Biology subjects

Du, H.

Publications and source records attributed to Du, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Expanding genetic code to generate human brain organoids with both vasculature and microglia

Brain organoids offer an invaluable model system for studying human brain development and disease. However, the establishment of high-fidelity brain organoids with multiple cell lineages including vasculature and immune cells remains a huge challenge. Here, we present a new strategy to generate human cerebral organoids with vasculature and microglia-like cells using genetic code expansion technology (GCE-T) via site-specific protein engineering. The strategy integrates orthogonal genetic translation machinery in hPSCs via PiggyBac transposon system, enabling temporally control of ETV2 expression and endothelial differentiation in hPSC-derived cerebral organoids. The vascularized human cerebral organoids (vhCOs) exhibit coordinated development of multiple cell lineages and blood-brain barrier (BBB) features. Moreover, vhCOs form perfusable vascular network after transplanted in the immune-deficient mice. Single-nucleus RNA sequencing reveals enhanced neurovascular interactions, multi-brain-regional identities, diverse neuronal subtypes and specialized endothelial subclusters in vhCOs, closely resembling human fetal brain. Strikingly, we identify enriched microglia-like cells comprising three distinct subtypes in vhCOs, which contribute to microglia-vascular interactions and synergistically modulate vascular development. Upon Zika virus (ZIKV) infection, vhCOs show neurovascular dysfunction and impaired microglia development, offering new insights into viral-induced neurodevelopmental disorders. This study offers a unique platform for producing more valuable brain organoids with vasculature and immune components, opening a new avenue to advance organoid research and applications.

bioengineering↗

bioRxiv2026

Evolutionary Origins of Molecular Programs Underlying Brain Circuitry

The vertebrate pallium harbors independently evolved structures that, nevertheless, support strikingly similar sensory and cognitive circuit architectures. The mechanisms and evolutionary timing driving the emergence of these parallel pallial circuits remain unelucidated. Here, we integrated spatial transcriptomic and single-nucleus RNA-seq datasets from eight representative vertebrate species spanning approximately 500 million years of evolution to reconstruct the evolutionary assembly of the primary sensory-allocortical (Pr-Al) molecular axis, a conserved cortical hierarchical axis defined in our prior work. We uncovered that Pr- and Al-like neuronal identities are deeply conserved across sarcopterygians, encompassing all tetrapods and lobe-finned fishes. Intriguingly, this ancestral neuronal homology is uncoupled from spatially partitioned patterning: only tetrapods further compartmentalized these Pr- and Al- neurons into distinct pallium regions. Functional enrichment of Pr- and Al- gene programs uncovered a conserved tetrapod genetic core suite including MAPK signaling and axon guidance pathways. This core toolkit underwent sequential functional refinement from amphibians through mammals. Notably, mammals and birds convergently evolved association-cortical molecular profiles enriched for synaptic regulatory genes to support advanced cognitive functions. Collectively, this work delineates a stepwise vertebrate pallium evolutionary paradigm that explains how conserved molecular modules shape spatially organized brain circuitry across deep evolutionary time.

evolutionary biology↗

bioRxiv2026

Boosting carbon fixation and microbial dynamics in the coastal sediment ecosystem through large-scale cultivation of Gracilariopsis lemaneiformis

