Biology subjects

He, W.

Publications and source records attributed to He, W..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Complete Genomes of Cultivated Gut Bacteria Reveal Mobile Genetic Element-Driven Functional Diversity with Therapeutic Implications

Cultivated bacterial isolates are essential for elucidating gut microbiota functions, yet reliance on fragmented draft genomes and limited mobile genetic element (MGE) annotation has constrained high-resolution analyses. Here, we present the Cultivated Complete Genome Reference (CCGR), a comprehensive compendium of 1,150 fully circularized human gut bacterial genomes. Overcoming draft limitations, CCGR achieves chromosome-scale resolution and reveals distinct evolutionary strategies shaping gene topological organization in response to bacterial growth. Furthermore, we decode the dynamic landscape of MGEs, demonstrating that broad-host-range phages follow strict positional patterns by integrating at conserved chromosomal hotspots flanked by nutrient transporter loci. Importantly, we provide mechanistic in vivo evidence that accessory genomic elements drive strain-level functional heterogeneity. Specifically, the plasmid-encoded scrK gene in Levilactobacillus brevis involved in fructose catabolism is required to mitigate fructose-diet-exacerbated colitis. Collectively, CCGR establishes a framework linking chromosomal architecture and MGEs to bacterial evolution and host health, enabling precise, strain-resolved functional investigations.

microbiology↗

bioRxiv2026

Hyperactive STAT1 Promotes T Follicular Helper Type 1 Cell Differentiation to Trigger Autoimmunity

ABSTRACTSHeterozygous gain-of-function (GOF) mutations in signal transducer and activator of transcription 1 (STAT1) cause an inborn error of immunity characterized by immune dysregulation, recurrent infections and various autoimmune manifestations. However, the precise pathogenic mechanism by which STAT1 GOF contributes to autoimmunity remains elusive. In our cohort, STAT1-GOF patients exhibit biased circulating follicular helper T (cTfh) populations with CXCR3+ Tfh1-like features. Using a Stat1 GOF mouse model that spontaneously developed autoimmunity, we found that overactivated STAT1 promotes Tfh differentiation and disrupted T cell-dependent humoral responses with skewed immunoglobulin class switching towards IgG2. Furthermore, STAT1 GOF directly targets to Tfh and Th1 cell signature genes and thereby drives the development of Tfh1 cells with excessive IFN-{gamma} production, which implicated in autoantibody production and the development of autoimmunity. Notably, IFN-{gamma} neutralization significantly alleviated autoimmune cellular responses and autoantibody levels in mutant mice, highlighting IFN-{gamma} blockade as a promising targeted therapy for the STAT1-GOF patients with autoimmunity. Our findings suggest that proper regulation of STAT1 activity within a reasonable magnitude is crucial for ensuring optimal host-protective humoral immunity. One-sentence summaryOveractivated STAT1 promotes Tfh1 differentiation to drive autoimmunity.

immunology↗

bioRxiv2026

ProteinMCP: An Agentic AI Framework for Autonomous Protein Engineering

Computational protein design is often constrained by slow, complex, inaccessible, and highly sophiscated and expert-dependent workflows that hinder its transferrability and generalization power for broader applications. We present ProteinMCP, an agentic AI framework designed to accelerate and democratize protein engineering. ProteinMCP automates end-to-end scientific tasks, delivering dramatic gains in efficiency; for instance, a comprehensive protein fitness modeling workflow was completed in just 11 minutes. This performance is achieved by an AI agent that intelligently orchestrates a unified ecosystem of 38 specialized tools, made accessible through a Model-Context-Protocol (MCP). A cornerstone of the framework is an automated pipeline that converts existing software into MCP-compliant servers, ensuring the platform is both powerful and perpetually extensible. We further demonstrate its capabilities through the successful autonomous design and selection of high-affinity de novo binders and therapeutic nanobodies. By removing technical barriers, ProteinMCP has the potential to shorten the design-build-test cycle and make advanced computational protein design accessible to the broader scientific community.

bioinformatics↗

bioRxiv2026

ATP-independent unfolding of ubiquitin by Ufd1 initiates Cdc48/p97-mediated substrate processing

