Biology subjects

Qiu, X.

Publications and source records attributed to Qiu, X..

At least 19 recordsLinked to original sources

bioRxiv2026

Stereociliary localization and function of the tip-link protein PCDH15-CD2 are regulated by the PDZ-scaffold NHERF-1

Sensory hair cells in the inner ear convert mechanical sound deflections into electrical signals via the stereociliary hair bundle on their apical surface. Proper bundle function requires that structural, adhesion, and motor proteins be delivered to specific stereocilia sub-compartments and maintained at precise levels throughout life, yet the underlying mechanisms remain poorly understood. Here we investigated how spatiotemporal localization of Protocadherin-15 (PCDH15), a component of kinociliary links, transient lateral links, and tip links, is regulated in mouse auditory hair cells. Using biochemical assays in vitro, we identified the PDZ-domain scaffolds NHERF-1/2 as direct binding partners of CD2, a PCDH15 isoform essential for hearing. We mapped the interaction to NHERF-1's PDZ1 domain and CD2's PDZ-binding motif (PBM), and showed that this binding is regulated by phosphorylation of the CD2 PBM. Using Nherf1 knockout and Pcdh15-CD2 knock-in mice defective in this interaction, we found CD2-NHERF-1 binding is required for proper CD2 levels and localization in the developing hair bundle. Loss of this interaction largely spared early bundle morphogenesis and MET function but caused high-frequency hearing loss and degeneration of the shortest stereociliary row in adult mice. Together, these findings define an important regulatory mechanism with therapeutic relevance for hair bundle repair.

cell biology↗

bioRxiv2026

Repetitive transcranial magnetic stimulation targeting motor cortical region induces cell-type-specific transcriptional reprogramming and behavioral recovery in non-human primate model of Rett syndrome

Rett syndrome (RTT), a severe neurodevelopmental disorder caused by mutations in the MECP2 gene, currently lacks effective treatments. The motor cortex is a pivotal hub in RTT and autism spectrum disorders, and its impairments contribute to motor, social, and cognitive deficits. Here we examined the effects of repetitive transcranial magnetic stimulation (rTMS) targeting motor area in non-human primate of RTT (MECP2-mutant monkey) and investigated neuromolecular basis underlying therapeutic effects. We identified a new treatment target, ventral premotor cortex (PMv), for RTT and found that following a 20-day rTMS course, several behavioral and functional connectivity measures showed directional changes. Neuroimaging analyses confirmed that rTMS induced reorganization of large-scale functional connectivity with enhanced functional integration between the somatomotor and the salience networks and normalized coupling between the motor cortex and both the thalamus and the anterior cingulate cortex. Notably, single-nucleus RNA sequencing revealed that rTMS triggered cell-type-specific transcriptional reprogramming: it rescued pathological hyperactivity of excitatory neurons by restoring the expression and regulatory networks of immediate early genes (e.g., FOS, EGR1) and corrected dysregulated intercellular signaling (e.g., NRG, WNT). These findings indicate that targeting motor cortical areas with brain stimulation may treat RTT, which warrants further clinical validation.

neuroscience↗

bioRxiv2026

Lymphatic ERG Governs Junctional Plasticity and Fluid Clearance via an EDNRB Signaling Axis in Pulmonary Fibrosis

