region gene exons, with antigen selecting for high affinity B cells by providing survival advantage. This mechanism accounts for antibody affinity maturaton over the gradual course of an immune response. Affinity maturation is critical for generating potent, neutralizing antibodies against diverse strains of the human immunodeficiency virus-1 (HIV-1). These broadly neutralizing antibodies (bnAbs) are heavily mutated, reflecting lengthy affinity maturation over years of chronic infection. Recapitulating the affinity maturation process is a major challenge for bnAb induction by vaccination. In immunization experiments, bnAb development often stalls at rate limiting steps that involve infrequent, but functionally important, mutational events. Overcoming such obstacles requires boost immunogens that can stimulate the stalled B cells to acquire the requisite mutations. To this end, we recapitulated the maturation arrest of a bnAb lineage by expressing a stalled antibody in mouse germinal center B cells. Using this mouse model, we developed boost immunization conditions that advanced the antibody maturation beyond a roadblock to attain neutralizing activities against heterogenous viruses.

immunology↗

bioRxiv2026

UniST: A Unified Computational Framework for 3D Spatial Transcriptomics Reconstruction

Spatial transcriptomics (ST) enables the measurement of gene expression in its native spatial context, yet most ST datasets are acquired as two-dimensional (2D) sections. Consequently, the underlying three-dimensional (3D) organization of tissues is only partially observed, and 3D ST data generated from serial sections are typically sparse and heterogeneous, with substantial tissue loss and missing measurements. These limitations pose major analytical challenges for reconstructing coherent 3D tissue architecture, rather than issues of experimental scalability alone. Here, we present UniST, a unified generative artificial intelligence (AI) framework designed to computationally reconstruct dense and continuous 3D ST landscapes from sparse serial sections, without altering the underlying experimental ST technologies. UniST integrates three complementary modules: kernel point convolution with cross-attention layers for point cloud upsampling, optical flow-based interpolation for continuous slice reconstruction, and a graph autoencoder with implicit neural representations for gene expression imputation. Together, these components densify sparse slices, resolve discontinuities, and map spatial coordinates to high-dimensional transcriptomics. Across multiple ST platforms and tissue contexts, UniST accurately restored structural continuity and biologically meaningful expression patterns. In a mouse embryo dataset, UniST reconstructed a dense 3D heart architecture from sparsely sampled slices. In two 3D human cancer tissues, UniST recovered critical spatial features, including tumor-immune boundaries and tertiary lymphoid structures, that were fragmented in the original data. By providing a generalizable computational solution that complements existing ST acquisition protocols, UniST facilitates cost-efficient and scalable reconstruction of 3D ST landscapes, enabling more faithful investigation of tissue organization and disease biology.

bioinformatics↗

bioRxiv2026

Combining Anion Exchange and Size Exclusion Chromatography for Extracellular Vesicle Enrichment from Small Volumes of Human and Mouse Plasma for Quantitative Proteomics

Extracellular vesicles (EVs) are promising biomarkers, yet their proteomic analysis from plasma is hampered by low abundance and co-purification of contaminants (e.g., lipoproteins, platelets) and technical variability, particularly in small-volume animal models. We developed and validated a modular protocol integrating Size Exclusion Chromatography (SEC) with Strong Anion Exchange (SEC-SAX) specifically tailored for quantitative LC-MS proteomics from small starting volumes (150 l of plasma). SEC alone successfully removed 99% of Albumin, and the SAX step significantly enriched EVs over contaminating lipoproteins. Downstream single pot solid phase enhanced (SP3) sample prep and STAGE tip solid phase extraction ensured maximum proteome depth. Critical confounding factors were objectively assessed: Platelet Factor 4 (PF4) was confirmed as a highly sensitive platelet marker, confirming the necessity of meticulous plasma preparation. Sample hemolysis impacted the plasma EV proteome data. As such, an objective measure (nanodrop spectrophotometer) of hemolysis and exclusion of hemolysed samples (heme >0.3 mg/ml) is recommended. The protocol is applicable to both human and mouse plasma as demonstrated by EV enrichment and quantification of biomarker proteins associated with neurodegenerative diseases from eight individual mouse plasma samples. Manuscript HighlightsO_LIDevelopmental workflow for a quantitative SEC-SAX protocol for EV proteomics from small plasma volumes (150 l). C_LIO_LIA range of variables tested including SAX beads amount, digestion buffer, digestion time, STAGE tip solid phase extraction, SAX elution buffer and sample filtration. C_LIO_LIThe SAX step significantly enhances EV proteome depth by increasing EV purity in relation to ApoB lipoproteins. C_LIO_LIShows the impact of the major confounding factors of sample hemolysis and platelet contamination on the EV proteome. C_LIO_LIPlatelet contamination increases the number and abundance of proteins detected including known disease biomarkers and sample hemolysis is associated with proteins derived from platelet and red blood cell derived EVs. C_LIO_LIPlatelet Factor 4 (PF4) is identified and confirmed as a sensitive marker for platelet contamination. C_LIO_LIApplicable to both human and mouse plasma. C_LI

