Biology subjects

Jiang, Z.

Publications and source records attributed to Jiang, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

OmicOS: A Comprehensive Omics Ecosystem Infrastructure and Agent System for the AI Era

Biology has accumulated a vast ecosystem of omics methods, but much of this ecosystem remains built for expert humans rather than scientific agents. Methods are scattered across Python packages, R/Bioconductor and CRAN workflows, command-line tools, incompatible data containers and implicit object states, making even routine analyses difficult for an AI system to choose, execute and verify reliably. Here we introduce OmicOS, a comprehensive omics ecosystem infrastructure and agent system that turns OmicVerse V2, an open-source omics community, into an executable foundation for agentic biology. OmicVerse V2 provides the community substrate: scalable AnnDataOOM-compatible rust backends, agent-friendly Python algorithms for single-cell, spatial, bulk and multi-omics analysis, interfaces to single-cell foundation models, and Python-native reconstructions of historically R-centred Bioconductor/CRAN-style workflows. OmicOS makes this substrate actionable by registering analytical functions as state-aware capability contracts, allowing agents to inspect live data objects, select valid methods, execute controlled workflows and record provenance. The result is not a fixed pipeline, but a programmable omics environment in which agents compose real analyses from verified community methods rather than inventing tools. Across external and purpose-built benchmarks, OmicOS ranked first among the evaluated systems, reaching 81.2% on BiomniBench. Adding OmicVerse to a minimal agent improved task completion by up to 34.2 percentage points with qwen-3.6-35b, and controlled ablations showed that the gains came from registry-grounded execution rather than from larger models, documentation retrieval or unrestricted tool exposure. The same infrastructure scaled to atlas-sized data, reproduced R-centred workflows in Python and converted external pathology software into agent-usable skills. In a discovery task starting from a whole-body spatial map and the term "Alzheimers disease", OmicOS composed a non-canonical workflow that integrated spatial expression, genetic association, eQTL and colocalization evidence to nominate a colon epithelial risk axis centred on PICALM, CD2AP and CR1. Together, OmicVerse and OmicOS define an open foundation for AI-era omics, showing how a community of biological methods can be transformed into a reliable, extensible and agent-operable system for discovery. HighlightO_LIOmicVerse 2.0 consolidates 694 methods spanning 11 omics domains into agent-callable high-level APIs. C_LIO_LIRebuildR automatically reconstructs and evolves R/Bioconductor methods as Python-native implementations under output-equivalence gates. C_LIO_LIOmicOS establishes a state-of-the-art omics agent harness, ranking first on general omics benchmarks across models and substantially improving the analytical capability of local open-source models. C_LIO_LICompositional use of ecosystem modules nominates a colon epithelial axis associated with Alzheimers disease risk. C_LIO_LIExternal algorithm packages supporting automatic iterative evolution can be integrated into the OmicOS ecosystem. C_LI

bioinformatics↗

bioRxiv2026

Hypermutability of ultraconserved histone genes and its contribution to human disease

Histone genes are among the most evolutionarily conserved sequences in eukaryotes, reflecting their essential role in nucleosome architecture. Intriguingly, our analysis reveals unexpectedly high germline mutation rates in replication-dependent histone genes across vertebrates. We provide multiple lines of evidence suggesting that this hypermutability is largely driven by off-target mutagenic effects of AID/APOBEC enzymes, representing an unintended fitness cost associated with vertebrate immune system innovation. To characterize the impact of these mutations, we develop HistMTR, a paralog-aware missense constraint framework that outperforms existing tools in predicting the pathogenicity of histone mutations. Applying this framework to large-scale human genomic data, we demonstrate that both coding and regulatory histone mutations contribute to a spectrum of diseases, including developmental disorders and reproductive failure. Analyses of allele transmission ratios and the distribution of fitness effects indicate intense ongoing negative selection against deleterious histone mutations in humans. Together, these findings uncover a hidden vulnerability of ultraconserved histone genes and establish HistMTR as an important framework for characterizing the underappreciated role of histone mutations in human disease.

evolutionary biology↗

bioRxiv2026

GYS2 Promotes the Progression of Aortic Dissection and Aortic Aneurysm via C5a/NF-κB-Mediated Pro-Inflammatory Macrophage Polarization

