Biology subjects

Fang, Y.

Publications and source records attributed to Fang, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Iron availability regulates PIN-mediated auxin transport and distribution to modulate root gravitropic growth in Arabidopsis

Iron (Fe) is an essential micronutrient for plant growth, and the hormone auxin is a key regulator of developmental processes, including root gravitropism. Here, we investigated the molecular mechanisms underlying the crosstalk between iron nutrition and auxin-mediated root growth in Arabidopsis thaliana. Phenotypic analysis revealed that iron deficiency strongly shaped root system architecture and root gravitropism, and these phenotypes were exacerbated in the iron uptake mutant irt1-1. Genetic analysis revealed that iron deficiency did not aggravate the gravitropic defect of the pin2 mutant, eir1-4, suggesting that iron availability modulates root gravitropism through a PIN2-dependent pathway. Further transcriptomic analysis confirmed that iron deficiency significantly altered the expression of numerous genes related to the auxin pathway, providing molecular evidence for the observed physiological connection. Collectively, this study revealed that iron availability regulates root gravitropic growth by modulating PIN-mediated auxin transport and distribution, providing insights into how plants integrate nutritional cues with developmental programs. Graphical abstract A brief descriptionIron modulates auxin transport and root tip distribution by regulating PIN2 protein, thereby mediating root gravitropism in Arabidopsis. Public summaryO_LIIron nutrition specifically regulates root gravitropism and architecture in Arabidopsis. C_LIO_LIIron deficiency disrupts local auxin homeostasis in root tips and impairs asymmetric distribution in response to gravity. C_LIO_LIIron deficiency stress significantly reduces the abundance of PIN2 protein in root tip cells and disrupts its polar localization pattern on the plasma membrane, thereby precisely modulating polar auxin transport by interfering with the vesicle trafficking and recycling efficiency of PIN2. C_LIO_LIRNA-seq results showed that iron deficiency induced differential expression of multiple auxin-related genes, indicating that iron nutrition affects root development through the auxin pathway. C_LI

plant biology↗

bioRxiv2026

An Engineered Halotolerant Chimeric T7 RNA Polymerase for High-Yield, Low-Immunogenicity Synthesis of RNA via Simple Batch Transcription

The rapid advancement of mRNA therapeutics has imposed stringent requirements on both the quality and scalability of in vitro transcription (IVT) products. However, the accumulation of double-stranded RNA (dsRNA) byproducts and 3-terminal heterogeneity during T7 RNA polymerase (T7 RNAP)-mediated transcription can robustly trigger deleterious innate immune responses and compromise translation efficiency. Existing enzyme engineering strategies frequently struggle to reconcile the trade-offs between salt tolerance, volumetric productivity, and product purity. Here, we report a novel engineering strategy for halotolerant T7 RNAP by fusing optimized mutant polymerases with diverse DNA-binding domains (e.g., Sso7d, MC1). This approach orchestrated the development of a series of chimeric T7 RNAP mutants designed to bolster catalytic activity and template selectivity under high-salt conditions while concurrently suppressing RNA-dependent RNA polymerase (RdRP) activity. Our lead chimeric mutants exhibited exceptional salt tolerance and processivity in the presence of up to 270 mM NaCl. Notably, these mutants significantly diminished dsRNA formation to less than 0.001%, while markedly improving transcript integrity and 3 homogeneity, thereby facilitating superior translation efficiency for both linear mRNA and circular RNA (circRNA). Crucially, this heightened salt tolerance does not necessitate a trade-off in RNA yield, affording broader flexibility for downstream process optimization. In an enzymatic circRNA synthesis system, these mutants enabled a non-fed-batch configuration with high initial rNTP concentrations (15 mM each), resulting in a 50% increase in yield and achieving an unprecedented titer of 15 mg/mL. This research provides a robust enzymological solution that harmonizes quality and productivity for the industrial-scale manufacturing of high-concentration, low-immunogenicity RNA.

genomics↗

bioRxiv2026

Comparative single-cell transcriptomic roadmap of mammalian fetal ovarian development