Pulmonary lymphatic vessels are essential for interstitial fluid balance and macromolecular clearance, yet the endothelial mechanisms regulating lymphatic vessel function during chronic fibroproliferative lung injury remain undefined. Here, we demonstrate that the lineage-defining transcription factor ERG in lymphatic endothelial cells (LECs) governs junctional plasticity and fluid drainage in pulmonary fibrosis. In human idiopathic pulmonary fibrosis (IPF) lungs, lymphatic ERG expression is markedly downregulated. Lineage-specific inducible deletion of Erg in murine LECs (Erg-CKO) unexpectedly conferred robust protection against bleomycin-induced pulmonary fibrosis, significantly dampening acute inflammation, reducing edema, and preserving pulmonary compliance. Mechanistically, loss of ERG enhanced lymphatic drainage capacity in vivo. Transcriptomic profiling of isolated LECs revealed that ERG deficiency activates actomyosin contractile pathways and selectively upregulates Endothelin Receptor Type B (Ednrb), driving junctional remodeling from continuous zippers into discontinuous button-like configurations that facilitate interstitial fluid entry. Pharmacological blockade of EDNRB with BQ-788 abolished junctional reorganization, eliminated the enhanced lymphatic drainage, and completely reversed the anti-fibrotic protection in Erg-CKO mice. Together, our findings identify an endothelial ERG-EDNRB regulatory axis that controls lymphatic junctional architecture and demonstrate that promoting lymphatic clearance via endothelial junctional remodeling represents a viable therapeutic strategy for fibrotic vascular remodeling.

cell biology↗

bioRxiv2026

A tumor-cell MHC-II program is associated with checkpoint-blockade outcomes across stages of bladder cancer

Purpose: A minority of patients with bladder cancer derive lasting benefit from immunotherapy, and current biomarkers capture only part of the biology. We evaluated whether tumor-cell MHC class II defines an immune state associated with outcome across disease stages and after PD-1/PD-L1 blockade. Experimental Design: We localized differential MHC-II activity to malignant epithelial cells by single-nucleus and single-cell RNA sequencing and confirmed HLA-DR expression by immunohistochemistry in 122 specimens. Chromatin profiling and IFN-{gamma} stimulation of cell lines and primary tumors supported derivation of an 11-gene tumor-cell program. Associations were tested in 434 patients with non-muscle-invasive disease, 82 receiving neoadjuvant pembrolizumab, and 288 receiving atezolizumab for metastatic disease. Results: Tumor-cell MHC-II was present in approximately one third of bladder cancers, and malignant cells accounted for the differential signal between MHC-II-high and MHC-II-low tumors. The program was inducible by IFN-{gamma} through JAK/STAT signaling. Within luminal non-muscle-invasive disease, MHC-II-low status was associated with progression (HR 3.31, 95% CI 1.37 to 7.99). In PURE-01, the 11-gene program was associated with pathological complete response (52% versus 24%, p = 0.018) and recurrence-free survival (p = 0.0054), retaining an independent association in models including tumor mutational burden and PD-L1. In bladder-primary metastatic disease, program-high status was associated with overall survival in unadjusted analysis (HR 0.62, 95% CI 0.44 to 0.89); the association did not extend to upper tract tumors (interaction p = 0.0018). Conclusions: Tumor-cell MHC-II defines an inducible state associated with outcomes across bladder cancer stages and after checkpoint blockade, supporting prospective evaluation by RNA and immunohistochemistry.

cancer biology↗

bioRxiv2026

Connectivity allometry is a robust organizing principle of the human functional connectome

A defining feature of the human brain is its multiscale organization, in which regional processes are integrated into coherent whole-brain network architecture. How local functional organization adapts to variation in this global architecture, however, remains largely unknown. Here, we addressed this question by applying an allometric scaling framework to resting-state functional magnetic resonance imaging data from four large-scale datasets spanning different cultures, cognitive states, developmental stages, and clinical conditions. We found that human functional networks were organized according to a robust and spatially heterogeneous connectivity allometry, whereby regional functional connectivity scales nonlinearly with whole-brain connectivity strength. This scaling architecture closely followed the cortical sensorimotor-association hierarchy, with lower-order systems exhibiting supralinear scaling and higher-order systems exhibiting sublinear scaling. Connectivity allometry was further associated with multiscale neurobiological organization, including regional metabolic properties, neurotransmitter receptor distributions, and transcriptomic landscapes, indicating that local-global functional scaling is embedded within fundamental biological gradients of cortical organization. Moreover, the scaling pattern and its biological associations were highly reproducible across independent cross-cultural cohorts. Importantly, connectivity allometry remained remarkably stable across working memory conditions regardless of cognitive load, emerged by late childhood, and was broadly preserved in children and adolescents with autism spectrum disorder despite region-specific alterations. Together, these findings establish connectivity allometry as a previously unrecognized organizational principle of the human functional connectome and provide a quantitative framework linking regional functional organization to whole-brain network architecture in health and disease.