BackgroundAortic aneurysm and aortic dissection (AAD) are lethal cardiovascular emergencies characterized by sudden onset and extremely high early mortality. The pro-inflammatory polarization of macrophages is one of the core factors driving the pathogenesis of AAD, but its underlying mechanism remains unclear. This study focuses on the aberrant expression of glycogen synthase 2 (GYS2) in the AAD microenvironment and its role in driving macrophage polarization toward the pro-inflammatory M1 phenotype. MethodsProteomic analysis was conducted to identify protein heterogeneity associated with AAD. Clinical and animal samples were used to evaluate the correlation between GYS2 expression and AAD progression. Whole-body GYS2 knockout mice and adeno-associated virus (AAV)-mediated macrophage-specific gain- and loss-of-function models were utilized to investigate the regulatory role of GYS2 in macrophage polarization and complement activation. Downstream molecular pathways were identified and validated through in vitro stimulation and in vivo exogenous C5a rescue experiments. ResultsGYS2 expression was significantly upregulated in AAD tissues and primarily localized in macrophages. Activation of GYS2 by LiCl or macrophage-specific overexpression of GYS2 exacerbated aortic dilation and extracellular matrix degradation, and increased mortality in AAD mice. Conversely, whole-body GYS2 knockout or macrophage-specific GYS2 knockdown suppressed inflammatory factors, significantly reduced the incidence of AAD, and attenuated vascular injury. Mechanistically, excessive GYS2 in macrophages specifically triggered the complement-coagulation cascade, promoting the generation of the potent anaphylatoxin C5a. C5a further bound to its receptor C5AR1, activating the downstream PLC{beta}3/NF-{kappa}B signaling pathway, thereby inducing M1 macrophage polarization and matrix metalloproteinase-mediated extracellular matrix degradation. In vivo exogenous C5a rescue completely reversed the vascular protective effects conferred by GYS2 deficiency. ConclusionsThis study demonstrates that highly expressed GYS2 regulates the pro-inflammatory polarization of macrophages and extracellular matrix degradation via the complement C5a/PLC{beta}3/NF-{kappa}B signaling axis, which is a key mechanism driving AAD progression. Specific inhibition of macrophage GYS2 can effectively alleviate aortic vascular inflammation and prevent AAD progression, providing a promising novel strategy for the clinical conservative treatment of AAD.

Molecular Biology↗

bioRxiv2026

The origin and evolution of archaeal Borg extrachromosomal elements

Borgs are giant linear extrachromosomal elements (ECEs) of methane-oxidizing Methanoperedens archaea whose evolutionary origin and ecosystem distribution remain unknown. Here we detected 240 Borgs in diverse saline, soil, and freshwater ecosystems. 27 encode methyl-coenzyme M reductases central to methane metabolism, eight have full rRNA operons related to those of Methanoperedens, and some contain up to four ribosomal proteins. We also identified 323 mini-Borgs whose proteome content and gene phylogenies classify as a distinct ECE type. Based on 105 complete and near-complete genomes, Borgs and mini-Borgs share core genes in conserved order, indicating common ancestry. Phylogenetic and diversity analyses suggest that Borgs evolved via gene acquisition into a backbone inherited from mini-Borgs. This evolutionary trajectory mirrors those proposed for giant viruses of both eukaryotes and bacteria.

microbiology↗

bioRxiv2026

Salvianolic acids are natural senolytics and increase lifespan in old age

Cellular senescence plays a critical role in chronological aging and is implicated in the onset and progression of multiple age-related disorders. Targeting senescent cells represents a promising strategy to reduce disease burden and improve healthspan. Here we report the senotherapeutic properties of salvianolic acid (SA) family members, specifically A (SAA), B (SAB) and E (SAE). From a natural medicinal agent library, we identified selective cytotoxicity of these SA compounds against senescent cells across diverse senescence types and cell lineages. Mechanistically, SAA, SAB and SAE enhance ROS production and target glutathione S-transferase Pi1 (GSTP1), a redox homeostasis modulator, inducing both apoptosis and ferroptosis in senescent cells. Incorporation of SAs into chemotherapeutic regimens enhanced anticancer efficacy and prolonged post-treatment survival. Intermittent SA administration improved physical function and increased healthspan and lifespan in aged mice. Collectively, our study establishes SAs as an emerging class of natural senolytics (phenolic acids) with the capacity to delay aging and alleviate age-related pathologies in advanced life.

cell biology↗

bioRxiv2026

An efficient and stable ascorbate/O2-driven route for L-DOPA synthesis by heme-dependent tyrosine hydroxylase