Early ovarian development establishes the cellular basis of female reproduction, yet its cellular composition and developmental dynamics remain poorly characterized across mammalian species. Here, we generated a cross-species single-cell transcriptomic atlas of early female gonadal development in cattle (E38-E112), human (PCW6-16), and mouse (E11.5-E18.5), integrating 107,930 cells across comparable developmental windows, spanning sex determination and early ovarian differentiation. We identified 11 shared gonadal cell types across three species, including germ cells and granulosa cells, and uncovered a previously undescribed bovine-specific cell population with steroidogenic features, suggesting species differences in ovarian somatic lineage development. Epigenetic regulators exhibited dynamic activation in germ cells and granulosa cells. Developmental trajectory analysis revealed shared and species-specific genes associated with germ cell and granulosa cell development, including conserved dynamically expressed genes such as TFAP2C and ZCWPW1 in germ cells and FOS and JUNB in granulosa cells. Cross-species cell type classification using a machine learning support vector machine (SVM) model revealed transcriptionally conserved cell types, such as immune cells and germ cells, while granulosa cells showed substantial cross-species divergence, associated with extracellular matrix-related gene expression. Together, our study provides a comparative framework for understanding conserved and divergent mechanisms of early ovarian development across mammals.

developmental biology↗

bioRxiv2026

Extra-lineage tissue programs define the transcription states of human pancreatic cancer

Cancers acquire alternate transcriptional states as they evolve, but the origins, timing and determinants of this plasticity are poorly understood in many tumours. We investigated the transcriptional states of pancreatic cancer by integrating [~]1000 tumour-enriched genomes and transcriptomes from 464 patients combined with scRNA-seq, multiome profiling, and spatial proteomics. Four epithelial states covering the spectrum of lineage plasticity were identified (Classical-1, Classical-2, Basal-1, Basal-2). Comparing these states to normal and pan-cancer human single cell atlases showed each state reflects distinct tissue programs found in other malignancies. Single cell analysis uncovered that the main transcription state of this disease (Classical-1) emerges before KRAS mutations. Spatial proteomics from patients and cancer-free donors showed that the Classical-1 program emerges during acinar-to-ductal metaplasia, and also unexpectedly, in normal ducts without disrupting their morphology. Overall, these findings link the extensive lineage plasticity potential of this organ to the origins of the transcriptional states.

cancer biology↗

bioRxiv2026

Transcriptomic, Genomic, and Clinical Characterization of Morphological Classes in Localized and Metastatic Pancreatic Cancer

BackgroundHistomorphology is a strong prognostic biomarker correlated with basal-like and classical programs in surgically resected pancreatic ductal adenocarcinoma (PDAC). However, the spectrum of morphology and its biological associations remain poorly defined in advanced disease. ObjectivesWe explored the transcriptomic and genomic underpinnings and clinical relevance of morphological classes across localized and metastatic PDAC. DesignWe unified morphological classifications into four classes: glandular, cribriform, solid, and squamous. We integrated transcriptome and whole-genome sequencing following laser-capture microdissection with morphological classifications in 348 PDAC patients, where half of the cohort included locally advance and metastatic stages to uncover molecular associations. ResultsNon-glandular morphologies comprised three distinct classes that were enriched in metastatic disease. Transcriptomic profiling exhibited that glandular tumours predominantly expressed classical epithelial programs, although a subset displayed partial or full epithelial- mesenchymal transition signatures. In contrast, non-glandular morphologies showed basal-like transcriptional programs with subtype-specific pathways, including ciliogenesis in cribriform tumours, extracellular matrix remodelling and immune evasion in solid tumours, and keratinisation programs in squamous tumours. The solid class was significantly enriched in liver metastatic lesions and was associated with increased intra-tumoural morphological heterogeneity, whole-genome doubling, KRAS major allelic imbalance, and elevated KRAS-ERK signalling. ConclusionNon-glandular morphologies identify biologically distinct PDAC tumour states that are enriched in liver metastases and associated with subtype-specific transcriptional programs and KRAS-driven genomic alterations.

cancer biology↗

bioRxiv2026

Cost and benefits of gene amplification-mediated antibiotic resistance

Bacteria evolve antibiotic resistance through various mechanisms, including horizontal gene transfer, sequence-altering mutations, and tandem duplications/amplifications in genomic regions that increase the dosage of resistance determinants. This phenomenon, known as gene duplication-amplification (GDA), is a transient and reversible genetic mechanism that allows bacteria to rapidly adapt to antibiotic stress. Due to the unstable nature of amplification, the quantitative relationship between gene copy number, resistance levels, and the associated physiological costs remains poorly defined. Here, we constructed strains with fixed GDA copy numbers in a clinical Enterobacter cloacae strain. Using growth curve and time-kill assays, we show that ceftazidime (CAZ) resistance scales with GDA copy number, but the benefit under selection comes with a growth cost in the absence of antibiotic. Notably, we find that while GDA provides a survival advantage under CAZ pressure, it simultaneously increases susceptibility to rapid killing at supra-MIC concentrations. Our analysis further illustrates that survival is jointly shaped by gene dosage, antibiotic concentration, and exposure time. Together, these results clarify that GDA-mediated resistance is highly context dependent, shaped by trade-offs between resistance benefits and physiological costs.