Microorganisms are the key drivers of carbon cycling in coastal marine sediment ecosystems, significantly influencing carbon storage and release during Gracilariopsis lemaneiformis cultivation. This study employed 16S rRNA sequencing, a high-throughput qPCR chip, and carbon isotope labeling to assess the impact of G. lemaneiformis cultivation on carbon cycling processes in coastal sediments. A comparative analysis was conducted between cultivated zones (GZ) of G. lemaneiformis and adjacent control zones (CZ). The results indicated that macroalgae cultivation significantly modified sediment-seawater exchange dynamics and accelerated carbon cycling within coastal marine sediment ecosystems. Furthermore, G. lemaneiformis cultivation increased the abundance of genes linked to polysaccharide degradation and carbon fixation pathways, thereby enhancing carbon cycling efficiency. The ecosystem multifunctional index, calculated based on carbon fixation gene abundance, was significantly higher in GZ compared to CZ. Incubation experiments using 13C-NaHCO3 demonstrated that cultivation markedly elevated the carbon fixation rate of sediment, emphasizing a higher potential for carbon sequestration in sedimentary environments cultivated with macroalgae. Additionally, cultivation significantly altered sediment microbial communities, simplifying their structural complexity. Key microbial taxa identified via k-core species analysis--including Subgroup10 of Desulfobacterota and MBNT15, correlated strongly with carbon fixation rates, indicating their pivotal roles in sediment carbon cycling processes. This study provides critical insights into how large-scale macroalgae cultivation influences coastal carbon dynamics and informs strategies for optimizing carbon management in aquaculture ecosystems. ImportanceGracilariopsis lemaneiformis cultivation is a widely promoted eco-aquaculture model along Southeast Chinas coast. This study finds it can drastically boost carbon sequestration efficiency in coastal sediments. Through field comparison and isotope tracing, we confirm that key carbon-fixing microbes in farmed sediments show significantly higher activity, with far stronger carbon storage potential than non-farmed zones. This research delivers direct scientific evidence for scaling up macroalgae farming to unlock new blue carbon gains, and offers a practical new solution for optimizing carbon management in aquaculture ecosystems.

microbiology↗

bioRxiv2026

Acoustic Characteristics of Low-Frequency Vocalizations of Bryde's Whales (Balaenoptera edeni edeni) in the Weizhou Island Waters of the Beibu Gulf, China

Brydes whales (Balaenoptera edeni edeni) are nationally protected in China, and the waters around Weizhou Island in the Beibu Gulf support one of the countrys few regularly observed coastal groups. However, acoustic data for this population remain limited, and the potential effects of local vessel noise are poorly described. We conducted 16 vessel-based surveys around Weizhou Island and adjacent waters in January 2024 using a low-disturbance sailboat platform and passive acoustic recorders, with concurrent visual observations where possible. We identified 734 low-frequency signals classified as putative Brydes whale vocalizations and quantified their temporal and spectral parameters. Call duration was significantly negatively correlated with maximum frequency and center frequency, but not with minimum frequency or bandwidth. Comparisons with published records indicate that the recorded signals are most similar to vocalizations previously reported from juvenile Brydes whales or mother-calf pairs, although individual source attribution could not be confirmed. Speedboat passage significantly increased root-mean-square sound pressure levels, and the dominant noise band overlapped the frequency range of the recorded Brydes whale signals, indicating potential for acoustic masking. These results expand the bioacoustic baseline for Brydes whales in Chinese coastal waters and provide evidence relevant to the management of vessel activity and whale-watching tourism around Weizhou Island.

animal behavior and cognition↗

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

A generalizable system for antigenic peptide targeting across HLA-I allotypes

T cell receptors (TCRs) and TCR-mimicking antibodies recognize peptide antigens in the context of specific Human Leucocyte Antigen (HLA-I) allotypes, and the extreme polymorphism of the HLA locus limits the breadth of immunotherapy development. Key barriers include divergent molecular surfaces on HLA proteins and differences in the peptide structure. As a result, existing modalities cannot confer therapeutic coverage across patients of divergent genetic backgrounds. Here, we develop an approach which combines a peptide conformational prediction tool, PepPred, with a cross-HLA binding protein engineering system, TRACeR-I1, to outline a generalized framework for developing binders (xTRACeRs) with compatibility across HLA allotypes while maintaining high levels of specificity towards the peptide antigen. We use our system to develop and validate xTRACeRs against clinically relevant, established peptide antigens presented across common alleles within five HLA-A/B/C supertypes2. Cryo-EM structures of xTRACeR-pHLA complexes for an oncofetal antigen from PRAME and a neuroblastoma-specific peptide from PHOX2B reveal effective mechanisms to navigate polymorphic HLA surface residues, and extensive interactions with the peptide. We implemented these two xTRACeRs as Chimeric Antigen Receptor (CAR) T cells and demonstrated their potent killing efficacy and specificity. Overcoming restriction across HLA supertypes lifts a key barrier in HLA-targeted immunotherapy by expanding patient coverage.