molecular biology↗

bioRxiv2026

Leveraging Large Language Models to Extract Prognostic Pathology Features in Ewing Sarcoma

BackgroundCurrent risk stratification for Ewing sarcoma relies heavily on clinical factors such as metastatic status, failing to capture histologic heterogeneity as a potential prognostic indicator. Although pathology reports contain rich biological data, this information remains locked in unstructured narrative text, limiting large-scale retrospective analyses. We aimed to validate the utility of Large Language Models (LLMs) for scalable data abstraction and to identify prognostic histologic features from a large multi-institutional cohort. MethodsWe conducted a retrospective cohort study using data from six Childrens Oncology Group (COG) clinical trials. We utilized an LLM-based pipeline (OpenAI o3) to extract structured variables--including immunohistochemical (IHC) markers and CD99 staining patterns--from digitized, Optical Character Recognition (OCR)-processed pathology reports. Extraction accuracy was validated against a human-annotated ground truth (n=200) and cross-validated against senior experts (n=48). We assessed the association between extracted features and Overall Survival (OS) using Kaplan-Meier analysis and multivariable Cox proportional hazards regression, adjusting for metastatic status. FindingsWe analyzed 931 diagnostic pathology reports from 185 institutions spanning over 21-years. The LLM achieved a weighted average accuracy of 94% across 17 IHC markers; in a cross-validation subset, the LLM outperformed human annotators (weighted average accuracy over 15 IHC markers: LLM o3: 98.1%, a pediatric resident 91.4%, and a pediatric oncologist 95.9%). Survival analysis identified Neuron-Specific Enolase (NSE) and S100 as significant prognostic biomarkers. After adjusting for metastatic status, NSE positivity was associated with significantly inferior survival (HR 2.15, 95% CI 1.15-4.02, p=0.016); this risk was most pronounced in patients with non-metastatic disease (HR 5.64, p=0.0055). Conversely, S100 positivity was associated with improved survival (HR 0.58, 95% CI 0.34-1.00, p=0.046). InterpretationLLM-assisted extraction of pathology variables is highly accurate and scalable, capable of unlocking "dark data" from historical clinical trials. We identified NSE as a potent risk factor and S100 as a protective marker in Ewing sarcoma, particularly in localized disease. These findings suggest that AI-derived histologic data can refine risk stratification and, if validated, warrant inclusion in future prospective trials. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and Google Scholar for articles published up to December 2025, using terms such as "Ewing sarcoma", "prognosis", "risk stratification", "large language models", "natural language processing", and "pathology report extraction". Current risk stratification for Ewing sarcoma relies predominantly on clinical variables, specifically the presence of metastatic disease and tumor size. While histologic heterogeneity is well-documented, it is rarely incorporated into risk models because extracting structured data from narrative pathology reports is labor-intensive. Small, single-institution studies have suggested potential prognostic roles for markers like Neuron-Specific Enolase (NSE) or S100, but results have been inconsistent and limited by small sample sizes. Furthermore, while Large Language Models (LLMs) have demonstrated potential for extracting clinical data, their application to "rescue" data from legacy, multi-institutional clinical trial documents (scanned PDF images) for rare disease biomarker discovery has not been validated at scale. Added value of this studyTo our knowledge, this is the largest study to utilize AI to extract histologic data from Ewing sarcoma pathology reports, aggregating 931 patients from six distinct Childrens Oncology Group (COG) clinical trials spanning over 21 years. We validated an LLM-based pipeline that converted noisy, optically character-recognized text from diverse institutions into structured data with 98.1% accuracy, outperforming human annotators. This scalable approach revealed that NSE positivity is a significant independent risk factor for mortality (HR=2.15), particularly in patients with non-metastatic disease where it confers a more than 5-fold increased risk of death. Conversely, we identified S100 positivity as a protective factor associated with improved survival (HR=0.58). Implications of all the available evidenceThis study demonstrates that LLMs can reliably unlock "dark data" from historical clinical trials, rendering vast archives of unstructured medical documents accessible for retrospective analysis. The identification of NSE and S100 as robust prognostic biomarkers suggests that these widely available immunohistochemical stains provide valuable information beyond standard diagnostic information. These findings support the integration of automated data extraction tools in research workflows and suggest that NSE and S100 status should be considered in the design of future risk-stratified clinical trials for Ewing sarcoma.

