Biology subjects

Xu, H.

Publications and source records attributed to Xu, H..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Glucose is a ligand-like trigger for secretion of postprandial GLP-1

Glucagon-like peptide 1 (GLP-1) is secreted from the intestinal L cells in a glucose-dependent manner. However, the mechanism underlying how glucose stimulates the secretion remains unclear. Here, we found that glucose at postprandial concentrations near the Km of GK for glucose ([~]10 mM), as well as nonmetabolizable glucose analogs, triggers GLP-1 secretion by intestinal L cells through directly binding to glucokinase (GK), without increasing intracellular ATP levels. We also show that in postprandially high glucose, glucose-bound GK interacts and inhibits KATP, as assessed by immunoprecipitation and FRET-FLIM analyses, as well as patch clamping. In addition, we have utilized GK mutants identified in diabetics, demonstrating that those mutants defective in binding to glucose impair GLP-1 secretion in however high glucose, whereas mutants constitutively bound to glucose with defects in catalysis, promote GLP-1 secretion even in low glucose. Furthermore, the KATP mutant unable to bind to GK blocks GLP-1 secretion in high glucose. We have also provided evidence showing that sodium-glucose cotransporter 1 (SGLT1) plays an important role in the basal secretion of GLP-1, but not in high glucose. We have thus revealed that glucose the molecule itself and GK act as a ligand and the receptor, respectively, to induce GLP-1 secretion in response to high glucose, providing new therapeutic avenues targeting metabolic diseases.

biochemistry↗

bioRxiv2026

Cryo-EM reveals the structural basis of subtype-specific, noncompetitive inhibition of the human P2X3 receptor

P2X receptors are ATP-gated cation channels, and the P2X3 subtype plays crucial roles in peripheral sensory neurons, including in chronic pain and chronic cough. Accordingly, P2X3 has attracted substantial interest as a therapeutic target. Gefapixant, a negative allosteric modulator (NAM) of P2X3, has been approved in some countries for the treatment of chronic cough; however, its limited selectivity for P2X3 homomers over P2X2/P2X3 heteromers is associated with taste disturbance as a prominent adverse effect. These limitations have motivated the development of next-generation NAMs with improved subtype selectivity, but their subtype-specific allosteric inhibition mechanisms are unclear. Here, we report the cryo-EM structure of the human P2X3 receptor in complex with ATP and the P2X3-selective next-generation NAM sivopixant, an investigational drug. Sivopixant binds to an allosteric site at the portal of the central pocket in the extracellular domain, and structure-based mutational analysis by electrophysiology identifies key residues required for sivopixant-dependent inhibition of human P2X3. Comparisons with P2X structures from other subtypes, together with gain-of-function mutants, define a structural basis for subtype-selective allosteric inhibition of the P2X3 receptor. Furthermore, structural comparisons with apo and ATP-bound open states of P2X3 receptors, together with molecular dynamics simulations, revealed that sivopixant expands the upper body domain to suppress the lower-body movements required for channel activation, thereby preventing channel opening even in the presence of ATP.

biophysics↗

bioRxiv2025

Multi-modal choroid plexus pathology in aging and Alzheimer's disease

Brain barriers, cerebrospinal fluid (CSF) dynamics, and peripheral factors are implicated as significant contributors to Alzheimers disease (AD). The choroid plexus (ChP) is a blood-brain interface that produces CSF and forms the blood-CSF barrier. However, how ChP pathology develops across the lifespan and contributes to AD has not been systematically characterized. Here, we report a multi-modal ChP atlas integrating single-nucleus transcriptomics from 49 individuals, AI-assisted quantitative histopathology across >500 postmortem samples age 16 to 105, spatial transcriptomics, and functional studies in 5xFAD mice. We identify fibrosis, calcification, and macrophage abnormalities as hallmarks of ChP aging, with AD pathology conferring additional effects, including expansion of a pro-inflammatory fibroblast-macrophage signaling niche. In 5xFAD mice, macrophage dysfunction is associated with impaired epithelial barrier maintenance and repair. Together, these data provide a foundational resource for understanding ChP dysfunction in aging and AD and propose the macrophage-fibroblast-epithelial barrier axis as a driver of ChP pathology.