microbiology↗

bioRxiv2026

MANF Clears Mutant Uromodulin in Human Kidney Organoids of Autosomal Dominant Tubulointerstitial Kidney Disease

Autosomal dominant tubulointerstitial kidney disease due to uromodulin mutations (ADTKD-UMOD) is one of the leading hereditary kidney diseases. Currently there is no targeted treatment. To illuminate human relevance of mesencephalic astrocyte-derived neurotrophic factor (MANF)-based therapy, we have established patient induced pluripotent stem cell (iPSC)-derived kidney organoid model carrying UMOD p.H177-R185del, the leading mutation causing ADTKD. We have discovered that MANF can directly bind and repress ER calcium release channel IP3R1, thus enhancing AMPK-induced autophagy in a TRIB3-dependent manner. The therapeutic implication of this finding may well be extended to other protein misfolding diseases.

genetics↗

bioRxiv2026

Geometric-aware and interpretable deep learning for single-cell batch correction via explicit disentanglement and optimal transport

Single-cell RNA sequencing enables high-resolution characterization of cellular heterogeneity, yet integrating datasets from diverse sources remains challenging due to batch effects. Current methods rely on implicit feature disentanglement and and lack geometric constraints, often result in under-correction, over-correction, or compromised biological fidelity. Here, we present iDLC, an interpretable deep learning framework that performs dual-level correction through explicit feature disentanglement and optimal transport-regularized adversarial alignment. iDLC separates biological and technical components within a structured latent space, then leverages high-confidence mutual nearest neighbor pairs to guide geometrically constrained distribution alignment. Systematic evaluation across pancreatic cancer datasets with varying batch effect intensities, multi-source human immune cells, and large-scale cross-species atlases demonstrates that iDLC robustly eliminates complex batch effects while preserving fine-grained cell subtypes, continuous developmental trajectories, and rare populations. The framework scales efficiently to datasets exceeding one million cells and consistently outperforms existing methods in both batch correction and biological conservation metrics. iDLC provides a principled and reliable tool for constructing unified single-cell reference atlases across diverse experimental conditions and biological systems.

bioinformatics↗

bioRxiv2026

Single-nucleus RNA sequencing reveals cell type-specific responses to heat stress in bovine mammary gland

BackgroundHeat stress (HS) poses a major challenge to the dairy industry by reducing milk production, yet its cell type-specific effects in the bovine mammary gland remain incompletely defined. In this study, we recorded production traits and collected mammary biopsies from cows under thermoneutral (TN), HS, and pair-fed (PF) conditions. ResultsClinical measurements confirmed HS-induced physiological alterations. Compared with TN cows, HS cows exhibited reduced dry matter intake (DMI), milk yield, and yields of fat, protein, and lactose, along with increased water intake and milk urea nitrogen. The use of PF controls indicated that decreased DMI accounted for 45% of the milk-yield reduction, whereas direct HS effects accounted for the remaining reduction. We applied single-nucleus RNA-seq (snRNA-seq) on mammary biopsies to generate cell-resolved HS responses. We identified 14 distinct cell clusters, including epithelial, immune, and stromal populations. Under the TN condition, casein genes (e.g., CSN1S1, CSN2) were broadly expressed across luminal cells but were attenuated under HS, whereas luminal alveolar cells showed relative upregulation. Heat shock protein genes were strongly induced by HS, primarily in epithelial clusters. Gene-set enrichment analyses revealed increased ribosomal activities across HS-responsive clusters and enrichment of protein folding and metabolic pathways in luminal alveolar cells, suggesting elevated proteostasis demands under stress. Pseudotime analysis positioned luminal cells along a progenitor-to-secretory trajectory under TN, accompanied by increased casein gene expression, whereas under HS, mature luminal cells shifted toward a homeostasis regulatory state. Cell-cell communication analysis demonstrated HS-induced remodeling of interepithelial signaling, including altered ERBB4-mediated signaling from luminal hormone-sensing to alveolar lineages. Finally, transcription factor activity profiling highlighted cell type-specific HS-activated regulators and their downstream target genes. ConclusionsTogether, this cell type-resolved atlas delineates how HS alters bovine mammary epithelial function, developmental state, and intercellular crosstalk. These findings point to proteostasis pressure, disrupted signaling pathways, and rewired regulatory networks as mechanistic contributors to reduced lactational performance under HS, offering insights for improving heat resilience in dairy cattle.