bioinformatics↗

bioRxiv2025

Identification and characterization of host-modulating effectors encoded by the Cluster F1 mycobacteriophage NormanBulbieJr

NormanBulbieJr (NBJ) is a temperate siphovirus isolated on the host Mycobacterium smegmatis mc2155 that encodes 102 gene products, 60 of which have no known function (NKF). Based on gene content, NBJ is classified as a Cluster F, Subcluster F1 phage and shares 70% of its encoded gene phamilies with Girr, another F1 mycobacteriophage that was recently analyzed in a genome-wide overexpression screen and found to encode 29 diverse gene products capable of inhibiting growth of M. smegmatis. Similar functional screens in other mycobacteriophages have uncovered a growing repertoire of diverse, phage-encoded bacterial growth inhibitors, providing prime candidates for dissecting novel bacterial-phage interactions. An arrayed overexpression library encoding all 102 genes was constructed and systematically screened using a plate-based cytotoxicity assay, identifying 29 genes that inhibit mycobacterial growth. Because mycobacteriophage genomes are also known to encode systems involved in phage-phage competition, we conducted additional phage defense assays for a subset of NBJ genes in our library. This analysis confirmed homotypic immunity by the predicted immunity repressor and identified gp45 as a second defense factor that protects against Cluster F phages and promotes NBJ lysogen stability. Additional mechanistic analyses indicate that gp45 functions in a secretion-dependent manner, acting after phage adsorption to reduce productive infection and early phage transcript accumulation. Escape mutant and bacterial two-hybrid analyses implicate Cluster F tape measure proteins as the likely target of gp45, consistent with disruption of an early step in phage genome delivery. Finally, we extended our analysis to explore the essentiality of all identified host-modulating genes in the NBJ life cycle, using CRISPR-enhanced recombineering to generate phage deletion mutants, revealing two host modulators that are critical for lytic growth. Conducted as part of the SEA-GENES undergraduate research consortium, this study adds to a growing functional genomics resource and provides new insights into the complex interactions between phage gene products and the mycobacterial host cell.

microbiology↗

bioRxiv2025

Conformational State of Myosins Disordered Loop 2 Structure Mediates Actomyosin Association During Crossbridge Formation

The binding of myosin to actin to form crossbridges is a critical step for force generation by sarcomeres. A recent cryo-electron microscopy structure has resolved the weakly-bound actomyosin complex (AM.ADP.Pi); however, the structural and dynamic factors that influence actin-myosin association are unclear. The disordered loop 2 of myosin is thought to mediate actomyosin interactions in complex, chemomechanical state-dependent fashion; however, the loop is usually unresolved in structural studies due to its intrinsic disorder. Here, we utilize a combination of molecular dynamics simulations and electrostatic calculations to investigate the dynamics of these actin binding regions of myosin. Our results show that loop 2 experiences disordered dynamics and that specific conformations sampled by loop 2 modulate the strength of the associative electrostatic force between actin and myosin. Variation in the actin-myosin associative force was associated with the presentation and orientation of positively charged residues in loop 2. We provide an in-depth analysis of the conformational state space occupied by loop 2 during nine 500 ns molecular dynamics simulations of pre-powerstroke human {beta}-myosin S1, with three replicates each of wildtype and two different mutant (E525K and V606M) myosin structures. This dataset allowed for exploration of how loop 2 conformational sampling is altered by these two mutations which have been clinically and experimentally associated with cardiomyopathy and altered actin binding affinity. The E525K and V606M mutations altered the conformational ensemble sampled by loop 2 and were associated with associative actin binding strength. These results highlight the importance of the positive charges on loop 2 for actomyosin interactions and demonstrate how disease-causing mutations outside of loop 2 can still affect it.