The Cdc48 ATPase (p97 or VCP in mammals) cooperates with its cofactors Ufd1 and Npl4 to extract polyubiquitinated proteins from membranes or multi-subunit complexes, promoting their proteasomal degradation. A ubiquitin molecule in the chain is unfolded in an ATP-independent manner and initiates substrate translocation through the central pore of the ATPase. How ubiquitin is unfolded remains unclear. Here, we demonstrate that the UT3 domain of Ufd1 interacts simultaneously with two Lys48-linked ubiquitins and unfolds one of the ubiquitins by binding its C-termianl {beta}-strand into a cleft. This unfolded ubiquitin is subsequently captured by Npl4 and Cdc48/p97. Experiments in vitro and in cells show that unfolding-defective mutants of Ufd1 indeed compromise Cdc48/p97 function. Our results explain how simple protein-protein interactions cause the unfolding of the remarkably stable ubiquitin. We also establish a linkage-specific recognition that involves ubiquitin unfolding.

biophysics↗

bioRxiv2026

A Single-Cell Temporal Atlas of Mouse Nasal Embryonic Development

The mammals breathe and perceive odors through anatomically and functionally distinct respiratory and olfactory regions of the nose; however, how the early embryo endows this system remains largely unknown. Here, we present a temporal high-resolution single-cell RNA sequencing (scRNA-seq) atlas of mouse nasal development, comprising 183,247 cells collected from 20 embryos spanning embryonic day 10.5 (E10.5) to E18.5. We identified 7 major cell clusters and 52 molecularly defined subtypes, including previously unrecognized rare populations and niche-derived signaling components involved in progenitor cell maintenance. Lineage reconstruction of epithelial and mesenchymal compartments revealed dynamic cell fate transitions and highlighted candidate regulators of lineage specification, including Foxa1 as a regulator of nasal respiratory ciliated epithelium differentiation. Integration with adult nasal epithelium datasets further delineated transcriptional dynamics of olfactory stem cells. This study provides a molecular roadmap of nasal development and offers a valuable resource for future research into nasal biology and regenerative strategies.

developmental biology↗

bioRxiv2026

Control of motility and cell shape of Haloferax volcanii is linked by a transcriptional regulator

Archaea rely on motility and morphological plasticity to navigate their environments, yet the transcriptional regulation of these processes remains poorly understood. In Haloferax volcanii, archaellum-dependent motility is transcriptionally regulated, but an EarA-like master regulator is absent. Here, we identify CsmR as a transcriptional regulator that links archaellum biogenesis and cell-shape transitions in H. volcanii. Deletion of csmR abolished detectable motility, whereas overexpression increased motility and promoted a sustained rod-like morphology. Comparative transcriptomics defined a CsmR-associated regulon that includes archaellum and chemotaxis genes as well as rod-shape determinants (e.g., Sph3 and RdfA), and upstream motif enrichment supports a direct role for CsmR in transcriptional control. Furthermore, csmR and cirA, a KaiC-like regulator, share extensive transcriptional overlap, with CirA likely fine-tuning CsmR-mediated regulation through post-translational modification. These findings establish CsmR as a key integrator of motility and cell shape regulation in Haloferax volcanii, suggesting that haloarchaea coordinate these fundamental processes through an unidentified transcriptional network. Moreover, Northern blotting and cell shape observation suggest that transcription factor RosR is involved in the regulation of an sRNA that shares extensive overlap with the cirA gene, possibly fine-tuning the effect of CirA on the regulation of the archaellum cluster and the rod shape determinants sph3 and rdfA. Understanding this interplay provides new insights into archaeal adaptability and may reveal broader regulatory principles in prokaryotic cell biology.

microbiology↗

bioRxiv2026

RNAseq analysis reveals the recurrent loss of heterozygosity in lung cancer and associated transcription patterns

A key limitation in cancer transcriptomics is the lack of accompanying genomic profiling such as whole-genome sequencing (WGS) or copy number alteration (CNA) data. Here we address this by showing that RNA-seq alone can be used to infer chromosomal aberrations and identify biologically meaningful patterns in lung cancer. Through a large-scale meta-analysis of publicly available RNA-seq datasets from non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), and matched controls, we reconstructed large scale CNA profiles and identified deletions in 3p, 9p, and 17p as the most frequent genomic events. Validation against paired WGS data confirmed a high degree of accuracy for RNA-seq-based inference. Our analyses revealed that while deletion-associated transcriptional heterogeneity exists, approximately 25% of differentially expressed genes were shared across all three deletion classes, indicating a conserved oncogenic program in lung cancer. Enrichment analysis linked these shared genes to pathways governing cell division, DNA replication, and extracellular matrix organization, while deletion-specific effects reflected disruption of tumor suppressor pathways, notably p53 signaling in 17p-deleted tumors, leading to deregulation of NOS2 and PLOD2. Integrating gene-level expression data, we identified both shared and deletion-specific biomarkers: TPX2 was consistently overexpressed across all deletion groups, while PTPRZ1 and CLDN9 were uniquely associated with del3p and del9p, respectively. Experimental validation in lung cancer cell lines confirmed these predictions, particularly the upregulation of CLDN9 in del9p carriers. By demonstrating that RNA-seq data can capture large-scale chromosomal events and reveal their transcriptional consequences, this study establishes an efficient framework for genomic inference and biomarker discovery, introducing CLDN9 as a novel, deletion-specific marker with potential prognostic and therapeutic value for 9p-deleted lung cancers.