genomics↗

bioRxiv2026

PlantMDCS: A code-free, modular toolkit for rapid deployment of plant multi-omics databases

With the rapid accumulation of diverse omics datasets, achieving efficient management and integrative analysis of plant multi-omics data remains a major challenge. Conventional solutions rely on constructing web-based databases, which often demand substantial programming expertise and long-term financial support. To address these limitations, we developed the Plant Multi-omics Database Construction System (PlantMDCS)-a locally deployable, user-friendly, and collaborative platform that unifies database construction and downstream multi-omics analysis within a graphical environment. PlantMDCS adopts a decoupled front-end/back-end architecture. The back end serves as the core engine for data management and computation, and is responsible for the storage, preprocessing, integration, and hierarchical association of multi-omics data. Once initialized, the front end supports the complete research workflow, including data import, querying, integrative analysis and visualization. All operations can be performed without programming, while local resource usage is dominated by disk storage required for user-provided datasets rather than sustained computational overhead. Benchmarking across plant species ranging from Arabidopsis to hexaploid wheat demonstrated that database construction can be completed within minutes, independent of genome size or data complexity. PlantMDCS is designed for local deployment to ensure data security, while allowing multi-user collaboration within local networks and supporting controlled remote access for teams distributed across different regions. Overall, PlantMDCS offers a secure and sustainable framework that integrates data management and analysis within a unified system. This design shifts multi-omics research away from fragmented file-based processing toward persistent, database-driven exploration, thereby enhancing analytical efficiency and reproducibility.

bioinformatics↗

bioRxiv2026

Rapid diversification of a natural Heterosigma akashiwo virus population during a host bloom

Despite the ecological importance of viruses, our understanding of their evolutionary dynamics in natural environments remains limited. This gap is particularly pronounced for giant dsDNA viruses of the phyla Nucleocytoviricota and Mirusviricota. Most knowledge on their population genetic dynamics is derived from a small number of laboratory-based experiments, whereas patterns in nature are rarely observed. To overcome this limitation, we traced genetic structure and transcription status of Heterosigma akashiwo virus (HaV) using high-frequency, time-resolved sampling during a host bloom in a coastal area of Japan, by integrating cell counting, metabarcoding, metagenomic and metatranscriptomic sequencing. Our study revealed that HaV dominated the giant virus community in most samples, with the relative abundances of up to 56%. Despite the high abundances, the HaV population exhibited a relatively low level of microdiversity but with a high pN/pS ratio compared to other giant viruses in the study site. Microdiversity increased during the early sampling period, reached a maximum at mid-sampling, and decreased during the later period, consistent with rapid diversification during viral expansion, possibly driven by both in situ mutations and the succession of pre-existing minor variants. Several accessory genes, including a glycosyltransferase and an endonuclease, were highly expressed, providing functional evidence consistent with host interaction-driven selective pressure during the bloom. Together, these results indicate that HaV population dynamics during algal blooms are shaped by host-driven selection acting on standing genetic variation.

ecology↗

bioRxiv2026

Transcriptomics-based modeling of methionine metabolism effectively estimates sample-wise DNA methylation activity and epigenetic aging

DNA methylation is a central epigenetic modification that regulates gene expression, maintains genomic stability, and guides cellular differentiation. However, direct measurements of DNA methylation, such as whole-genome bisulfite sequencing or DNA methylation arrays, are costly and require substantial DNA input, limiting their scalability for large cohorts and their applicability to emerging modalities such as single-cell and spatially resolved transcriptomics. In this study, motivated by the fact that DNA methylation is fundamentally a metabolic process, we investigate whether sample-wise DNA methylation activity can be inferred directly from transcriptomic profiles of genes involved in methionine and one-carbon metabolism. We show that a compact metabolic model comprising seven core reaction steps and 98 genes accurately predicts total DNA methylation activity across matched transcriptomic and methylation datasets from CCLE, TCGA, GTEx, and an independent single-cell multi-omics data set. Building on this framework, we develop Total DNA Methylation Activity (TDMA), a physics-informed neural network-based score that enables robust estimation of DNA methylation activity from bulk, single-cell, and spatial transcriptomics data. We demonstrate that TDMA captures methylation-dependent transcriptional regulation and identifies genes and pathways under epigenetic control. Applying TDMA to GTEx, we further reveal strong associations between the predicted total methylation activity, chronological aging, and established epigenetic clocks. We also demonstrated that TDMA can serve as a transcriptomics-derived epigenetic clock and highlights age-dependent roles of folate and glutathione metabolism in epigenetic aging. Applying TDMA to single cell and spatial transcriptomics data collected from pancreatic adenocarcinoma (PDAC), we identified that methionine metabolism and DNA methylation regulates T cell cytotoxicity in the tumor microenvironment of PDAC. Together, this work establishes a scalable, modality-agnostic framework for estimating DNA methylation activity from transcriptomics and provides new insights into the metabolic regulation of epigenetic aging.