molecular biology↗

bioRxiv2025

Skeletal muscle TDP-43 aggregation drives progressive motor dysfunction and neurodegeneration with potential for functional recovery after clearance

Understanding the mechanisms driving TDP-43 pathology is essential for combating amyotrophic lateral sclerosis and other neurodegenerative diseases. To investigate the contribution of skeletal muscle to disease onset, progression, and recovery, we generated an inducible, muscle-specific TDP-43 mouse model. Cytoplasmic aggregation of exgogenous human TDP-43 protein in skeletal muscle led to muscle dysfunction, denervation, motor neuron loss, and dysregulation of mRNA markers related to myogenesis and neuromuscular junction stress at disease early-stage, along with muscle atrophy, neurodegeneration, and fatal motor decline at disease late-stage. Notably, this endogenous TDP-43 propagated from skeletal muscle to the spinal cord and brain, underscoring the vulnerability of the central nervous system to muscle-derived TDP-43 toxicity. Suppression of cytoplasmic TDP-43 in skeletal muscle improved survival and promoted substantial recovery of muscle dysfunction, motor deficits and neurodegeneration. These findings highlight the therapeutic potential of targeting skeletal muscle-derived TDP-43 toxicity as an approach to delaying neurodegenerative disease.

neuroscience↗

bioRxiv2025

Engineered yeast biofilms deliver plastic degrading enzymes to PET substrates

Enzymes that degrade PET and other plastics are being discovered with increasing pace, and engineering approaches further increase their activity. Most proposed applications for such enzymes require their purification, enabling the regeneration of monomeric subunits suitable for the production of new plastic. However, large amounts of plastics exist as environmental contaminants, and are unlikely to be suitable for standard recycling. Such waste may still be suitable for bioremediation using enzymatic activities, albeit without the economic incentives of a full recycling process. Here we develop a delivery system for PET hydrolases, based on engineered yeast biofilms that grow and secrete enzymes directly on the substrate to be degraded. The system does not require any enzyme purification steps, and the biofilms at least partially assimilate the degradation products into biomass. Our work provides proof-of-principle that demonstrates the potential of biofilm-based approaches.

bioengineering↗

bioRxiv2025

A spatially targeted metric of potential koala populations based on Bayesian Networks for conservation management

Koalas (Phascolarctos cinereus) face significant threats from habitat loss and fragmentation, with South-East Queensland (SEQ) experiencing some of the most severe population declines. Current metrics used to assess conservation impacts often lack spatial resolution, transparency, or integration of diverse data sources. We propose a novel, spatially targeted metric, Koala Population Potential (KPP), to estimate the potential number of koalas that could inhabit a given area under ideal conditions. This metric is derived from a Bayesian Network model that integrates ecological, environmental, and threat data, including satellite imagery, expert knowledge, and stakeholder input. We developed and validated the KPP within an interactive online platform, the Koala Bayesian Network Platform (KBNP), enabling stakeholders to visualise and assess the conservation impact of various management scenarios at the land-parcel scale. Application of the KPP across SEQ revealed substantial spatial variation in potential koala populations. Regional areas like Somerset and the Scenic Rim exhibited high KPP scores, while urban LGAs such as Redland City and Logan had lower scores due to elevated threat levels. Model predictions of habitat support were strongly correlated with independent habitat quality assessments (R{superscript 2} = 0.803, p < .001), supporting the validity of the approach. The KBNP provides an accessible, evidence-based decision-support tool that empowers landholders, planners, and conservation managers to evaluate and communicate the likely outcomes of their actions. While developed for koalas, this framework is adaptable to other vulnerable species requiring localised, data-driven conservation planning under uncertainty.

ecology↗

bioRxiv2025

Targeted Molecular MRI of Colorectal Cancer by Antibody Functionalized Hyperpolarized Silicon Particles