cancer biology↗

bioRxiv2025

The impact of downsampling on data quality, univariate measurement and multivariate pattern analysis in event-related potential research

The choice of sampling rate is a critical preprocessing step in event-related potential (ERP) research, yet its impact on different analytic approaches remains underexplored. In this study, we systematically evaluated how downsampling affects data quality measured via Standardized Measurement Error (SME), conventional univariate ERP metrics (mean amplitude, peak amplitude, peak latency, and 50% area latency), and multivariate pattern analysis (MVPA; decoding). We analyzed seven commonly studied ERP components: P3, N400, N170, N2pc, mismatch negativity, error-related negativity, and lateralized readiness potential collected from neurotypical young adults. Results showed that both amplitude- and latency-based scores were significantly affected by sampling rate changes, particularly for 50% area latency that presented increased SME (reduced data quality) at lower sampling rates. Amplitude-based measures and their corresponding effect sizes were more influenced by sampling rate variations, whereas latency-based measures were comparatively stable across different temporal resolutions. In contrast, multivariate decoding performance remained highly robust, with decoding accuracy and effect sizes showing minimal variation even at the lowest sampling rate (e.g., 64 Hz). Overall, these findings suggest that caution should be exercised when employing lower sampling rates for data quality and conventional univariate ERP analyses. Nevertheless, lower sampling rates (e.g., 64 Hz) may still be appropriate for decoding analyses, particularly in studies where precise temporal resolution is not critical. For researchers analyzing ERP data with similar components, noise levels, and participant populations as in this study, following these recommendations should yield robust statistical power.

neuroscience↗

bioRxiv2025

Multicolored, Sonosensitizer-optimized Organic Mechanoluminescent Nanoparticles for Functional Sono-optogenetics

Light enables precise visualization and control of cellular processes, but its utility in deep tissues is fundamentally limited by poor optical penetration, particularly in the deep brain. Ultrasound-triggered mechanoluminescence offers a non-invasive strategy for remote light delivery, yet existing organic systems remain monochromatic and low-intensity, largely due to an incomplete understanding of ultrasound-induced emission. Here, we report a multicolor mechanoluminescence platform that couples reactive oxygen species-responsive chemiluminescent donors with fluorescent acceptors via Forster resonance energy transfer, generating tunable emission from blue (459 nm) to red (592 nm). Systematic screening potentially reveals that electronic energy gap-dependent reactive oxygen species generation serves as a predictive design principle for high-performance mechanoluminescent materials. The emitted spectrum and intensity are sufficient to activate ChR2 and ChRmine and inhibit eOPN3, enabling bidirectional, fiber-free neuromodulation under focused ultrasound. By integrating spatially precise ultrasound with programmable photon output, this platform establishes a non-invasive strategy for deep-tissue neural monitoring and provides a foundation for applications in bioimaging, gene editing, and precision therapeutics.

bioengineering↗

bioRxiv2025

A haplotype-resolved T2T genome assembly of Indigofera pseudotinctoria reveals the genetic basis of flavonoid biosynthesis in Chinese Indigo