bioinformatics↗

bioRxiv2026

Carbon dioxide sequestration into biomineral armor by ants

Over geologic time, Earths climate has been shaped by the capture and conversion of atmospheric carbon dioxide (CO2) into stable carbonate minerals, including dolomite [CaMg(CO3)2]. Accelerating natural carbon mineralization offers significant potential for mitigating anthropogenic climate change. Using stable carbon isotope tracking, nano-scale secondary ion mass spectroscopy, and 13C SSNMR, we show that, paralleling global biosphere-level processes, Sericomyrmex amabilis fungus-farming ants rapidly convert CO2 in their nest chambers into a biomineral layer covering their exoskeletons. We further reveal that biogenic carbon mineralization by these ants produces partially ordered dolomite. This rapid sequestration of CO2 into defensive armor in ants provides a fascinating natural example of mediation of potentially toxic accumulation of atmospheric CO2 that could inform human efforts to mitigate climate change.

ecology↗

bioRxiv2026

Medication and Developmental Stage Shape the Brain-Age Gap in ADHD

Identifying robust biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) remains challenging. The brain-age gap (BAG), which is the difference between predicted biological brain age and chronological age, has been proposed as a marker of atypical neurodevelopment, yet findings have been inconsistent across studies, limiting its clinical translation. We hypothesized that two major sources of heterogeneity, medication status and developmental stage, contribute to these discrepancies. To test this, we analyzed structural MRI data from a large multi-site cohort (N = 947; ages 7-26 years). Individuals with ADHD were stratified by medication history (medicated vs. unmedicated) and developmental stage (childhood vs. adolescence) and compared with matched typically developing controls. We estimated global- and network-level BAG using publicly available pretrained models. Our results revealed that BAG differences were contingent on medication status, with abnormalities predominantly observed in unmedicated individuals. Developmental stage further moderated the presence of this effect: BAG abnormalities were present significantly in children with ADHD but not in adolescents. Network-level analyses demonstrated spatial specificity, with significant effects in visual, ventral attention, and dorsal attention networks. Together, these findings provide compelling evidence that BAG in ADHD is both medication- and development-dependent, highlighting the need to account for treatment exposure and developmental stage when evaluating BAG as a biomarker and further underscoring the importance of early intervention during childhood.

neuroscience↗

bioRxiv2026

Site-specific integration of transposon via engineered piggyBac transposase

The precise integration of large DNA fragments into the human genome holds significant therapeutic potential. Here, we demonstrate that combining engineered piggyBac (PB) transposase with CRISPR/Cas9 enables targeted integration of PB transposons into specified genomic loci. Our engineered PB transposase (PBase) retains high excision activity while substantially reducing endogenous integration activity. In the developed Cas9-PBase fusion system, PBase excises the transposon to generate linear DNA fragments, while Cas9 introduces site-specific double-strand breaks (DSBs), facilitating insertion of the excised fragment at the target locus. The optimized tool achieves 6.1-7.3 kb transposon integration at multiple genomic sites with 10-15% efficiency, demonstrating 60-80% targeted integration specificity. As a proof of concept, we inserted a 7.1 kb transposon encoding three genes into the {beta}2M locus of human induced pluripotent stem cells (iPSCs), conferring protection against allogeneic natural killer (NK) cell-mediated cytotoxicity in derived iNK cells. These results establish Cas9-PBase as a precise and programmable platform for large DNA sequence insertion with potential clinical applications.

genetics↗

bioRxiv2025

Marine biotoxin depuration rates: management applications, research priorities, and predictions for unstudied species