neuroscience↗

bioRxiv2026

In vivo intercellular CRISPR screens using viral proximity barcoding reveal regulators of tumor-immune interactions

Cell-cell interactions shape tumor growth, immune evasion, and therapeutic response, but systematically dissecting their genetic regulators in vivo remains challenging. Existing cell-cell interaction tracing technologies rely largely on protein labels or enzymatic reactions, limiting their information content and scalability. To overcome these limitations, we developed match-seq, an imaging-free, sequencing-based cell proximity tracing system that uses virus-like particles to transmit barcodes between neighboring cells. Barcoded mRNAs are transmitted from sender cells to nearby receiver cells, thereby establishing a spatial linkage that can be computationally reconstructed by barcode sequencing after tissue dissociation. We apply this system to an in vivo syngeneic murine tumor model, where we observe robust labeling of all immune cell lineages, and leverage barcode labeling to reconstruct cell type niches that recapitulate known tumor spatial biology. Furthermore, we couple this system with CRISPR perturbations and single-cell RNA sequencing to perform genetic screens in vivo on tumor-immune interactions at single-cell resolution. We use this method to infer cell-cell spatial relationships and uncover genetic dependencies in cancer cells that change the composition and cell state of their local microenvironments. By calculating a local immune activation signature, we are able to prioritize targets whose deletion enhances anti-tumor immunity through distinct effector cell types: loss of Tgfb1 engages CD8 T cells and macrophages, Traf7 loss elicits a CD4 T cell response, and Nectin3 loss promotes NK cell-mediated immunity, relationships that we validate by in vivo immune cell depletion. Notably, Tgfb1 and Nectin3 deletion had little effect on cancer cell fitness in the pooled screen yet suppressed tumor growth when deleted throughout the tumor, demonstrating the potential of match-seq to reveal functionally important tumor-immune interactions that would otherwise remain hidden. Together, these results establish a general framework for pooled genetic dissection of cell-cell interactions in vivo, extending CRISPR screening from cell-intrinsic phenotypes to the mechanisms by which cells shape and respond to their local microenvironments.

cancer biology↗

bioRxiv2026

High-throughput physics-based enzyme engineering

Enzyme engineering aims to tailor natural enzymes for industrial and therapeutic applications, yet physically grounded rational design has been limited by a trade-off between accuracy and cost, leaving the field heavily dependent on expert intuition. Here we present a scalable physics-based framework that combines field-aware machine learning with molecular mechanics to capture enzyme electrostatics at quantum-mechanical accuracy while enabling efficient, atomistic exploration of reaction free-energy landscapes. Coupled with microkinetic modelling, the framework translates molecular free-energy landscapes into catalytic rates and selectivity across competing, multistep reaction pathways. Applied to a newly engineered oxidative amidase (OxiAm), the framework predicts catalytic rate constants with near-experimental accuracy, quantitatively resolves the selectivity between hydrolysis and aminolysis, and generalizes across substrates, mutations and enzyme homologues. Transition-state ensemble analysis further reveals the reaction mechanism and guides the design of enzyme variants for pharmaceutical synthesis. By bringing chemical accuracy and high-throughput sampling to enzyme catalysis, this approach shifts rational design from static, empirical practice toward dynamic, free-energy-driven design, and should accelerate the engineering of biocatalysts.

biophysics↗

bioRxiv2026

Bio-Babel: autonomous cross-language reconstruction of agent-ready computational biology ecosystems