L-DOPA is a key therapeutic agent for Parkinsons disease, with growing demand due to global population aging. Here we report that heme-dependent tyrosine hydroxylase (TyrH) can utilize an ascorbate/O2 system--as an alternative to H2O2--to synthesize L-DOPA with markedly enhanced operational stability. While exogenous H2O2 rapidly inactivates TyrH within minutes, sodium ascorbate (NaAsc) enables sustained catalysis for up to 24 h, surpassing the H2O2-driven yield after only 30 min. UV-vis spectroscopy confirms that H2O2 readily degrades the heme center, whereas the heme remains intact in the presence of NaAsc. QM/MM simulations reveal that in situ generated H2O2 leads to the active species of Compound I for tyrosine hydroxylation. Through systematic optimization, we establish efficient reaction conditions (40 {micro}M TyrH, 1 mM L-Tyr, 100 mM NaAsc, pH 8.5, 40 {degrees}C), achieving >95% conversion of L-Tyr to L-DOPA within 2 h. This work not only provides a robust and sustainable biocatalytic route for L-DOPA production but also highlights the broader applicability of the ascorbate/O2 pathway in heme-enzyme catalysis.

biochemistry↗

bioRxiv2026

Improving Biological Sequence Prediction with AlphaFold2 Representation

MotivationAccurate prediction of functional sites from primary sequences is essential for elucidating biological mechanisms and advancing rational drug design. However, traditional sequence-based features are inherently unable to capture complex structural protein contexts. Recently, AlphaFold2 (AF2) revolutionized protein structure prediction, raising expectations of AF2 to serve as a feature extractor providing structure-rich representation, which can be useful for sequence-based prediction, particularly for unknown sequences. ResultsWe present a novel feature-engineering paradigm that leverages a high-dimensional latent representation matrix (of L x D, where L is the sequence length and D is the feature dimension size) extracted directly from the AF2 Evoformer module. We systematically evaluated the AF2 representation, comparing with conventional sequence-based features, such as hidden Markov model profiles, using a variety of machine learning models, on two structurally contrasting tasks, calpain cleavage site and nucleic-acid-binding site prediction. The AF2 representation outperformed conventional sequence-based features clearly and entirely, particularly for targets with low sequence homology to training data. Furthermore, interpretability analyses, using SHapley Additive exPlanations (SHAP) and Uniform MAnifoldapproximation and Projection (UMAP), showed more details behind the performance advantage of AF2 representation through feature importance ranking and visualization. Overall, these empirical results confirmed that AF2 representation could effectively bridge the sequence-to-structure gap as a feature input for sequence prediction, without increasing heavy computational burden. Availability and implementationSource code, pre-trained models, and datasets are freely available to non-commercial users at https://github.com/Lili-irtyd/Improve-biological-sequences-prediction-by-AlphaFold2. Contactmami@kuicr.kyoto-u.ac.jp

bioinformatics↗

bioRxiv2026

Dissecting inter-focal heterogeneity and convergent immunosuppressive ecosystems in multifocal hepatocellular carcinoma through single-cell and spatial multi-omics

Background Multifocal hepatocellular carcinoma (HCC) comprises spatially separated tumor foci with distinct evolutionary trajectories, posing a major therapeutic challenge. Whether divergent lesions retain shared immune-evasion mechanisms beyond lesion-specific heterogeneity and offer cross-focal therapeutic opportunities remains unknown. Objective To resolve malignant and microenvironmental heterogeneity across tumor foci and identify conserved immunosuppressive programs underlying multifocal HCC progression. Design Matched tumour foci and peritumoural tissues from patients with multifocal HCC underwent integrated single-cell and spatial multi-omics profiling, including scFAST-seq (n=15), scATAC-seq (n=12), and Stereo-seq (n=14). In-house RNA-seq (n=13), public scRNA-seq (HRA001748) and RNA-seq datasets (TCGA-LIHC, OEP000321) were used for validation. Multiplex immunohistochemistry (n=96) and functional assays validated key findings. Results Multifocal HCC exhibited extensive inter-focal heterogeneity in malignant genomic, transcriptional, epigenetic, and evolutionary states, accompanied by diverse immune and stromal landscapes. Despite this divergence, spatially separated tumor foci converged on shared malignant states marked by elevated TMED2 expression and conserved immunosuppressive ecosystems characterized by regulatory T-cell (Treg) and SPP1+/SPRED1+ macrophage enrichment, impaired cytotoxic CD8+ T-cell immunity, and recurrent stromal-vascular remodeling. Mechanistically, malignant hepatocytes engaged SPP1+/SPRED1+ macrophages through C3/C5 complement signaling across divergent tumor foci, while macrophages and Tregs contributed to CD8+ T-cell dysfunction through CD274-PDCD1, CD80/CD86-CTLA4/CD28, and MHC-I-CD8 interactions. A tumor-intrinsic TMED2-ADAR1-dependent A-to-I RNA editing program promoted C3/C5 complement expression and secretion, linking malignant heterogeneity to conserved tumor-immune signaling. Conclusions Despite divergent malignant evolution, multifocal HCC converges on shared immunosuppressive ecosystems. The TMED2-ADAR1-C3/C5 complement axis represents a conserved tumor-immune vulnerability that may enable therapeutic strategies targeting common immune-evasion mechanisms across heterogeneous tumor foci.

