Biology subjects

Tucker, N.

Publications and source records attributed to Tucker, N..

5 recordsLinked to original sources

bioRxiv2026

Lung-Targeting Interleukin-10 mRNA Lipid Nanoparticles Ameliorate Acute Lung Injury

Acute respiratory distress syndrome (ARDS) is the most severe manifestation of acute lung injury (ALI), characterized by diffuse pulmonary inflammation, impaired gas exchange, and high morbidity and mortality. Despite its clinical significance, no specific or effective pharmacological therapies are currently available for its treatment. In this study, we developed a lung -targeted mRNA-sulfonium lipid nanoparticle (mRNA/sLNP) delivery system for the treatment of ALI in a mouse model. We first optimized sulfonium lipid structures, and the optimized sLNP was comprehensively characterized and subsequently loaded with interleukin-10 (IL-10) mRNA. In a lipopolysaccharide (LPS)-induced ALI mousemodel, IL-10/sLNPdemonstrated both prophylactic and therapeutic efficacy, significantly attenuating pulmonary and systemic inflammation, restoring barrier integrity, and reducing tissue injury.

bioengineering↗

bioRxiv2025

Size-Modulated Mesoderm-Endoderm Divergence and Myocardial Cavitation in Micropatterned Cardioids

The human heart, originating from the splanchnic mesoderm, is the first functional organ to develop, co-evolving with the foregut endoderm through reciprocal signaling. Previously, cardioid models offered new insights on cardiovascular cell lineages and tissue morphogenesis during heart development, while mesoderm-endoderm crosstalk remain incompletely understood. Here, we integrated micropatterned cardioids, CRISPR-engineered reporter hiPSCs, deep-tissue imaging, and single-cell RNA sequencing (scRNA-seq) to explore synergistic mesoderm-endoderm co-development. scRNA-seq with PHATE trajectory mapping reconstructed lineage bifurcations of mesoderm-heart and endoderm-foregut lineages, identifying key cell types in cardiac and hepatic development. Ligand-receptor interaction analysis highlighted mesodermal cells enriched in non-canonical WNT, NRG, and TGF-{beta} signaling, while endodermal cells exhibited VEGF and Hedgehog activity. We found that micropattern sizes influenced cellular composition, cardioid cavitation, contractile functions, and mesoderm-endoderm signaling crosstalk. The cardioids generated from 600 {micro}m diameter circle patterns showed larger cavity formation resembling early heart chamber formation. Our findings establish micropatterned cardioids as a model for mesoderm-endoderm co-development, enhancing our understanding of heart-foregut synergy during early embryogenesis.

bioengineering↗

bioRxiv2025

TARRAGON: Therapeutic Target Applicability Ranking and Retrieval-Augmented Generation Over Networks

The identification of therapeutic protein targets is fundamental to the success of drug development and repurposing. Traditional approaches for target selection require extensive preclinical evaluation for toxicity and efficacy, making the process time-intensive and resource-heavy. Computational tools that efficiently prioritize and validate novel targets are needed to streamline drug discovery workflows. To address this gap, we developed TARRAGON: Therapeutic Target Applicability Ranking and Retrieval-Augmented Generation Over Networks, a computational framework that integrates data mining and machine learning to identify, rank, and assess target-disease relationships to nominate new therapeutic targets. TARRAGON mines knowledge graphs to uncover meta-paths, or rules of graph traversal, linking potential therapeutic targets to diseases. It employs a classification model to rank target-disease hypotheses based on evidence patterns and utilizes a retrieval-augmented generation workflow to prompt a large language model for generating feasibility reports on prioritized targets. Using TARRAGON, we prioritized potential drug targets for non-muscle invasive urinary bladder cancer. Top-ranked candidates were validated using CRISPR gene effect and expression data from the Broad Institute DepMap portal. We further proposed chemical modulators for these targets to inform combination drug screening alongside approved bladder cancer therapeutics. TARRAGON introduces a novel, interpretable computational pipeline for therapeutic target discovery and pharmaceutical candidate nomination, offering the potential to accelerate drug development across diverse disease areas.

bioinformatics↗

bioRxiv2023

Bovine blood and milk T-cell subsets in distinct states of activation and differentiation during subclinical Staphylococcus aureus mastitis

T-lymphocytes are key mediators of adaptive cellular immunity and knowledge about distinct subsets of these cells in healthy and infected mammary gland secretions remains limited. In this study, we used a multiplex cytometry panel to show that staphylococcal mastitis causes the activation of CD4+, CD8+ and {gamma}{delta} T-cells found in bovine milk. We also highlight remarkable differences in the proportions of naive and memory T-cells subsets found in blood and milk. These observations will contribute to a better understanding of cell-mediated immune mechanisms in the udder and to the development of new therapeutic and preventive strategies targeting mastitis.

immunology↗

bioRxiv2019

Detailed Regulatory Interaction Map of the Human Heart Facilitates Gene Discovery for Cardiovascular Disease

Most disease-associated variants identified by population based genetic studies are non-coding, which compromises finding causative genes and mechanisms. Presumably they interact through looping with nearby genes to modulate transcription. Hi-C provides the most complete and unbiased method for genome-wide identification of potential regulatory interactions, but finding chromatin loops in Hi-C data remains difficult and tissue specific data are limited. We have generated Hi-C data from primary cardiac tissue and developed a method, peakHiC, for sensitive and quantitative loop calling to uncover the human heart regulatory interactome. We identify complex CTCF-dependent and -independent contact networks, with loops between coding and non-coding gene promoters, shared enhancers and repressive sites. Across the genome, enhancer interaction strength correlates with gene transcriptional output and loop dynamics follows CTCF, cohesin and H3K27Ac occupancy levels. Finally, we demonstrate that intersection of the human heart regulatory interactome with cardiovascular disease variants facilitates prioritizing disease-causative genes.

genomics↗