Scientific software is often locked in its source language, callable from others but not natively extensible or built upon. We present Bio-Babel (biobabel.stanford.edu), an autonomous framework that rebuilds software natively in target ecosystems and makes it agent-callable, shipping each package with an agent-readable contract of its usage. Reconstructing a hierarchical, interdependent R-to-Python single-cell stack, Bio-Babel reproduced the originals faithfully and revealed pancreatic differentiation dynamic defects under graded SWI/SNF loss.

bioinformatics↗

bioRxiv2026

ACKR1-expressing venous endothelial cells establish a pro-fibrotic niche in pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by excessive extracellular matrix deposition and irreversible architectural distortion of the lung. Fibrotic remodeling is driven by dynamic interactions among endothelial, fibroblast, epithelial and immune cells. Although pulmonary endothelial cells (ECs) are increasingly recognized as important contributors to IPF pathogenesis, the molecular and cellular events underlying endothelial dysfunction remains poorly understood. Using integrative multi-omics analyses of human IPF lungs combined with functional in vitro assays, we identify ACKR1-expressing venous endothelial cells (ACKR1+ VECs) as critical regulators of a pathogenic niche that promotes lung fibrosis. Single-cell RNA sequencing and spatial transcriptomics analyses reveal that ACKR1+ VECs exhibit a distinct pro-fibrotic and pro-inflammatory transcriptional program enriched for hypoxia responses, extracellular matrix remodeling, and immune cell recruitment. In both mouse and human fibrotic lungs, ACKR1+ VECs localize adjacent to fibroblastic foci and are surrounded by pro-fibrotic CD68+/CCR5+/SPP1+ macrophages-monocytes, suggesting a spatial organized cellular crosstalk supporting fibrotic remodeling. Consistent with these findings, in vitro co-culture assays using ACKR1+ VECs isolated from IPF lungs demonstrate that these cells drive myeloid recruitment and fibroblast activation through ACKR1 dependent mechanisms. Silencing of ACKR1 in IPF-derived VECs suppressed inflammatory and fibrotic transcriptional programs, and pharmacological inhibition of ACKR1 attenuated stromal and immune remodeling and reduced bleomycin-induced lung fibrosis in vivo. Together, these findings identify ACKR1+ VECs as key orchestrators of fibrosis progression and establish ACKR1 and the pathogenic vasculature as promising therapeutic targets for IPF. Clinical RelevanceIdiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with limited treatment options. We identify ACKR1-expressing venous endothelial cells as key drivers of inflammatory and fibrotic remodeling and show that pharmacologic inhibition of ACKR1 attenuates experimental lung fibrosis. These findings establish endothelial ACKR1 as a promising therapeutic target and highlight the pulmonary vasculature as a novel avenue for disease-modifying therapies in IPF.

molecular biology↗

bioRxiv2026

FXR-mediated recruitment of PPP1CB suppresses SMAD2/3 phosphorylation to mitigate pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease with limited treatment options and poorly understood molecular underpinnings. Dysregulated TGF-{beta}/SMAD signaling is a key driver of fibrotic remodeling, promoting persistent myofibroblast activation and excessive extracellular matrix deposition. Here we identify the Farnesoid X receptor (FXR), a bile acid activated nuclear receptor, as a previously unrecognized suppressor of pulmonary fibrosis. FXR expression is significantly reduced in lung tissues from patients with PF and in myofibroblasts derived from BLM-induced mouse models, correlating inversely with fibrosis severity. Genetic ablation of FXR exacerbates BLM-induced pulmonary fibrosis by promoting fibroblast hyperactivation and dysregulation of the TGF-{beta}/SMAD signaling pathway. Mechanistically, we identify PPP1CB as a previously unrecognized FXR-interacting protein in primary myofibroblasts derived from IPF patients. We further show that FXR both increases chromatin accessibility at the PPP1CB locus and assembles a functional complex with PPP1CB, which in turn promotes SMAD2/3 dephosphorylation and suppresses their nuclear translocation. Notably, the clinical-stage FXR agonist TERN101 exhibits potent therapeutic efficacy in a BLM-induced mouse pulmonary fibrosis model. These findings establish FXR as a critical antifibrotic regulator in lung tissue and suggest that pharmacological activation of FXR may offer a promising therapeutic strategy for IPF.