cancer biology↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

Engineering age-adaptive mRNA lipid nanoparticle cancer vaccines via reprogramming systemic gene expression

Lipid nanoparticle (LNP)-based mRNA vaccines have transformed cancer immunotherapy, yet their efficacy in older individuals, who represent the majority of cancer patients, remains poorly understood. Here, we uncover a critical and previously underappreciated barrier to mRNA LNP cancer vaccine performance in aged hosts: impaired systemic transgene expression. Using the SM-102 mRNA LNPs as a benchmark formulation, we show that while local immune activation and antigen presentation at the injection site and draining lymph nodes remain largely intact with age, transgene expression in peripheral organs, including the liver, lungs, and spleen, is markedly reduced. This deficit limits the magnitude and durability of CD8 and CD4 T cell responses and substantially compromises tumour control. Transcriptomic profiling further reveals that attenuated transgene expression parallels broad attenuation of antigen processing, presentation, and activation pathways in immune cells from aged animals, implicating impaired systemic mRNA translation as a central driver of the downstream immune defects and antitumour efficacy loss. Building on these insights, we identify a rationally selected LNP formulation that reestablishes distal antigen expression across age groups as an engineering strategy to revive T cell immunity, achieving full rescue of therapeutic efficacy in aged mice without additional intervention. Together, these findings establish systemic mRNA translation as a tuneable lever of vaccine performance and highlight that optimizing LNP formulations to sustain systemic transgene expression across age groups may enable next-generation, age-adaptive mRNA vaccines for cancer and other diseases of aging.

bioengineering↗

bioRxiv2026

Connectome-based spatial statistics enabling large-scale population analyses of human connectome across cohorts

Large-scale population analyses of structural connectome organization remain challenging because of cross-subject alignment, pathway interpretability and computational burden. No widely adopted standard exists for systematic evaluation across processing methods. We developed connectome-based spatial statistics (CBSS), a scalable framework for anatomically aligned and functionally informed quantification of white-matter microstructure that yields atlas-defined pathways organized into 13 functional networks. Using data from 56,510 UK Biobank participants together with five independent lifespan cohorts, we evaluated the streamline-, voxel- and network-level measures in the aspects of reliability, heritability, structure-function coupling, cognitive and behavioral prediction, brain aging patterns and lifespan trajectories across cohorts. The systematic evaluation workflow compares population-level white-matter representations across methods, spatial scales, tasks and datasets. The results support CBSS as a common connectome reference for large-scale, cross-cohort diffusion MRI studies.

neuroscience↗

bioRxiv2026

Tetrahydrocannabinol exposure to postejaculatory sperm compromises sperm structure, function, the epigenome, and early embryo development