neuroscience↗

bioRxiv2025

Temporal boundary gating of auditory sensitivity

Perception unfolds over time, but whether continuous sounds are sampled with uniform sensitivity is unknown. We combine human psychophysics, EEG and rodent neurophysiology to show that local auditory change detection is strongly gated by stimulus boundaries. In humans, brief perturbations inserted at different temporal positions within 0.5-1-s tones revealed an inverted U-shaped sensitivity profile: detection was attenuated near sound onset and offset and maximal mid-epoch, with EEG change responses showing a closely matching dependence on change timing. Electrocorticography in awake rats exhibited homologous temporal weighting, and analogous profiles for amplitude changes and visual motion demonstrated cross-feature and cross-modal generality. To uncover circuit mechanisms, we recorded single units along the inferior colliculus-medial geniculate body-auditory cortex pathway together with laminar local field potentials in A1. Onset-locked suppression of change responses emerged in midbrain and was progressively amplified in thalamus and cortex, whereas the full start-end profile was expressed in granular-layer alpha-gamma power. A simple biophysically grounded model in which onset responses saturate and cortical populations integrate over finite temporal windows recapitulates this pattern, explaining how stimulus boundaries disrupt prospective and retrospective integration and thereby degrade change detection near the beginning and end of sounds.

neuroscience↗

bioRxiv2025

Ultrahigh-Throughput Forster Resonance Energy Transfer-Activated Droplet Sorting for Terminator Polymerase Engineering

Droplet microfluidic screening systems enable high-throughput, labor-saving enzyme directed evolution by employing fluorescence, absorbance, and Raman-activated sorting strategies for library screening. Forster resonance energy transfer (FRET) - a nanoscale technique for monitoring intramolecular/intermolecular conformational changes - is yet to be integrated into this process. We upgraded a single-channel sorter to a dual-channel one without redesigning the microscopy setup, which can monitor FRET signals during enzyme reactions in droplets at kilohertz rates. We applied this upgraded sorter to improve the incorporation efficiency of KOD DNA polymerase towards reversible terminator deoxyribonucleotides, a property crucial for its application in next-generation sequencing (NGS). Our data show that a single-round sorting can achieve 30-fold enrichment of active variants. Five KOD variants enabling 100-cycle single-end runs of DNA sequencing were identified using a novel cyclic reversible termination (CRT) substrate featuring a terminator group {approx} 5-fold bulkier than the classical azidomethyl moiety. We also engineered a metagenome-derived novel polymerase, and a variant achieving 90% terminator incorporation efficiency within 2 minutes was identified after two rounds of enrichment. In sum, we provide a practical setup for dual-channel FRET-based droplet sorting, and demonstrate its ability in terminator polymerases engineering, thereby broaden the scope of microfluidic applications.

biochemistry↗

bioRxiv2025

Closing the Sim-to-Real Gap: An End-to-End Robotic Ultrasound System Leveraging In Vivo Reinforcement Learning and 3D-Prior Guided Hybrid Control

Abdominal ultrasound is a crucial first-line diagnostic tool, yet its efficacy is inherently constrained by a strong dependency on operator skill, leading to significant inter-operator variability and limiting its widespread adoption. While robotic ultrasound systems with artificial intelligence have emerged to mitigate this, current approaches face critical limitations: they often rely on simulated or phantom data for training, which hampers generalizability, and employ control strategies that lack the flexibility to adapt to complex human anatomy. To address these challenges, this paper introduces a novel, end-to-end robotic system for autonomous abdominal scanning. Our methodology is systematic: it begins with coarse scan planning via RGB and 3D point cloud-based localization of key anatomical landmarks (e.g., xiphoid process). The core of our approach involves training a reinforcement learning scanning policy directly on live human volunteers, enabling the development of a strategy that is robust to anatomical diversity. This high-level policy is executed by a sophisticated hybrid force-position controller, enhanced with real-time normal vector calibration and 3D point cloud-based respiratory phase detection to dynamically adjust contact force, particularly during inspiration. This innovation proves critical for improving scan quality in subjects with higher Body Mass Index (BMI). Extensive validation against expert sonographers demonstrates that our system achieves high precision in standard plane recognition and superior scanning efficiency. Furthermore, to holistically assess performance where standard planes are difficult to acquire, we introduce a 3D reconstruction-based coverage metric. Results confirm that our system delivers strong adaptability and significantly improved consistency, marking a substantial step toward clinically viable, operator-independent ultrasound robotics.