synthetic biology↗

bioRxiv2026

Autoluminescence characteristics of 25 Phalaenopsis orchids following transient transformation with eFBP2

Engineering autoluminescent plants, especially horticultural crops, has recently emerged as a promising research area, with one current approach involving the transgenic introduction of fungal bioluminescence pathway genes. Although autoluminescent plants such as tobacco and petunia have been created, it remains unclear whether all horticultural plants have the potential to be autoluminescent after genetic modification, especially those having flowers with dark colors and thick cuticles. To understand whether, and what if any, floral traits affect autoluminescence potential, we assess the autoluminescence characteristics of 25 representative Phalaenopsis cultivars after transient transformation of fungal bioluminescence pathway genes, alongside several key morphological and biochemical traits. Our results demonstrate that autoluminescence characteristics are correlated with floral color lightness, organ textures and epidermal cell types. In contrast, the content of the substrates of luciferin--caffeic acid and tyrosine, and the infiltration ease of inoculation solution into floral organs after injection, have limited effects on autoluminescence characteristics. Autoluminescence intensity can be reasonably predicted using five floral traits investigated, as 80.4% of variation can be explained by these traits. Our study not only identifies specific Phalaenopsis cultivars with high potential for developing autoluminescent lines but also provides a selection framework applicable to other horticultural crops.

plant biology↗

bioRxiv2026

Damaging the conical morphology of HIV-1 capsid by targeting the FG-binding pocket and disfavoring pentameric subunits needed for core closure

The HIV-1 capsid is an essential viral component, targeted by the long-acting antiretroviral Lenacapavir (LEN). LEN binds to the HIV-1 capsid protein (CA) at the phenylalanine-glycine (FG) binding pocket (FGBP), a site for multiple host-factor and antiviral interactions in CA hexamers (CAHEX). Previously, we generated a chemical library to investigate the FGBP; ZW-1261, a lead compound, exhibits potent antiviral activity and strong inter-subunit interactions within CAHEX. Here, we report the molecular mechanism by which ZW-1261 affects the morphology and integrity of capsid lattice. ZW-1261 alone rapidly induces tubular CA assemblies; simultaneous addition of ZW-1261 with the assembly cofactor inositol hexaphosphate (IP6) forms morphologically distinct tubes. In mature virions, IP6 is required for the assembly of both CAHEX and CA pentamers (CAPENT). Cryogenic-electron microscopy analysis of in vitro assembled capsid-like particles (CLPs) with IP6 suggests that ZW-1261 leads to the absence of CAPENT and damages the pre-formed conical lattice. To elucidate how this FGBP-targeting antiviral impacts CAPENT, we further solved structures of CAPENT-only icosahedral assemblies (T = 1), formed by reported mutations, that were treated with ZW-1261. We find that ZW-1261 binding in these constrained T = 1 assemblies converts CAPENT to a CAHEX-like conformation. Collectively, this suggests a mechanism by which addition of FGBP-binding inhibitor to native cores leads to the absence of CAPENT, impacting capsid closure and core integrity.

molecular biology↗

bioRxiv2026

OmicClaw: executable and reproducible natural-language multi-omics analysis over the unified OmicVerse ecosystem.

Advances in bulk, single-cell and spatial omics have transformed biological discovery, yet analysis remains fragmented across packages with incompatible interfaces, heterogeneous dependencies and limited workflow reproducibility. Here, we present OmicClaw, an executable natural-language framework for multi-omics analysis built on the unified OmicVerse ecosystem and the J.A.R.V.I.S. runtime. OmicVerse organizes upstream processing, preprocessing, single-cell, spatial, bulk-transcriptomic and foundation-model workflows into a shared AnnData-centered interface spanning more than 100 methods. J.A.R.V.I.S. converts this ecosystem into a bounded analytical action space through a registry-grounded, state-aware and recoverable execution layer that validates prerequisites, preserves provenance and supports iterative repair, while enabling conversational, notebook and visual interfaces to operate over the same live analytical state. Rather than relying on unconstrained code generation, OmicClaw translates user requests into traceable workflows over live omics objects. Across a benchmark of 15 tasks spanning scRNA-seq, spatial transcriptomics, RNA velocity, scATAC-seq, CITE-seq and multiome analysis, ov.Agent improved rubric-based performance over bare one-shot large language model baselines, particularly for long-horizon multi-step workflows. OmicClaw further supports external agent access through an MCP-compatible server and a beginner-friendly web platform for interactive analysis, code execution and million-scale visualization. Together, OmicClaw provides a practical foundation for reproducible human-AI collaboration in modern multi-omics research