The development of non-invasive, non-ionizing sensitive molecular targeting approaches to detect colorectal cancer (CRC) lesions is warranted to improve high risk patient outcomes. Hyperpolarized silicon nanoparticles and microparticles are potentially well-suited to act as targeted molecular imaging agents because of their overall biocompatibility and long-lasting enhanced magnetic resonance imaging (MRI) signals. In this study, dynamic nuclear polarization was performed on silicon particles functionalized with an antibody to Mucin-1 (MUC1), a surface mucin glycoprotein aberrantly expressed in CRC. Antibody conjugation to the particle surface did not affect 29Si hyperpolarization characteristics. Similarly, conjugation and the dynamic nuclear polarization process did not adversely affect the affinity of the targeting antibody. In vivo MRI scans performed 10-15 minutes after luminal administration of targeted hyperpolarized particles into human MUC1-expressing orthotopic CRC mouse models showed that particles actively targeted tumor sites. These results were supported by chemical and biological controls and blocking experiments as well as correlative immunohistochemical analysis. These surface-functionalized silicon particles are under development as a platform technology that will allow non-invasive molecular targeting of CRC using hyperpolarized MRI. Single Sentence SummaryTargeted molecular MR imaging of colorectal cancer by hyperpolarized silicon particles functionalized with mucin 1 antibody.

cancer biology↗

bioRxiv2025

The costimulatory domain influences CD19 CAR-T cell resistance development in B-cell malignancies.

CD19-CAR-T-cells emerge as a major therapeutic option for relapsed/refractory B-cell-derived malignancies, however approximately half of patients eventually relapse. To identify resistance-driving factors, we repeatedly exposed B-cell lymphoma/B-cell acute lymphoblastic leukemia to 4-1BB/CD28-based CD19-CAR-T-cells in vitro. Generated models revealed costimulatory domain-dependent differences in CD19 loss. While CD19-4-1BB-CAR-T-cells induced combination epitope/total CD19 protein loss, CD19-CD28-CAR-T-cells did not drive antigen-escape. Consistent with observations in patients relapsing after CD19-4-1BB-CAR-T-cells, we identified CD19 frameshift/missense mutations affecting residues critical for FMC63 epitope recognition. Mathematical simulations revealed that differences between CD19-4-1BB- and CD19-CD28-CAR-T-cells activity against low-antigen-expressing tumor contribute to heterogeneous therapeutic responses. By integrating in vitro and in silico data, we propose a biological scenario where CD19-4-1BB-CAR-T-cells fail to eliminate low-antigen tumor cells, fostering CAR-resistance. These findings offer mechanistic insight into the observed clinical differences between axi-cel (CD28-based) and tisa-cel (4-1BB-based)-treated B-cell lymphoma patients and advance our understanding on CAR-T resistance. Furthermore, we underscore the need for specific FMC63 epitope detection to deliver information on antigen levels accessible for CD19-CAR-T-cells. Visual abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/640707v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1728c4org.highwire.dtl.DTLVardef@759660org.highwire.dtl.DTLVardef@1e3a0deorg.highwire.dtl.DTLVardef@15653e4_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Neuronal cell adhesion molecule (NRCAM) variant defined by microexon skipping is an essential, antigenically distinct, and targetable surface proteoform in high-grade glioma

To overcome the paucity of known tumor-specific surface antigens in pediatric high-grade glioma (pHGG), we contrasted splicing patterns in pHGGs and normal brain samples. Among alternative splicing events affecting extracellular protein domains, the most pervasive alteration was the skipping of [≤]30 nucleotide-long exons. Several of these skipped microexons mapped to L1-IgCAM family members, such as NRCAM. Bulk and single-nuclei short- and long-read RNA-seq revealed uniform skipping of NRCAM microexons 5 and 19 in virtually every pHGG sample. Importantly, the {Delta}ex5{Delta}ex19 (but not the full-length) NRCAM proteoform was essential for pHGG cell migration and invasion in vitro and tumor growth in vivo. We developed a monoclonal antibody selective for {Delta}ex5{Delta}ex19 NRCAM and demonstrated that "painting" of pHGG cells with this antibody enables killing by T cells armed with an FcRI-based universal immune receptor. Thus, pHGG-specific NRCAM and possibly other L1-IgCAM proteoforms are promising and highly selective targets for adoptive immunotherapies.

cancer biology↗