bioengineering↗

bioRxiv2025

Echoes as Signal, Not Noise: Reverberation Sharpens Sensitivity to Temporal Structure

Sensitivity to temporal structure is fundamental to hearing, yet how natural reverberation shapes this sensitivity is unclear. Here we identify echo-facilitated temporal sensitivity (EFTS), a principle whereby the auditory system exploits echoes to selectively enhance responses to rapid temporal changes. Using transitional click trains with subtle inter-click-interval (ICI) shifts, we first show that increasing echo strength systematically enlarges the sound-level step at ICI transitions in both recorded and simulated stimuli, sharpening the physical boundary between segments of distinct temporal structure. In humans, psychophysical detection of ICI changes improves monotonically with echo level in both simulated and real free-field environments, while a late EEG change response scales with echo strength as onset responses remain comparatively stable. In awake rats, electrocorticography over auditory cortex reveals parallel echo-dependent enhancement of transition-evoked activity. Single units exhibit echo-level-dependent amplification of change-related firing and improved neurometric discriminability. Laminar local field potential and current source density analyses further show that echo-dependent divergence emerges first in granular and infragranular layers before propagating to supragranular cortex, consistent with thalamocortical drive followed by intracortical amplification. Together, these findings establish EFTS as a cross-species mechanism that reframes echoes as structured signals the brain uses to sharpen temporal integration in everyday listening.

neuroscience↗

bioRxiv2025

Microbial community-based protein enables sustainable fishmeal replacement and improved resilience in Pacific white shrimp (Litopenaeus vannamei)

The growing demand for aquaculture feeds requires sustainable alternatives to fishmeal. Microbial community-based single-cell protein (SCP) produced from soybean-processing wastewater offers a circular approach that combines nutrient recovery with aquafeed production. We evaluated SCP as a fishmeal replacement for Pacific white shrimp (Litopenaeus vannamei) across four feeding trials lasting 42-84 days, involving shrimp from different hatcheries and SCP produced at laboratory and pilot scales. Diets containing 0-100% fishmeal replacement, corresponding to up to 220 g SCP kg-1 feed, were tested. Replacement of 50% was consistently supported across trials, while levels up to 90% maintained several key performance outcomes, including specific growth rate, feed conversion ratio, and survival, without significant differences from the fishmeal control. Complete replacement reduced growth in one trial, potentially reflecting the lower protein content and less favourable amino acid balance of SCP relative to fishmeal, particularly its lower lysine and methionine proportions. Shrimp tissue proximate and amino acid compositions showed no clear adverse responses to SCP inclusion in the trial in which they were assessed. Cross-trial analysis revealed a positive association between SCP replacement and survival after accounting for trial-specific baseline differences, with survival increasing by an estimated 1.53 percentage points for every 10-percentage-point increase in replacement (HC3 95% CI: 0.90-2.17; P < 0.001). Although the mechanisms underlying this association remain to be established, the findings support investigation of potential functional effects through targeted challenge and mechanistic studies. Overall, performance across four heterogeneous trials supports substantial fishmeal replacement by microbial community-based SCP and demonstrates its potential for practical application as a circular aquafeed ingredient.