Indigofera pseudotinctoria, commonly known as Chinese Indigo, is a multifunctional leguminous shrub widely distributed in East Asia, valued for its medicinal, ecological, and forage importance, and naturally adapted to drought and nutrient-poor soils. However, the absence of genomic resources has hindered insights into the genetic basis of its bioactive metabolites and adaptive traits. Here, we present a haplotype-resolved, telomere-to-telomere (T2T) reference genome of I. pseudotinctoria, which represents the first complete genome within the genus Indigofera. By integrating PacBio HiFi sequencing, Oxford Nanopore ultra-long reads, and Hi-C chromatin conformation sequencing technologies, we successfully constructed two gap-free haplotypes assemblies (647.38 Mb and 657.52 Mb), characterized by high BUSCO completeness and QV scores, and fully captured all telomeric sequences. Comparative analysis between haplotypes revealed extensive synteny but notable structural heterozygosity but notable structural heterozygosity. Approximately 46% of structural variations overlap with genic or regulatory regions, leading to allele-specific expression divergence. Between the two haplotypes, we identified 2,607 and 2,331 haplotype-specific genes, reflecting a complementary functional specialization in defense and repair versus metabolism and growth. Integrative transcriptomic and metabolomic profiling across six tissues reconstructed the flavonoid biosynthetic network and identified MYB, bHLH, NAC, WRKY, and ERF transcription factors regulating five key pharmacologically active flavonoids (Calycosin, Butein, Sulfuretin, Chrysoeriol, and Genistin). These results collectively uncover the haplotype-specific regulatory and structural basis of Indigofera pseudotinctoria and establish a high-quality genomic framework for evolutionary, medicinal, and metabolic engineering studies in leguminous plants, and provide a framework for molecular breeding and bioactive compound discovery in medicinal legumes.

genomics↗

bioRxiv2025

Dorsomedial hypothalamus cold-sensitive neurons drive shivering thermogenesis

Hypothermia, a decline in core body temperature below 35{degrees}C in homeotherms, elicits rapid, asynchronous involuntary shivering thermogenesis; however, the hypothalamic neurons responsible for initiating this response remain uncharacterized. Here, retrograde transsynaptic tracing combined with RNA-seq identified a distinct population of VGLUT2-positive neurons enriched with Calbindin D28k (CALB1) within the dorsomedial hypothalamic nucleus (DMHCalb1/Vglut2). Convergent evidence from chemogenetic, optogenetic, fiber photometry calcium imaging, and electromyography (EMG) experiments demonstrated that these neurons selectively mediate hypothermia-triggered shivering thermogenesis. Bidirectional perturbation of DMHCalb1/Vglut2 activity modulated shivering intensity, while CALB1-negative VGLUT2-expressing DMH neurons were responsible for non-shivering thermogenesis (NST). Genetic ablation of afferent inputs from LSI/POA/VLPAG projecting to DMHCalb1/Vglut2, as well as ex vivo pharmacological synaptic blockade, failed to eliminate shivering responses during hypothermia, indicating that their activation is independent of canonical cold-responsive circuits. Hypothermia significantly suppressed transient A-type K (IA) currents, without affecting delayed rectifier K (IK) currents, accompanied by a pronounced reduction in the IA inactivation time constant relative to normothermic 36 {degrees}C. Collectively, hypothermia elevates DMHCalb1/Vglut2 excitability through IA-dependent reshaping of action potential dynamics. Shortened action potential repolarization and afterhyperpolarization duration cooperatively boost neuronal firing, constituting an intrinsic mechanism for DMHCalb1/Vglut2 neuron-driven shivering initiation.

neuroscience↗

bioRxiv2025

Nanobodies targeting hnRNPA2/B1 and tau

Heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2/B1) is an RNA-binding protein that mislocalizes to the cytoplasm and forms stress-induced granules in tauopathy and multisystem proteinopathy. It also preferentially interacts with oligomeric tau and is required for tau-mediated neurodegeneration in a mouse model of Alzheimers disease. To study endogenous hnRNPA2/B1 and tau, we generated nanobodies that specifically recognize these proteins. We screened yeast surface display nanobody libraries using an avidity-enhanced screening strategy that enabled selection of binders against short peptide ligands. This led to isolation of anti-hnRNPA2/B1 and anti-tau nanobodies with defined epitopes. Directed evolution of the anti-hnRNPA2/B1 nanobody improved binding affinity by over 20-fold but caused cytoplasmic aggregation, demonstrating a tradeoff between affinity and intracellular behavior. Although the final nanobodies retained modest affinities, they showed robust intracellular colocalization with their targets. Furthermore, fusion to ubiquitin ligase adaptor domains significantly decreased hnRNPA2/B1 and tau levels. Collectively, these nanobodies provide valuable tools for studying hnRNPA2/B1 and tau dynamics in their native cellular context.

bioengineering↗

bioRxiv2025

A Study on the Pharmacokinetic/Pharmacodynamic Profiles of the Novel PPAR Pan Agonist Chiglitazar Sodium in Rats with Hypoalbuminemia