Cannabis (marijuana) is the most widely used recreational drug in the USA accounting for about 62 million users in 2024. Among cannabis users, 26% are of prime reproductive age (18-25 years). Delta-9 tetrahydrocannabinol (THC) is the principal psychoactive component of cannabis and has been detected in human seminal fluids. Although abundant evidence indicates adverse effects of THC exposure on spermatogenesis in different species, acute effects of THC on postejaculatory sperm including fertilization potential and subsequent carryover effects on embryo development are largely unknown. The present study was designed to provide missing information on structural and mechanistic effects of THC exposure to postejaculatory sperm function by evaluating sperm indices often overlooked or masked during clinical evaluation. A bovine embryo continuum model was employed to determine effects of THC on sperm structure, kinematics, bioenergetics, and binding mechanisms. Effects of THC on the sperm genomic and epigenomic landscape were determined, complemented by paternal carry over effects on embryo development as a human translational model to elucidate paternal effects on future development, and to mirror sperm exposure during transport within the female reproductive tract. Cryopreserved bovine sperm from three bulls were independently exposed to physiologically relevant concentrations of THC (0 and 32nM, n = 2 individual replicates/bull) for 24 h under non-capacitating conditions at 25{degrees}C followed by quantification of sperm kinematics at 37{degrees}C. Samples of THC-exposed sperm and vehicle-control (0.1% DMSO) were collected in replicate following immediate addition of THC (0 h) and again at 24 h. DNA damage, acrosome integrity, bioenergetics, changes to DNA methylation and embryo development were quantified. Data were analyzed by logistic regression with a generalized linear mixed effect model. Computer-assisted sperm assessment revealed a reduction in progressive motility of THC-exposed sperm after 24 h while other parameters were not affected. Acrosome integrity as determined by flowcytometric analysis with FITC-PSA was severely compromised in THC-exposed sperm (P [≤] 0.05), despite no detectable difference in capacitation status using merocyanine staining. Similarly, DNA integrity as determined by TUNEL assay was significantly impaired after 24 h of THC exposure (P [≤] 0.05). Mechanistic effects of THC were explored through characterization of the transmembrane G-protein coupled cannabinoid 1 receptor (CB1). CB1 is expressed in the post-acrosomal region and its abundance decreased as compared to unexposed sperm. Alterations to the methylation landscape of sperm were then determined after 24 h of THC exposure through whole-genome Enzymatic Methyl Sequencing. PCA analysis indicated that sperm from different males formed distinct clusters, implying individual differences among bulls, while the effects of THC exposure produced tighter clusters. Paternal carryover effects on embryos derived by in vitro fertilization from THC exposed sperm had reduced 2-cell cleavage, 8-16 cell morula development, and reduced blastocyst development compared to unexposed sperm (46% vs. 33%). In conclusion, post-ejaculatory mammalian sperm exposure to THC compromises acrosome integrity, induces DNA damage, changes the sperm methylome, and reduces developmental potential. Collectively, these data implicate new considerations for recreational and clinical use of cannabis that impact cellular and molecular mechanisms important for sperm function with detrimental consequences for gamete interaction and embryo development.

cell biology↗

bioRxiv2026

Stepwise GRN co-option in the evolution of a dipteran respiratory organ

The origin of morphological novelty lies at the heart of evolutionary biology, yet how ecological shifts drive its emergence through rewiring of gene regulatory networks (GRNs) remains poorly understood. Here, we dissect the roles of GRN co-option in the development and evolution of the prothoracic respiratory organ (PROD), a key innovation facilitating aquatic respiration in dipteran pupae. Ancestral-state reconstruction across over 200 species reveals that PROD originated [~]241 Ma in the common ancestor of Diptera, with a major increase in structural complexity in schizophoran flies [~]66-70 Ma. These transitions coincide with the Carnian Pluvial Episode and the K-Pg mass extinction, periods of profound climatic and ecological upheaval that likely imposed selection pressure for efficient pupal gas exchange in flooded or submerged habitats. Using comparative transcriptomics, scRNA-seq, and genetic manipulations in Drosophila melanogaster and Aedes albopictus, we demonstrate that PROD is a prothoracic wing serial homolog, specified by a cut-centered spiracle GRN and arising through heterochronic activation of an appendage GRN. In schizophoran flies, increase in complexity of PROD involved additional co-option of a breathless-centered tracheal GRN. Our findings reveal a stepwise model of hierarchical GRN co-option and provide potential links between geo-climatic events to the origin and escalation of morphological novelty. This eco-evo-devo framework provides a mechanistic and generalizable paradigm for how ecological challenges are translated into morphological innovations over macroevolutionary timescales.

evolutionary biology↗

bioRxiv2026

A Hidden Binding Pocket in the β- ketoacyl-ACP Synthase FabB

Assembly-line enzymes carry out multi-step synthesis of diverse metabolites by using a handful of catalytic motifs in which minor structural differences control substrate specificity and reaction order. Here we examine differences in substrate binding to FabB and FabF, the two {beta}-ketoacyl-ACP synthases (KSs) responsible for fatty acid elongation in Escherichia coli, by exploring a peculiar mutational effect. In FabB, a blocking mutation in the acyl binding pocket yields a shifted, but broad product profile, while in FabF, the same mutation disrupts the binding of acyl chains longer than eight carbons (C8). X-ray crystal structures of the FabB mutant provide an explanation: a second, previously unobserved binding pocket allows medium-to-long acyl chains ([≥] C8) to bind with an alternate conformation. Molecular simulations suggest that this pocket is more stable in FabB than in FabF, where mutations reduce the catalytic competency of longer chains instead of shifting them to the alternate pocket. Our findings indicate that homologous KSs differ not only in their primary binding sites but also in the availability of alternative binding modes that can buffer against mutational effects and enable functional diversification.