bioinformatics↗

bioRxiv2026

The emergence of the language system in the toddler brain

Toddlerhood is a time when childrens language competence undergoes a dramatic transformation, making it a key period to examine the emergence of the brains language system. Functional magnetic resonance imaging data from 29 awake toddlers (19-36 months) scanned on a child-friendly language task reveal that, already at this young age, areas in the left frontal and temporal cortex respond more to comprehensible language (i.e., videos of puppets speaking in English) than the control condition (matched videos with incomprehensible audio). Although the magnitude of response to language is substantially weaker than in adults, the topography is already adult-like, challenging claims that the frontal component or left-hemispheric dominance do not emerge until later in life.

neuroscience↗

bioRxiv2026

Systematic Evaluation of Transfer Learning Strategies for Clinical Chemotherapy Response Prediction

Accurately predicting chemotherapy response remains a major challenge in precision oncology. Although machine-learning models based on tumour omics data have shown promise, the majority of existing studies are trained and evaluated on pre-clinical cell-line datasets, leaving their clinical applicability insufficiently characterised. In this study, we systematically evaluate a range of transfer-learning strategies for chemotherapy response prediction under realistic clinical constraints using patient data from The Cancer Genome Atlas (TCGA). Rather than proposing a new predictive model, we focus on assessing the effectiveness and limitations of commonly used approaches for transferring pre-clinical knowledge to clinical settings. These include cell-line-validated biomarkers, biologically informed feature representations, direct application of pre-clinical deep-learning models, model fine-tuning, and hybrid strategies that integrate pre-clinical predictions with clinical data. All methods are evaluated within a unified framework using consistent cohort construction, shared performance metrics, and bias-controlled validation procedures. Across multiple drugs and molecular data types, we find that most transfer strategies--including biomarker-based feature selection and direct pre-clinical model transfer--fail to produce robust or consistent improvements in clinical prediction performance. In contrast, conservative approaches based on fine-tuning pre-clinical models or incorporating pre-clinical predictions as features in clinical models yield more stable and reproducible gains. Further improvements are observed when basic pre-treatment clinical variables are integrated. Together, our results demonstrate the practical boundaries of pre-clinical to clinical transfer for drug response prediction and highlight hybrid and fine-tuning strategies as more reliable baselines for future translational modelling efforts.

bioinformatics↗

bioRxiv2026

Healthcare Infrastructure Shapes Evolutionary Trade-offs and Geographic Dissemination of Multidrug-Resistant Acinetobacter baumannii

Antimicrobial-resistant pathogens pose an existential threat to modern medicine, yet the evolutionary forces driving their adaptation in healthcare systems remain largely unexplored. We revealed that hospital network architecture functions as a primary selective pressure, driving pathogen evolution through infrastructure-dependent virulence-transmission trade-offs. Phylogenomic analysis of 5,023 Acinetobacter baumannii isolates across Chinas centralized healthcare system identifies two co-existing evolutionary strategies: a virulence-optimized clade (ESL2.4) that spread slowly (20.4 km per year) in low-connectivity hospitals, and a transmission-optimized clade (ESL2.5) that disseminate rapidly (65.2 km per year) through mega-city healthcare hubs, likely attributed to its capsule conversion and increased upper respiratory colonization. Comparative analysis with European A. baumannii populations demonstrates that healthcare connectivity, not geography, governs pathogen distribution through convergent genomic adaptations. Our simulation suggests competitive asymmetries of the two clades, following the ecotype principle and enabling stable coexistence. The COVID-19 pandemic provided a natural experiment validating these mechanisms: outpatient restrictions reduced transmission-optimized lineage spread by 89%, while virulence-optimized lineage persisted through inpatient networks. These findings establish healthcare infrastructure as a critical evolutionary driver with immediate implications for predicting and controlling antimicrobial resistance emergence across diverse healthcare systems.