ObjectiveTo compare the changes in the pharmacokinetic/pharmacodynamic (PK/PD) profiles of Chiglitazar Sodium between healthy rats and those with hypoalbuminemia, and to evaluate the medication safety of Chiglitazar in rats with hypoalbuminemia. MethodsLiquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) method was employed to determine the plasma concentration ofChiglitazar Sodium in both healthy rats and rats with hypoalbuminemia after administration. Pharmacokinetics were calculated based on the measured data. Blood glucose levels were monitored and recorded in both groups to observe pharmacodynamic changes. ResultsPharmacokinetic analysis revealed that, compared to the healthy group, only the Tmax in the hypoalbuminemia group was significantly earlier by 34.3% (P<0.001), while other pharmacokinetic parameters showed no significant differences. Pharmacodynamic studies indicated that blood glucose levels remained stable in both healthy rats and rats with hypoalbuminemia during the 0.25-10 hour monitoring period. ConclusionExcept for Tmax, there were no significant differences in PK/PD parameters between rats with hypoalbuminemia and healthy rats. Blood glucose levels remained stable in both groups after oral administration of Chiglitazar Sodium. The animal experimental results suggest that, under normal conditions, hypoalbuminemia does not affect the pharmacokinetic and pharmacodynamic profiles of Chiglitazar Sodium.

pharmacology and toxicology↗

bioRxiv2025

Probability Distribution for Rare Neutral Mutations in Cancers and Application to Dynamic Precision Medicine of Cancer

Cancers exhibit substantial genetic diversity between individual cells. Previous work shows greater overall diversity that also increases more quickly during a patients clinical course than heretofore expected. Rare subclones will harbor pre-existing resistance to any single agent and may cause medium to late term relapse, which may evolve further variants that have simultaneous resistance to non-cross resistant therapies. In this work, we present a probability distribution function (PDF) of the variant allele fraction (VAF), or prevalence, of a rare subclone, derived from previous evolutionary theory. We show that current clinical sequencing protocols fail to detect the vast majority of these rare subclones and that by the time of detection, simultaneous multiple resistance may already evolve. We apply the PDF to simulation of dynamic precision medicine (DPM), an evolutionary guided precision medicine paradigm that attempts to proactively eliminate singly-resistant subclones before they evolve multiple resistance, with significant potential to extend survival. We show the simulated benefit of DPM with perfect information is hampered by an inability to detect rare subclones if they are assumed to be absent when undetectable. However, the DPM benefit is restored if the PDF is used to calculate the likelihood of the subclone being present below the level of detection and incorporated into the DPM simulation and therapy recommendations in a probabilistic fashion. Two other common statistical distributions are less effective. This theoretical advance facilitates DPM and potentially other evolutionary guided approaches to precision cancer medicine in spite of the limitations of clinical sequencing. Significance StatementCancers contain many cells, each genetically unique. These variations can include pre-existing resistance to therapy, enabling relapse. DNA sequencing cannot detect minority cellular populations (subclones) below a certain size, by which time they may have already evolved simultaneous resistance to multiple therapies. We present a mathematical approach that assigns a risk that a subclone is present, and at what prevalence in the cellular population, even when undetected. We simulate applying this approach to dynamic precision medicine (DPM), which attempts to proactively eliminate singly resistant cells before they become resistant to multiple therapies. Using this probability distribution, we can retain the benefit of DPM even when most rare subclones are undetectable, in contrast to just assuming undetected subclones are absent.

systems biology↗

bioRxiv2025

Network pharmacology, bioinformatics, molecular docking and experimental verification of the mechanism of HXZTS treatment on osteoarthritis synovium

BackgroundOsteoarthritis (OA) is a prevalent joint disease characterized by synovial inflammation and synovial fibroblast dysfunction. Elucidating the molecular mechanisms underlying synovial tissue impairment in OA is crucial for developing targeted therapeutic interventions. Huoxuezhitongsan (HXZTS), a traditional Chinese medicine formula, has shown promising therapeutic effects in treating OA, but its mechanisms of action on synovial tissue remain unclear. MethodThis study integrated network pharmacology, bioinformatics analysis, molecular docking, and experimental validation to elucidate the potential targets, pathways, and mechanisms by which HXZTS exert therapeutic effects on osteoarthritic synovial tissue. ResultsNetwork analysis identified 21 active ingredients and 111 common targets of HXZTS for OA, with key compounds like quercetin, {beta}-sitosterol, and stigmasterol. Enrichment analysis revealed HXZTS modulates inflammation through TNF, IL-17, and MAPK signaling pathways, oxidative stress, apoptosis, angiogenesis, and metabolic regulation. Molecular docking demonstrated strong binding affinities of HXZTS compounds with targets like AKT1, TNF, TP53, IL6, and VEGFA. RT-qPCR validation confirmed the downregulation of inflammatory mediators like IL6 and PTGS2, alongside the upregulation of genes associated with potential cartilage repair effects, such as MMP1 and MMP3, upon HXZTS treatment. ConclusionsHXZTS exerts therapeutic effects on osteoarthritic synovial tissue through a multifaceted mechanism involving modulation of inflammation, oxidative stress, apoptosis, angiogenesis, and metabolic regulation. These findings provide insights into the potential application of HXZTS as a complementary or alternative therapeutic approach for managing OA and a foundation for developing novel targeted therapies.