microbiology↗

bioRxiv2025

Interpreting Convolutional Neural Networks in Population Genetics

AO_SCPLOWBSTRACTC_SCPLOWMachine learning approaches have become a powerful alternative to traditional methods in population genetics. Convolutional neural networks (CNNs) in particular have been successful in inferring natural selection, recombination rate estimation, introgression, dispersal distances, and effective population size changes. One limitation of CNNs and other deep learning methods is that they can be difficult to interpret. When they have been shown to be as or more successful than summary-statistic-based methods, what are they learning? Here we investigate CNNs from two different methods: the pg-gan discriminator for identifying real vs. simulated data, and two networks trained to detect selective sweeps. We first compute correlations between learned network features and traditional summary statistics, then assess whether summary statistics can be predicted from the learned features. To understand the learned features, we compute feature importance through SHAP values and feature groupings through dimensionality reduction. Finally we use decision trees and random forests to build an interpretable "model-of-the-model". Our results reveal that some CNN architectures can implicitly compute summary statistics such as pairwise heterozygosity, while statistics such as the site frequency spectrum are less similar to the networks learned features. We find that long-range linkage disequilibrium is readily approximated by the networks and may be more efficiently computed by CNNs than traditional methods (which are quadratic in the number of sites). Overall, this work contributes to the interpretability of deep learning methods in population genetics by clarifying the relationships between model architecture, learned network features, established summary statistics, and predicted evolutionary parameters.

genomics↗

bioRxiv2025

IgG-Bridging-Seeded Synergistic Aggregation of SARS-CoV-2 Spikes Underlies Potent Neutralization by A Low-Affinity Antibody

Mechanistic studies of viral neutralization typically prioritize high-affinity antibodies, relegating low-affinity binders to the sidelines. We report P5-1C8, a Class 1 SARS-CoV-2 antibody that exemplifies this underexplored "low-affinity yet high-potency" phenotype, retaining strong neutralization of Omicron JN.1 despite markedly weakened trimer binding (KD = 225 nM; IC50 = 0.06 nM). Structural and biophysical analyses reveal that P5-1C8 engages WT and BA.1 spikes through canonical intra-spike bivalency, but with JN.1 it induces aggregation. Using virion-like nanoparticles displaying multiple spikes, we show that IgG remains bound with no detectable dissociation and triggers pronounced aggregation. Coarse-grained molecular dynamics delineate the stepwise pathway in which weak IgG-spike contacts seed aggregation via transient inter-spike bridging. Together, these findings establish the first mechanistic framework demonstrating how weak-binding antibodies can nonetheless achieve potent neutralization through higher-order aggregation, thereby expanding the conceptual landscape of antibody function and opening new directions for antibody evaluation and design. Graphical AbstractLow-affinity antibodies are frequently disregarded in discovery pipelines. This work reports P5-1C8, a Class 1 SARS-CoV-2 antibody with weak trimer binding (KD-to-IC50 > 3,700-fold) yet potent neutralization of Omicron JN.1. Structural, biophysical, functional and coarse-grained simulations collectively demonstrate that transient inter-spike IgG bridging seeds higher-order aggregation, which in turn drives neutralization and provides a mechanistic framework. O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/691454v1_ufig1.gif" ALT="Figure 1000"> View larger version (79K): org.highwire.dtl.DTLVardef@1d4f132org.highwire.dtl.DTLVardef@1274400org.highwire.dtl.DTLVardef@e186a6org.highwire.dtl.DTLVardef@4f1870_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Fluctuating flooding motivates the facilitation of a wetland invader: a probe into the stress gradient hypothesis