microbiology↗

bioRxiv2026

Dynamic control of Raf-ERK signaling modulates neuronal activity across biological scales

Neuronal activity robustly engages the extracellular signal-regulated kinase (ERK) signaling pathway through Ca2+-dependent mechanisms; however, whether ERK can acutely and causally modulates ongoing neuronal activity remains unsolved due to complex upstream regulation and diverse subcellular functions. Here, we directly address this question using an optogenetic ERK activator, opto-miniRaf, that enables selective, rapid, graded, and reversible control of ERK signaling. Combining this AAV-compatible system with calcium imaging and electrophysiology, we interrogate ERK functions across biological scales, from cultured neurons, acute brain slices, and the intact brain. Acute optogenetic activation of ERK enhances synchronized network burst activity in cultured rat cortical neurons and increases calcium activity of cortical pyramidal neurons in awake and moving mice following non-invasive light stimulation. Together, these results establish ERK signaling as an acute modulator of neuronal and network activity, positioning opto-miniRaf as a generalizable platform for precise spatiotemporal control of intracellular kinase signaling in complex biological systems.

neuroscience↗

bioRxiv2025

Structural, biophysical, and virological mechanistic characterization of HIV-1 capsid-targeting antivirals

Due to its significant role in virus replication, the HIV capsid is an attractive antiviral target. This is validated by the recent clinical approval of lenacapavir for both treatment and pre-exposure prophylaxis (PrEP). PF74 is a well-characterized capsid-targeting antiviral that was discontinued in further study due to potency and metabolic issues. We hypothesized that making chemical modifications at certain sites of PF74 could result in capsid-targeting antivirals with improved potency and bioavailability. Our cumulative studies show that making changes at the R1 and R3 positions of PF74 results in compounds with increased antiviral potency, increased stability of wild-type HIV capsid hexamers and virions, tighter binding to wild-type HIV capsid hexamer compared to PF74, and different interactions at the "FG" binding site of capsid compared to PF74. These data provide insights into the design of future capsid-targeting antivirals relevant for clinical use.

biochemistry↗

bioRxiv2025

Dose-dependent NFI regulation of progenitor lifespan and output underlying human neocortical malformation

Nuclear Factor I (NFI) misexpressions in humans are associated with severe brain malformations, yet the underlying mechanisms remain poorly understood. Here we show that NFIs regulate the broad lineage progression and lifespan of radial glial progenitors (RGPs), and consequently neocortical development in a dose-dependent manner. Human cerebral organoids carrying patient-mimicking NFI mutations exhibit expression level-dependent bidirectional impairments in RGP temporal development, coinciding with patient phenotypes. In mouse models, selective removal of NFIs leads to a dramatic protraction of RGP lineage progression and lifespan, excessive progeny output, and neocortical overgrowth and abnormal folding, whereas overexpression of NFIs accelerates RGP lineage progression, resulting in developmental stage-dependent precocious productions of diverse neural progenies. Moreover, NFIs exhibit a positive auto-regulation and progressive increase in expression, and regulate distinct temporal-specific targets underlying RGP lineage progression. These results suggest that NFIs act as evolutionarily conserved key global temporal regulators of RGP lineage progression and neocortical development. HIGHLIGHTSO_LINFIs affect human RGP temporal development coinciding with patient phenotypes. C_LIO_LINFI removal protracts RGP lineage progression and lifespan with excessive progeny output. C_LIO_LINFI overexpression accelerates RGP lineage progression with precocious progeny output. C_LIO_LINFIs regulate distinct temporal-specific targets underlying RGP lineage progression. C_LI

neuroscience↗

bioRxiv2025

MS4MS: LLMs-driven Multi-agent System for Small-molecule Identification via LC-MS/MS