biochemistry↗

bioRxiv2026

Cost-effective hybrid long- and short-read sequencing enables accurate somatic structural variant detection

Somatic structural variant (SSV) calling typically requires matched normal data. Incorporating relatively inexpensive short-read sequencing not only provides essential germline information but can also replace a substantial portion of long-read sequencing, thereby enabling more cost-effective somatic SV detection. Here, we present SomaSV, a hybrid sequencing framework that integrates 30x tumor long-read data with matched normal data comprising 10x long-read and 30x short-read sequencing. This design achieves high-accuracy somatic SV detection while remaining cost-competitive. Comprehensive benchmarking demonstrates that SomaSV outperforms current state-of-the-art methods by more than 13% in F1 score while reducing sequencing costs by approximately 19%. Moreover, SomaSV identifies clinically relevant cancer-associated genes, including CLDN4 and ROBO2, highlighting its potential for discovering valuable biomarkers to support early cancer screening and diagnosis. The source code for SomaSV can be accessed at https://github.com/eioyuou/SomaSV.

bioinformatics↗

bioRxiv2026

A Novel Method for Normalizing Data from DNA-Encoded Library Selections

DNA-encoded library screening represents a significant advancement in the field of drug discovery. Its ability to rapidly and cost-effectively identify potential drug candidates from large compound libraries has the potential to revolutionize the way new medicines are discovered and developed. While the strategies for DEL screening and data analysis have improved over the years, data normalization remains an open challenge. Existing normalization methods can yield poor correlation for compounds with high read count, and they do not account for inherent sources of noise. To overcome these drawbacks, we have developed a robust normalization technique using an antibody fragment and a DNA-conjugated peptide as an internal control. This innovative approach allows for normalization between samples of different conditions and accounts for technical challenges that occur during screening. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/700605v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1b04b91org.highwire.dtl.DTLVardef@1312295org.highwire.dtl.DTLVardef@d59713org.highwire.dtl.DTLVardef@b1786a_HPS_FORMAT_FIGEXP M_FIG C_FIG SynopsisNormalization of DNA-encoded library selection data reduces bias and noise, enabling accurate identification of true binders and reliable enrichment analysis.

biochemistry↗

bioRxiv2026

Histology-Aware Graph for Modeling Intercellular Communication in Spatial Transcriptomics

Cell-cell communication (CCC) is essential to how life forms and functions. Recent tools achieve single-cell-resolved CCC inference utilizing spatial transcriptomics (ST). However, most ignore the modeling of tissue contexts surrounding cells, causing high false-positive/negative rates. Here, we propose HARMONIC, a CCC inference method integrating multimodal ST and hematoxylin and eosin (H&E)-stained images. HARMONIC causally modeling the transcriptomic-to-contextual relationships for CCC inference. The state-of-the-art performance was verified across ST platforms, species and healthy/diseased status, on both synthetic and biological samples. HARMONIC was applied in various real-world scenarios, especially on tissues with clear morphological boundaries, including cortical layers in mouse brain, medullary-cortex structures in mouse kidney, as well as tumor-stromal/immune interface. Significant refinement of false-positive/negative predictions was observed compared to ST-only CCC tools.

bioinformatics↗

bioRxiv2026

Glucokinase links metabolism and lineage plasticity in neuroendocrine prostate cancer via interaction with AKT1

Cancer cells frequently rewire their metabolism to sustain growth and survival under stress. Despite the critical role of metabolic adaptation in tumorigenesis, how specific metabolic enzymes regulate lineage plasticity remains unclear. Here, through FDG-PET imaging and transcriptomic analyses, we reveal markedly elevated glucose uptake in neuroendocrine prostate cancer (NEPC) and identify glucokinase (GCK) as a MYCN-induced metabolic enzyme. Beyond its metabolic role, GCK is indispensable for maintaining the neuroendocrine lineage of prostate cancer cells by establishing a functional circuit with AKT1 through reciprocal regulation--AKT1 binds and phosphorylates GCK at S373, whereas GCK phosphorylates AKT1 at S473. Pharmacological disruption of this AKT1-GCK axis suppresses tumor growth in NEPC mouse models and patient-derived xenografts. Altogether, our findings uncover both the metabolic and noncanonical kinase functions of GCK and establish the AKT1-GCK axis as a key link between metabolic reprogramming and neuroendocrine lineage transition in prostate cancer.

cancer biology↗