Biology subjects

Hong, A.

Publications and source records attributed to Hong, A..

14 recordsLinked to original sources

bioRxiv2026

An oncolytic adenovirus armed with anticancer prodrug-activating enzyme offers enhanced tumor killing and antitumor immunity.

Oncolytic viruses are most commonly administered via intratumoral injection; however, their clinical efficacy in achieving tumor eradication remains limited by several challenges, including insufficient penetration into all tumor cells and the inability to elicit robust systemic antitumor immune responses capable of eliminating metastatic microtumors. Here, we report an oncolytic adenovirus, OAd-2B6, with an engineered adenoviral E1 region for tumor selectivity and carrying the prodrug- activating enzyme cytochrome P450 2B6 (CYP2B6) to activate the anticancer prodrug cyclophosphamide (Cytoxan, CTX). OAd-2B6 alone induced dose-dependent tumor cell killing across multiple human tumor cell lines and exhibited strong synergistic antitumor effects when combined with CTX. Importantly, OAd-2B6-mediated local activation of CTX resulted in a potent bystander killing effect that eliminated tumor cells not directly infected by the virus. In a H1299 lung cancer xenograft nude mouse model, intratumoral injection of OAd-2B6 combined with CTX significantly inhibited tumor growth and even achieved complete tumor regression, with markedly superior efficacy compared with monotherapy. In immunocompetent mice bearing 4T1 breast cancer xenografts, OAd-2B6 alone inhibited tumor growth and was accompanied by upregulation of IFN-{gamma} and GzmB expression in the tumor-infiltrated T cells. CTX combination therapy further enhances this anti-tumor immune response, promoting the activation of T cells to suppress non-injected tumors at a distal site. Collectively, this study demonstrates that OAd-2B6 exerts potent antitumor effects through multiple mechanisms, including direct oncolysis, intratumoral prodrug activation leading to bystander killing, and enhancement of systemic antitumor immunity. These findings provide a promising strategy for improving the therapeutic efficacy of oncolytic therapy.

cancer biology↗

bioRxiv2026

Combining xenium in situ spatial transcriptomics and imaging mass cytometry on a single tissue section

Spatial imaging technologies provide an expansive view of tissue microenvironments through high-plex profiling of protein and molecular targets in situ. Imaging mass cytometry (IMC; Standard BioTools) is a trusted method for defining immune phenotypes based on up to 40 protein targets, whilst Xenium in situ spatial transcriptomics (Xenium; 10x Genomics) is an emerging platform that can measure up to 5000 mRNA markers simultaneously. Although these platforms can reveal valuable insights on their own, there is an increasing need to analyse samples using a multi-omics approach to further our understanding of complex biological processes. To address this, we have assessed a novel dual-platform workflow that combines Xenium and IMC on a single formalin-fixed paraffin-embedded tissue section to enable the spatial profiling of both mRNA and protein targets at single-cell resolution. The feasibility of the workflow was determined by comparing the staining quality of IMC performed after Xenium to that of IMC performed alone on an adjacent tissue section, confirming that Xenium has little to no negative impact on subsequent IMC protein staining. Although the location of transcripts picked up by Xenium correlated with the corresponding proteins picked up by IMC at a global scale, discrepancies between the two technologies were apparent at the single-cell level. This is to be expected, as biologically transcript expression does not always correlate with protein, and both platforms have their own technical limitations. However, when we analyse T cells identified by both technologies, as opposed to T cells identified by Xenium or IMC alone, it produces the most biologically meaningful results at both the transcript and protein level for specific T cell markers. These results highlight how integration of the two platforms, identifying the presence of both RNA and protein, can foster a more comprehensive view of cellular landscapes and provide a greater depth of functional capabilities and cellular interactions.

immunology↗

bioRxiv2026

KCNH1 variants associated with neurodevelopmental disorders exhibit prominent gain-of-function

Pathogenic variants in KCNH1, encoding the human ether-a-go-go voltage-gated potassium channel (EAG1, KV10.1), are associated with the neurodevelopmental disorders Temple-Baraitser syndrome (TBS), Zimmermann-Laband syndrome (ZLS), and epileptic encephalopathy. Investigating the functional consequences of KCNH1 variants can provide information about molecular and cellular pathophysiological mechanisms, and help guide therapeutic directions. In this study, we determined the functional properties of 26 disease-associated KCNH1 variants including three recurrent and five that were previously unpublished. Findings were compared to the wildtype (WT) channel along with six rare population variants. Our approach used automated patch clamp recording of heterologously expressed KCNH1 variants in both the homozygous state (variant alone) and the clinically-relevant heterozygous state (variant co-expressed with WT channels). We also examined the impact of alternative splice isoforms on functional consequences of specific variants. We demonstrated that the majority of disease-associated KCNH1 variants exhibit features consistent with gain-of-function including hyperpolarized voltage-dependence of activation, accelerated activation kinetics, or both that promote hyperpolarization of the resting membrane potential. By contrast, one unique variant discovered previously in an autism cohort had a depolarized voltage-dependence of activation and was associated with a depolarized resting potential in cells. Pharmacological testing of KCNH1 variants demonstrated differences in potency for channel block by imipramine and an investigational non-selective potassium channel blocker (LY97241) for specific variants. Collectively, our findings support gain-of-function as the most common, albeit not exclusive, molecular mechanism underlying KCNH1-related disorders and suggest opportunities for potential therapeutic drug repurposing strategies for these conditions.