Small molecule identification is central to research fields such as drug discovery, but in complex systems like Traditional Chinese Medicine (TCM), traditional mass spectrometry analysis methods remain constrained by bottlenecks including insufficient database coverage, fragmented analysis workflows, and poor result interpretability. To address these limitations, we developed MS4MS, a large language model-driven multi-agent system that enables an end-to-end automated pipeline from raw data to small molecule identification. Validation on a public benchmark demonstrates that MS4MS achieves state-of-the-art performance in molecular formula prediction. Furthermore, its innovative small molecule identification agent enables efficient and interpretable compound elucidation. Verification using herbal extracts indicates MS4MSs outstanding performance regarding analytical coverage and the discrimination of isomers. Consequently, MS4MS offers a novel, accurate, interpretable, and high-throughput end-to-end automated strategy for small molecule identification, overcoming the analytical bottlenecks of traditional mass spectrometry in natural products and complex TCM systems.

bioinformatics↗

bioRxiv2025

Transcriptomic insights into developmental toxicity of per- and poly-fluoroalkyl substances (PFAS) in Caenorhabditis elegans: The potential key role of xenobiotic detoxification pathway

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants known to induce developmental toxicity across multiple species, yet the molecular mechanisms are still not fully understood. This study aims to evaluate the developmental toxicity of four long-chain legacy PFAS (PFOA, PFOS, PFNA, PFDA) and one short-chain alternative (PFBA) at environmentally relevant concentrations (1-5 M) using the model organism Caenorhabditis elegans, with a focus on elucidating the underlying molecular mechanisms. Phenotypic analysis indicated that PFDA and PFOS significantly delayed development of worms, and reduced the number of fertilized eggs in the uterus. RNA-seq and subsequent bioinformatic analysis revealed strong impacts of PFDA and PFOS on physiological age. A core set of xenobiotic detoxification genes (e.g., cyp-13A4, cyp-13A6, and cyp-13A7), which were found to be primarily regulated by nuclear hormone receptors (NHR-102, NHR-85, NHR-28), showed consistent up-regulation upon PFAS exposure. Gene co-expression network analysis (WGCNA) further linked this detoxification gene signature to developmental impairment. Cross-species comparison using public databases identified several evolutionarily conserved detoxification genes that are associated with PFAS-induced developmental toxicity, among which CYP3A4 and its orthologs appear to be emerging biomarkers of PFAS exposure. Our findings demonstrate that activation of conserved xenobiotic detoxification pathways is a central transcriptomic signature of PFAS exposure, providing mechanistic insights into the structure-dependent developmental toxicity of this kind of pervasive pollutant. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/689658v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@c50b2borg.highwire.dtl.DTLVardef@605b6dorg.highwire.dtl.DTLVardef@125fa8org.highwire.dtl.DTLVardef@464d34_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

pharmacology and toxicology↗

bioRxiv2025

Viral protease-Initiated Pyroptosis Activator mRNA therapy as a Universal Antiviral Strategy

Although therapeutic drugs targeting gasdermin (GSDM)-mediated pyroptosis have made remarkable progress in treating various diseases, their potential for antiviral therapy remains largely unexplored. Inspired by the autoinhibitory mechanism of GSDM proteins and the clinical success of mRNA vaccines, herein we propose a concept of viral protease-initiated pyroptosis (VIP) mRNA therapy as a universal antiviral strategy. Using Hepatitis A virus (HAV) as a model, we rationally engineered an HAV-specific VIP activator (VIPA) by replacing the native gasdermin D (GSDMD) cleavage motif with that of HAV 3C protease. Expression of this VIPA selectively triggered pyroptosis in HAV-infected cells, thereby terminating viral replication. Remarkably, in vivo delivery of VIPA mRNA via lipid nanoparticles (LNPs) significantly suppressed viral replication and shedding, alleviated liver injury, and elicited a pyroptosis-driven antiviral immune response in uninfected cells. Similarly, VIPA against Zika virus (ZIKV) also exhibited potent antiviral efficacy in both cell culture and mouse models. Furthermore, a generative artificial intelligence (AI) platform was deployed to design de novo cleavage motifs for the SARS-CoV-2 main protease NSP5, together with experimental screening, yielding optimized VIPAs with enhanced antiviral potency. Our work establishes the concept of VIPA mRNA therapy as a versatile platform for the treatment of diverse viral infections via "kill-and-alert" mechanism.

microbiology↗