Stress gradient hypothesis proposes that the plant interaction tends to convert from competition to facilitation when facing accelerating stress. The present study aims to explore the interaction between two co-existing wetland plant invaders - Alternanthera philoxeroides and Myriophyllum aquaticum with exposure to flooding stress. Different plant assemblages including monospecific (single individual per species), homospecific (two individuals of same species) and heterospecific (two individuals of different species) treatments were subjected to different flooding regimes including mesic habitat, constant flooding and fluctuating flooding. The plant interaction was evaluated by biomass accumulation, biomass allocation and relative competition intensity index (RCI). We found that the biomass accumulation and allocation of A. philoxeroides were consistent across different treatments of community assemblage and flooding regime, while the root mass, biomass and root mass allocation of M. aquaticum significantly increased at the presence of A. philoxeroides. Moreover, the RCI of M. aquaticum decreased at the presence of A. philoxeroides. Especially, the RCI of M. aquaticum was 0.06 in the homospecific community, while that of M. aquaticum was -0.82 in the heterospecific treatment under fluctuating flooding condition. Overall, Alternanthera philoxeroides facilitated M. aquaticum, especially under fluctuating flooding condition, which complies with the stress gradient hypothesis. The water level drawdown can benefit the impedance of the growth of M. aquaticum and the deceleration of the co-invasion of A. philoxeroides and M. aquaticum.

ecology↗

bioRxiv2025

Developmental deviations of structural connectivity in youths with ADHD predict symptom and treatment outcomes

Attention-deficit/hyperactivity disorder (ADHD) lacks validated biomarkers to track symptom development or guide treatment selection in youth. We quantified individual deviations from normative age-related trajectories of white-matter structural connectivity (SC) across two independent cohorts: 6,687 typically developing and 1,114 ADHD scans from the ABCD study, and 292 typically developing and 482 ADHD participants from a Chinese cohort. Youth with ADHD showed pronounced SC deviations, especially in higher-order association pathways. A subset of connections showed ADHD-specific developmental reductions in deviations beyond typical developmental patterns, and these changes mediated the age-related decline in ADHD symptoms. Longitudinal within-individual analyses demonstrated that decreases in deviation over two years tracked symptom improvement. Baseline deviations also predicted 12-week treatment response to atomoxetine, but not methylphenidate, and follow-up imaging revealed treatment-related reductions in deviation. Together, these findings identify SC deviation as a robust developmental biomarker with prognostic and theragnostic relevance for ADHD, supporting precision care through risk stratification, individualized pharmacotherapy selection, and objective monitoring of treatment effects.

neuroscience↗

bioRxiv2025

Evo2HiC: a multimodal foundation model for integrative analysis of genome sequence and architecture

Understanding how genomic sequences shape three-dimensional (3D) genome architecture is funda-mental to interpreting diverse biological processes. Although previous studies have shown that sequence information can predict 3D genome architecture, they fall short in capturing cell type-specific structures because they are trained solely on sequence inputs. The widely available Hi-C data, which contain rich structural information across biosamples, can provide complementary features to sequence data for study-ing cell type-specific architectures. Recently, DNA foundation models have demonstrated encouraging performance in capturing long-range genomic dependencies, holding promise for modeling chromatin interactions. However, the extremely high computational cost of running these models limits their applicability to Hi-C analysis, which requires genome-wide sequence embeddings. Here, we present Evo2HiC, a multimodal foundation model that jointly models genomic sequences and structures to study cell type-specific chromatin structure. The key idea of Evo2HiC is to distill a large-scale DNA foundation model, Evo 2 (7B), into a compact encoder, while guiding the distillation with Hi-C data to preserve genomic features critical for 3D genome analysis. The model supports two types of encoders, one that operates directly on DNA sequences, and a second that additionally takes as input corresponding Hi-C data. Using the DNA-only encoder and predicting Hi-C contact matrices, Evo2HiC improved Spearman correlation by 10.9% over Orca. Moreover, by jointly embedding Hi-C and sequence information Evo2HiC achieved the best overall Pearson correlation when predicting five representative epigenomic assays. Interpretation analysis of Evo2HiC revealed its ability to identify cell type-specific sequence motifs that explain changes in epigenomic signals. Finally, we demonstrated the cross-species generalizability of Evo2HiC on 177 species from the DNA Zoo dataset for Hi-C resolution enhancement. In summary, Evo2HiC is a foundation model that integrates genome sequences and 3D chromatin structure information, substantially reduces computational cost while maintaining state-of-the-art accuracy on predicting various epigenomic signals and genome architecture, enables the identification of cell type-specific motifs, and demonstrates robust generalizability across species.