cell biology↗

bioRxiv2026

Coronavirus papain-like protease antagonizes innate immunity by cleaving Importin α1 to disrupt nuclear transport

The Importin family, as key mediators of nucleocytoplasmic transport, represents a common target for viral immune evasion. However, whether coronaviruses directly manipulate Importin to disrupt nuclear trafficking and suppress antiviral immunity has remained unclear. In this study, we identify a previously unrecognized mechanism by which coronaviruses from all four genera subvert host innate immunity through the proteolytic inactivation of Importin 1, a key mediator of nuclear import of cargo proteins. We demonstrate that the membrane-associated papain-like protease (PLpro-TM) directly cleaves Importin 1 at specific glycine residues, G129 for PEDV and IBV PLpro, and G119 for MHV and PDCoV PLpro, thereby disrupting its nuclear import function. This cleavage impairs the nuclear translocation of multiple transcription factors (IRF3, STAT1, STAT2, and p65) and suppresses the expression of downstream antiviral genes, including IFN-{beta} and IFN-stimulated genes (ISGs). Importantly, cleavage-resistant mutants of Importin 1 (G129A or G119A) restore nuclear import capability and rescue IFN-{beta} signaling. Consequently, they exert a more potent inhibitory effect on viral replication than the wild-type Importin 1, fulfilling an antiviral role. Our work establishes PLpro-TM-mediated cleavage of Importin 1 as a conserved immune evasion strategy across coronaviruses and highlights this interaction as a potential target for broad-spectrum antiviral intervention. Author summaryThe nuclear transport of transcription factors is a critical checkpoint for the initiation of innate antiviral immunity. Here, we identify the PLpro-TM protein as a pan-coronavirus antagonist of nucleocytoplasmic trafficking and innate immune response. We demonstrate that PLpro-TM from four distinct coronavirus genera directly cleaves Importin 1 at specific glycine residues, thereby disabling its ability to mediate the nuclear import of key transcription factors and subsequent transcription of anti-viral genes. This work reveals a previously unrecognized, evolutionarily conserved immune evasion strategy shared across , {beta}, {gamma}, and {delta} coronaviruses. By uncovering the proteolytic inactivation of Importin 1 targeting by PLpro-TM, our findings not only resolve a long-standing question about how coronaviruses disrupt nuclear trafficking, but also establish PLpro-TM and Importin 1 as promising targets for the development of broad-spectrum antiviral therapeutics against current and emerging coronaviruses.

microbiology↗

bioRxiv2026

A novel AR molecular glue degrader via bivalent engagement of the N-terminal domain and RNF213-UBE2J2 complex

Targeted protein degradation enables the elimination of disease-relevant proteins through induced proximity between E3 ligases and substrates. Current androgen receptor (AR) therapies act via the ligand-binding domain (LBD) but fail against constitutively active LBD mutants or splice variants such as AR-V7. Here, we identify GZL626, a small-molecule degrader that induces proteasome-dependent degradation of both full-length AR and AR-V7. GZL626 suppresses AR transcriptional activity, inhibits proliferation of AR-positive prostate cancer cells, and blocks SARS-CoV-2 infection. Mechanistically, GZL626 binds the intrinsically disordered AR N-terminal domain (NTD) and promotes formation of a noncanonical RNF213-UBE2J2-AR ternary complex that drives AR ubiquitination and degradation. The AR DNA-binding domain (DBD) acts as a structural hub within this assembly. Distinct from PROTACs or classical molecular glues, GZL626 engages both AR and RNF213 bivalently, remodeling protein interactions to stabilize a functional E3-E2-substrate complex. These findings establish GZL626 as a first-in-class NTD degrader with potential to overcome resistance in advanced prostate cancer.