Monitoring and managing the public health risk posed by marine biotoxins is a daunting challenge. With expansive coastlines, 1000s of seafood species, and dozens of biotoxins, monitoring cannot occur everywhere at once. Improving the cost-effectiveness of biotoxin monitoring is thus critical to expanding coverage to include more species, toxins, and locations. Notably, understanding the rate at which seafood species depurate biotoxins can be used to optimize the cadence of monitoring. We conducted a systematic review to collate marine biotoxin depuration rates and synthesize the factors that influence them; identify knowledge gaps, best practices, and research priorities; and generate predictions of depuration rates for unstudied species. We found that only 85 marine species have been studied for their biotoxin depuration rates. Depuration rates for non-bivalves and for toxins besides paralytic shellfish toxins (PSTs) are especially understudied. Depuration half-lives varied from 0.03 to 1269 days based on species, toxin, tissue, and environmental conditions. In general, depuration accelerates with increased temperature and food availability, with implications for aquaculture siting, depuration enhancement, and biotoxin monitoring. We identified unstudied bivalve and finfish species that are highly produced and vulnerable to HABs that are high priorities for future research. Finally, we used a Bayesian regression model to predict PST depuration rates for 102 unstudied bivalve species, the only clade-syndrome with sufficient training data. These predictions can guide efficient monitoring and management until lab- or field-based depuration rates become available. We recommend that future studies directly estimate depuration rates to ensure their comparability across studies and utility to managers.

ecology↗

bioRxiv2025

The subclonal footprint of pervasive early dissemination in pancreatic cancer

Early is too late describes a central problem in pancreatic cancer referring to its relentless drive to disseminate and highlights the need to understand how this disease spreads so rapidly. In this study, we profiled 1,013 samples from 277 donors, including tissue whole genome and RNA sequencing combined with plasma whole genome sequencing at [~]25x. Strikingly, local primary tumours, including some reaching 7cm, were found to shed little to no circulating tumour DNA (ctDNA). Instead, metastatic burden in the liver but not extrahepatic sites, was a main physiologic determinant of ctDNA levels. Whole-genome duplication (WGD), high cell cycle activity, and non-glandular differentiation emerged as tumour-intrinsic features related to increased ctDNA shedding. By contrast, decreased shedding was related to extrinsic features including a reactive microenvironment and unexpectedly, humoral immunity. Analysis of tumour clonal architecture showed that in patients with low ctDNA levels, the signal disproportionately originated from subclones and this signal persisted even when the primary tumour was removed. Disseminated subclones were a significant source of ctDNA in early-stage patients. Longitudinal analysis of patients revealed that subclones seeded metastases and shed ctDNA in the blood years before detection. This first report of paired tissue and plasma whole genomes in pancreatic cancer is a unique resource and has broad implications for disease surveillance, treatment monitoring, and early detection in this disease.

cancer biology↗

bioRxiv2025

Composite biomaterials of polyelectrolyte complex micelle nanoparticles in hyaluronic acid gels enable local, targeted miR-92a inhibition and enhanced angiogenesis in diabetic wound repair

Diabetic wounds are characterized by various cellular deficiencies, particularly insufficient angiogenesis. MicroRNA 92a (miR-92a) is a known factor in diabetic wounds that perpetuates non-healing wound phenotypes by inhibiting angiogenesis. Therefore, its local inhibition at wound sites has therapeutic potential. To achieve this, we combine a nanoparticle formulation of polyelectrolyte complex micelles (PCMs) delivering miR-92a inhibitors with a hyaluronic acid (HA) gel formulation suitable for topical application to wound sites. The nanoparticles, formed by polyelectrolyte complexation of poly(ethylene glycol)-block-poly(L-lysine) with RNA cargo, are functionalized with targeting peptides against vascular cell adhesion molecule 1 (VCAM-1) to improve affinity for inflamed endothelial cells. We demonstrate effective PCM encapsulation and controlled release from gel formulations in vitro and in vivo. These PCMs are taken up in vivo by endothelial cells and exert functional transcriptional effects on miR-92a and its downstream targets. Furthermore, our composite PCM-gel formulation significantly accelerates wound closure in diabetic mouse models and improves angiogenesis, consistent with the known role of miR-92a inhibition in vascular regeneration. This work demonstrates a highly translatable formulation for improved wound healing, and lays the framework for modular nanoparticle-gel systems that can achieve local, cell-targeted RNA delivery. HighlightsPolyelectrolyte complex micelles (PCMs) can be combined with hyaluronic acid gels. VCAM-1 targeted PCMs released from gels are taken up by endothelial cells. PCM-gels deliver miR-92a inhibitors to modulate downstream gene expression in vivo. PCM-gels accelerate wound healing and enhance angiogenesis in diabetic mice.

bioengineering↗