bioinformatics↗

bioRxiv2025

Comparative Single-Cell Transcriptomics Uncovers Shared and Distinct Molecular Signatures in Cystic Fibrosis and Primary Ciliary Dyskinesia

RationalCystic Fibrosis (CF) and Primary Ciliary Dyskinesia (PCD) are both inherited respiratory disorders that result in impaired mucociliary clearance, and chronic sinopulmonary disease. Although the current approach to PCD management is extrapolated from CF care, both conditions arise from distinct genetic and molecular mechanisms. MethodsHere we performed a comparative transcriptomic analysis between CF and PCD to compare the cellular heterogeneity, molecular pathways and gene networks differences using publicly available sequencing data as well as those performed by our group. To explore gene regulatory networks, a pre-trained transformer model (scGPT) was fine-tuned using an integrated dataset, and differential attention analysis was conducted to identify genes and pathways with altered attention scores between the two conditions. ResultsThe comparative transcriptomic analysis revealed distinct molecular signatures between PCD and CF, which differed from normal cells. In ciliated cells, differential gene expression and pathway investigation highlighted the NRF2 pathways considerable overrepresentation in PCD compared to CF and healthy conditions. This observation was further supported by scGPT analysis, which revealed increased incoming attention to the NRF2 pathway markers. In secretory cells, PCD and CF exhibited increased immune and inflammatory signaling compared to controls. While similar inflammatory processes were active, results suggested a stronger inflammatory pattern in CF secretory cells compared to PCD and confirmed the activation of the unfolded protein response (UPR) pathway. ConclusionThese findings highlight the different molecular signatures between both conditions and the need for unique approaches to management in PCD compared to CF.

cell biology↗

bioRxiv2025

Machine Learning Analysis of Cilia-Driven Particle Transport Distinguishes Primary Ciliary Dyskinesia Cilia from Normal Cilia

RationalPrimary ciliary dyskinesia (PCD) is a genetic condition that results in dysmotile cilia and abnormal mucociliary clearance. Despite advances in understanding the pathogenesis of PCD, diagnosis continues to be challenging. Here we used feature-based machine learning and image-based deep learning to objectively quantify the directed particle transport of motile cilia and detect PCD-related cilia dysfunction. MethodsFluorescent microspheres were captured on cultured multiciliated cells using high-speed video microscopy as a proxy for motile cilia function. An interactive Jython script was designed to automatically detect, track and extract raw track metrics from videos. Data was subsequently analyzed to approximate a quantifiable and visual signature of ciliary transport through a custom-built Python Package, CiliaTracks. ResultsAirway epithelial cells were obtained from 14 individuals with genetically confirmed PCD, 10 healthy donors, and 2 patients with cystic fibrosis. A total of 602 videos (301 PCD and 301 non-PCD) were captured. Quantitative and visual analyses of fluorescent microsphere trajectories, including kinematic metrics and trajectory plots, revealed distinct motility profiles between PCD and non-PCD samples. Classical machine learning models and a convolutional neural network were employed to classify PCD using both modalities, demonstrating excellent accuracy of 95-97%, and the capacity to differentiate PCD from normal cells or cystic fibrosis. ConclusionCilia-propelled microsphere transport exhibits unique trajectory patterns in PCD, enabling differentiation from non-PCD samples. Machine learning provides an objective and accurate framework for characterizing ciliary dysfunction, offering potential as a diagnostic tool for PCD.

bioinformatics↗

bioRxiv2025

Protofibril Binding Peptides Recognize and Inhibit Huntingtin Amyloid Formation in vitro and in vivo