biophysics↗

bioRxiv2026

Chromosome-level genome assembly of Calotes wangi with dynamic colour variation

The Wangs garden lizard, Calotes wangi, is a widely distributed agamid species in Southern China and Northern Vietnam and exhibits pronounced colour variation and rapid body colour change. Despite increasing interest in the genomic basis of colour variation, chromosome-level genomic resources remain limited in agamid lizards. Here, we generated a chromosome-level reference genome of C. wangi using PacBio HiFi sequencing and Hi-C scaffolding. The final genome assembly was approximately 1.66 Gb in size and comprised 6 macrochromosomes and 11 microchromosomes, with a contig N50 of 110.09 Mb and 98.9% complete BUSCO genes. A total of 20,442 protein-coding genes were annotated. Comparative genomic analyses identified 297 significantly expanded gene families, with enriched functions associated with steroid metabolism, chromatin regulation, and epigenetic processes. This high-quality genome assembly provides an important genomic resource for future studies of colour variation, phenotypic plasticity, and evolutionary diversification in agamid lizards.

evolutionary biology↗

bioRxiv2026

Generative Modeling of Mouse Embryogenesis for Fate and Disease Prediction

Embryonic development is orchestrated by complex gene regulatory networks, and learning regulatory dynamics from developmental data could allow us to understand, predict, and ultimately engineer cell fates. Here we introduce Navigo (https://github.com/aristoteleo/Navigo-release), a biologically grounded generative modeling framework that learns a developmental vector field by integrating flow matching at the population level with RNA kinetics modeling at the molecular level. Navigo accurately maps developmental trajectories across lineages on a mouse embryogenesis scRNA-seq atlas spanning 43 time points and comprising 12.4 million cells. Applied to cardiac development, Navigo enables disease modeling by mechanistically resolving regulatory networks that distinguish congenital heart disease subtypes. Navigo also predicts perturbation effects in a zero-shot manner, as validated on independent in vivo data from six knockout genotypes without perturbation-specific training, uncovering lineage-specific gene-compensation mechanisms. Moreover, Navigo guides rational cell-fate engineering, exemplified by fibroblast reprogramming analyses, including identifying pro-fibrotic barriers to cardiac fates and evaluating hundreds of pairwise transcription factor combinations for neuronal fate, each consisting of one bHLH factor and one POU factor. Overall, Navigo provides a generalizable AI platform for perturbation-effect prediction, disease modeling, and rational cell-fate engineering, advancing toward AI-based virtual embryos for developmental biology and regenerative medicine.

bioinformatics↗

bioRxiv2026

Antagonists Perturb the MC2R MRAP Complex and Reshape Receptor Conformations

Melanocortin 2 receptor (MC2R) is a G protein-coupled receptor (GPCR) for adrenocorticotropic hormone (ACTH), and its trafficking and signalling are associated with the melanocortin receptor accessory protein (MRAP). Mutations in either MC2R or MRAP disrupt this signalling and cause familial glucocorticoid deficiency. Here, we combine native mass spectrometry (MS) and hydrogen deuterium exchange mass spectrometry (HDX MS) to uncover how MRAP association and post-translational modification status shape the conformations of MC2R. Using native MS, we demonstrate that MC2R associates with MRAP or when MRAP is depleted the protein is extensively palmitoylated at the C-terminus. ACTH binding is restricted to the MC2R MRAP complex. By contrast antagonists shift the equilibrium toward MRAP-independent receptor populations. Our HDX MS analysis shows that ACTH binding induces global stabilisation of MC2R and the MRAP N terminus, consistent with reinforcement of the receptor accessory protein interface. Antagonist binding by contrast destabilises this interface and increases dynamics in transmembrane helix 2 (TM2). Notably, TM2 destabilisation is retained when the MRAP complex is depleted. Together, MRAP association and palmitoylation define distinct MC2R assemblies with ligand-dependent dynamics, suggesting new ways to influence MC2R pharmacology.

biochemistry↗

bioRxiv2026

Rapid Determination of Drug-to-Antibody Ratios in Antibody Drug Conjugates Using Ultrafast Microdroplet Digestion Technology