bioinformatics↗

bioRxiv2025

Protein Crowders Remodel RNA Electrostatics, Hydration, and Dynamics: A Challenge to Steric Crowding Models

The intracellular environment is densely populated with macromolecules, creating crowded conditions. Whether in vitro environments or synthetic crowders like polyethylene glycol (PEG) accurately capture the complexity of RNA interactions in vivo remains unclear. Using extensive all-atom molecular dynamics simulations, we investigated the HIV-1 TAR RNA hairpin in dilute, PEG-crowded, and realistic protein-crowded solutions. We found that PEG primarily exerts excluded-volume effects, maintaining RNA hydration and Na+ ion condensation similar to dilute conditions. In contrast, protein crowders significantly altered RNA electrostatics, reducing Na+ condensation by nearly 60%, displacing surface hydration water, and forming chemically specific contacts dominated by positively charged residues, notably arginine and lysine. These interactions led to local RNA expansion and reshaped its conformational landscape without disrupting the global fold. Moreover, protein crowding dramatically slowed RNA translational and rotational dynamics, as well as local water and ion mobility, effects minimally observed with PEG. Our findings emphasize that crowder identity critically determines RNA behavior and challenge the use of PEG as a universal model for intracellular conditions, providing mechanistic predictions for RNA studies in biologically relevant environments.

biophysics↗

bioRxiv2025

Ultrasound-activated drug release with extracellular vesicles

Precise, noninvasive targeting and controlled drug release to the nervous system could transform both basic research and clinical therapy. In this work, we developed a focused ultrasound-responsive delivery system based on extracellular vesicles (EVs), which are naturally occurring and biocompatible phospholipid nanocarriers. To enable the ultrasound responsiveness, a lipid-gas phase transition material Perfluoropentane (PFP) was co-encapsulated with therapeutic agents into EVs via low-temperature sonication. The resulting EVs had a size of 100-200 nm and demonstrated efficient, on-demand release upon ultrasound stimulation. In primary cultured neurons, EVs loaded with lidocaine successfully suppressed calcium activity and showed minimum cytotoxicity. Finally, we demonstrated in vivo application of this system for modulation pain sensitivity in rats. Our EVs-drugs platform demonstrated a safe, and ultrasound-activated drug delivery with high spatiotemporal control, showing strong potential therapeutic applications.

bioengineering↗

bioRxiv2025

A machine-learning-guided hydrogen-bonded organic framework for long-term, ultrasound-triggered pain therapy

Effective treatment of chronic pain remains hindered by the lack of drug delivery systems that simultaneously achieve long-term stability, high spatial precision, and non-invasiveness1,2,3. Here, we utilize a programmable, ultrasound-responsive drug delivery platform based on hydrogen-bonded organic framework (HOF) nanoparticles, enabling on-demand anesthetic release with long-term and durable analgesic efficacy. A machine learning (ML)-guided screening pipeline was developed to evaluate about 250 FDA-approved drugs, spanning both hydrophilic and lipophilic agents, and identified bupivacaine (lipophilic) and lidocaine hydrochloride (hydrophilic) as optimal candidates. These agents were efficiently encapsulated into HOF nanoparticles via diffusion and double-solvent methods. Ultrasound-triggered drug release in vitro transiently suppressed calcium signaling in adeno-associated virus (AAV)-transfected neurons. In vivo, ultrasound-activated release of bupivacaine or lidocaine HCl at the sciatic nerve site significantly elevated mechanical nociceptive thresholds for up to seven days, reduced autotomy (self-mutilaion) behavior, and improved motor function in a rat model of chronic pain. Notably, the machine learning-identified top candidates not only exhibited high loading efficiency, but also demonstrated superior therapeutic outcomes in vivo, establishing a direct link between computational prediction and biological efficacy. This non-invasive, programmable HOF-based system provides a clinically translatable platform for on-demand, spatiotemporally precise pain management.

bioengineering↗