In Huntingtons disease, polyglutamine expansion in huntingtin exon 1 (Httex1) results in stepwise misfolding, amyloid formation, and neuronal death. Here we used mRNA display directed evolution to generate peptide ligands targeting Httex1 protofibrils, an early, toxic misfolding intermediate. Two distinct peptide families bind protofibrils, one tryptophan rich and the other glutamine rich, resulting in two predominant peptides HD1 (W-rich) and HD8 (Q-rich). Both peptides bind with high affinity and specificity to the misfolded polyQ structure present in protofibrils, a toxic component that is not recognized by existing huntingtin-directed antibodies. Homo- and heterodimers of HD1 and HD8 bind protofibrils with antibody-like affinity, and potently inhibit aggregation of recombinant and cellular Httex1. The HD8-1 heterodimer can be used like an antibody for immunocytochemistry to identify Httex1 aggregates in transfected cells and in the retina of a Huntingtons disease mouse model system (R6/1). Peptide binding to both in vitro and in vivo Httex1 validates in vitro generated Httex1 protofibrils share the same structural features as Httex1 amyloid from cellular and mammalian disease model systems. Further, HD8-1 protofibril recognition enables direct detection of a pathogenic form of Httex1 (misfolded polyQ) as a disease biomarker. Finally, HD1, HD8, and HD8-1 binding and aggregation inhibition defines the protofibril sites that mediate fibril growth. Overall, our observations support developing protofibril-directed ligands as novel, selective, diagnostics and therapeutics for Huntingtons disease. Significance StatementHuntingtin protein polyQ misfolding plays a central role in Huntingtons disease pathogenesis. We used mRNA display to discover a new class of huntingtin-directed ligands protofibril-binding peptides. Unlike presently available antibodies, these peptides selectively recognize misfolded polyQ region, enable using toxic huntingtin aggregates as disease biomarkers, and block huntingtin aggregation in vitro and in vivo. Protofibril binding peptides may thus assist analysis of huntingtin pathology and provide a starting point for designing protein misfolding inhibitors as Huntingtons disease therapeutics.

biochemistry↗

bioRxiv2025

Stc2a inhibits IGF-stimulated somatic growth in favor of organismal survival under hypoxia

In response to hypoxia, animals reduce somatic growth to shift energy resources toward the maintenance of vital functions and survival. Although this phenomenon is widespread in the animal kingdom, the factors and mechanisms involved remain poorly understood. Here we report that hypoxia causes major changes in zebrafish transcriptomic landscapes with hormonal activity or hormonal signaling identified as most prominently up-regulated GO term and KEGG pathway. Among the top in this group is Stanniocalcin 2a (Stc2a), a secreted glycoprotein that inhibits insulin-like growth factor (IGF) signaling by binding to pappalysin metalloproteinases and inhibiting their activities. The hypoxic induction of stc2a expression is attenuated in Hif2-deficient fish. Genetic deletion of Stc2a increased the developmental speed and growth rate, resulting in enlarged adult organ and body size. Under hypoxia, stc2a-/- fish grew faster than wild-type fish but showed reduced survival rate. These phenotypes were reversed by inhibiting pappalysin activity or blocking IGF signaling. These findings suggest that Stc2a limits IGF-mediated growth in favor of survival and that the induction of Stc2a is part of a conserved mechanism regulating the trade-off between somatic growth and survival under hypoxic stress.

physiology↗

bioRxiv2025

Reprogrammable bacterial nanosyringes for RNA and gene editors delivery

The engineered Photorhabdus virulence cassette (PVC) has not yet achieved the RNA packaging and injection delivery, although it can accurately deliver diverse proteins. Fortunately, RNA-binding proteins have a high affinity for binding to specific sequences and are excellent anchoring components between RNA and the inner tube of PVC. By combining the U1A RNA-binding domain (U1A RBD) and PVC, we developed a convenient, RNA non-degradable, and universal PVC-based RNA delivery tool, establishing DART (PVC Docker-based All-purpose RNA Injection Delivery Tool). DART successfully achieved the delivery of diverse RNAs, including Pepper RNA, gRNA, siRNA, and miRNA. We also demonstrated that the DART enabled effective knockout of GFP in vivo and in vitro. Our DART system provided a powerful platform for RNA and gene editing therapeutics in vivo.

molecular biology↗