Accurate determination of drug-to-antibody ratios (DARs) is essential for the development, quality control, and performance evaluation of antibody-drug conjugates (ADCs); yet conventional analytical approaches often require extensive sample preparation, long analysis time, and substantial sample consumption. The peak distribution of intact ADCs is highly complex due to inherent glycosylation heterogeneity and variable drug conjugation. By applying enzymatic digestion, ADC can be converted into smaller subunits or deglycosylated species, thereby significantly simplifying the mass spectral profile. This reduction in structural heterogeneity facilitates clearer peak assignment and enables more accurate and reliable DAR quantification. Herein, we report an ultrafast microdroplet digestion-mass spectrometry strategy for rapid DAR characterization of ADCs. Microdroplet enzymatic digestion of antibodies and ADCs occurs within microsecond-time scales during spray ionization, enabling direct online subunit analysis with minimal sample preparation. The method was validated using NIST monoclonal antibody (mAb) conjugated to ADC mimics spanning low to high DAR (0-14) ranges, Cetuximab-derived ADC mimics (DAR[~]5) with complex glycosylation, and the commercial ADC Kadcyla (DAR[~]3.5). Consistent DAR values were obtained across multiple enzymatic workflows (IdeS, EndoS2, and EndoF3) with good reproducibility (%CV typically <5%). This approach substantially reduces analysis time while maintaining analytical accuracy and structural specificity, providing a rapid, sensitive platform for high-throughput ADC characterization and process monitoring. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/729562v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@23145corg.highwire.dtl.DTLVardef@10ddd88org.highwire.dtl.DTLVardef@14b1370org.highwire.dtl.DTLVardef@1e94ad6_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

PXN Unlocks the Power of Public Gene Expression Data Through Cross-Technology Integration

The immense value of public gene expression repositories is constrained by the lack of compatibility among datasets generated from diverse experimental technologies. Differences in measurement scales, probe chemistries, and signal distributions create systematic discrepancies across platforms and laboratories. These inconsistencies make large-scale integrative analysis nearly impossible, even though such studies could achieve great statistical power and improved reproducibility. We introduce PXN, a probabilistic machine learning framework that captures a unified representation of biological signal across multiple gene expression technologies. Once trained, PXN can seamlessly translate data between multiple platforms, preserving informative biological variation while removing technology-specific biases. In benchmarking studies, PXN consistently outperforms existing normalization methods in cross-platform accuracy and substantially enhances the power of differential expression analysis. Importantly, we show that PXN is powerful enough to bridge even the most challenging technological divide--between microarray and RNA-seq. This capability provides a scalable route for integrating legacy microarray data with modern RNA-seq studies. By enabling direct comparison and integration of heterogeneous datasets, PXN unlocks the full potential of public repositories for future biological discovery and therapeutic innovation.

bioinformatics↗

bioRxiv2026

Automated Multimodal Correlative Registration for Organelle-Specific Molecular Imaging

Mapping subcellular drug distribution is essential for understanding trafficking and off-target effects. NanoSIMS enables chemical imaging of labeled therapeutics, but signal interpretation requires ultrastructural correlation with electron microscopy, a manual and laborious process. We present an automated AI-driven pipeline for correlating chemical and ultrastructural images, enabling multiscale, organelle-precise imaging of molecules in cells and tissues. The method integrates bidirectional optical flow, confidence-guided affine transformation, and automated template matching for cross-scale EM alignment. Morphology-rich ion channels (e.g., 32S) estimate transformations that propagate to sparse therapeutic signals (e.g., 79Br, 15N), overcoming low signal-to-noise challenges. We validate this framework across diverse cell and tissue types, tracking oligonucleotide and antibody therapeutics in vitro and in vivo to reveal cell-type- and organelle-specific distribution patterns. This work establishes a generalizable platform for automated multimodal registration and organelle-resolved subcellular pharmacology.

bioinformatics↗