neuroscience↗

bioRxiv2025

Gabija restricts phages that antagonize a conserved host DNA repair complex

Anti-bacteriophage systems like restriction-modification and CRISPR-Cas have DNA substrate specificity mechanisms that enable identification of invaders. How Gabija, a highly prevalent nuclease-helicase anti-phage system, executes self-vs. non-self-discrimination remains unknown. Here, we propose that phage-encoded DNA end-binding proteins that antagonize host RecBCD sensitize phages to Gabija. When targeting a temperate Lambda-like phage in Pseudomonas aeruginosa, Gabija protects the cell by preventing phage genome circularization and subsequent replication. Phage and plasmid sensitivity to Gabija is licensed by DNA end-binding complexes such as a phage exonuclease together with a ssDNA-annealing protein or GamMu dimers, which prevent loading of host repair complex RecBCD. Escape phages lacking these end-binding proteins become protected from Gabija by RecBCD translocation activities. RecBCD activity on the bacterial genome also prevents Gabija from targeting self-DNA. Therefore, we propose that Gabija antagonizes circularization of linear DNA devoid of RecBCD as a mechanism to identify foreign invaders.

microbiology↗

bioRxiv2025

Expanding the Bacteroides synthetic biology toolkit to develop an in vivo intestinal malabsorption biosensor.

The human gut is a highly dynamic physical environment where perturbations--including factors such as acidification, oxygenation, and particle concentration (osmolality)--can influence microbiota composition and contribute to disease states. Understanding gut environmental changes is essential for advancing diagnostic and therapeutic strategies for gut health. However, non-invasive methods for continuous monitoring remain limited. The bacterial gut microbiota represents a powerful platform for continuous, non-invasive biosensing technologies for the gut environment, with genetically tractable commensal species like Bacteroides thetaiotaomicron (B. theta) emerging as promising hosts for engineered biosensors. However, the availability of genetic tools for precise, modular environmental sensing and reporting control in B. theta remains limited. Here, we present an expanded genetic engineering toolkit for B. theta that enables precise, fluorescence-based environmental sensing of the gut environment. This toolkit includes i) three libraries of orthogonally inducible promoters capable of driving fluorescence expression, ii) a DNA-based system to tune repressor activity in B. theta, iii) a resulting modular transcriptional reporter circuit that integrates native promoter activation with fluorescent outputs, and iv) characterization of a novel plasmid integration mode in B. theta. To demonstrate its utility, we engineered biosensors for gut malabsorption, a condition characterized by increased luminal osmolality. Using identified osmolality-responsive native promoters from B. theta, we made biosensors capable of detecting changes in gut physiology through graded fluorescent outputs. These biosensors were validated both in vitro and in vivo using a murine model of laxative-induced malabsorption, where they enabled continuous, long-term, non-invasive monitoring of single-cell response from fecal samples with sensitivity to subclinical malabsorption levels. By expanding the genetic toolkit for Bacteroides and demonstrating its use in a physiologically relevant context, this approach highlights the potential of engineered gut bacteria as a monitoring platform for diverse gut health applications. This work advances strategies for microbial biosensing and positions gut commensals as key players in next-generation diagnostic methods.

synthetic biology↗

bioRxiv2025

The Adhesion GPCR ADGRL2 engages Gα13 to Enable Epidermal Differentiation

Homeostasis relies on signaling networks controlled by cell membrane receptors. Although G-protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors, their specific roles in the epidermis are not fully understood. Dual CRISPR-Flow and single cell Perturb-seq knockout screens of all epidermal GPCRs were thus performed, uncovering an essential requirement for adhesion GPCR ADGRL2 (latrophilin 2) in epidermal differentiation. Among potential downstream guanine nucleotide-binding G proteins, ADGRL2 selectively activated G13. Perturb-seq of epidermal G proteins and follow-up tissue knockouts verified that G13 is also required for epidermal differentiation. A cryo-electron microscopy (cryo-EM) structure in lipid nanodiscs showed that ADGRL2 engages with G13 at multiple interfaces, including via a novel interaction between ADGRL2 intracellular loop 3 (ICL3) and a G13-specific QQQ glutamine triplet sequence in its GTPase domain. In situ gene mutation of this interface sequence impaired epidermal differentiation, highlighting an essential new role for an ADGRL2-G13 axis in epidermal differentiation.

cell biology↗

bioRxiv2024

A sequence- and structure-based characterization of microbial enzymes identifies P. stutzeri as a plastic-degrading species

Plastic waste has accumulated rapidly in the past century and is now found throughout every ecosystem on Earth. Its ubiquitous presence means that plastic is routinely ingested by countless organisms, with potential negative consequences for organismal health. New solutions are urgently needed to combat plastic pollution. Among the many strategies required to curb the plastic pollution crisis, the bioremediation of plastic via enzymatic activity of microbial species represents a promising approach. Diverse microbes harbor enzymes capable of degrading plastic polymers and utilizing the polymers as a carbon source. Herein, we characterize the landscape of microbial protein-coding sequences with potential plastic degrading capability. Using the two enzyme systems of PETase and MHETase as a guide, we combined sequence motif analysis, phylogenetic inference, and machine learning-guided 3D protein structure prediction to pinpoint potential plastic-degrading enzymes. Our analysis platform identified hundreds of enzymes from diverse microbial taxa with similarity to known PETases, and far fewer enzymes with similarity to known MHETases. Phylogenetic reconstruction revealed that the plastic degrading enzymes formed distinct clades from the sequences of ancestral enzymes. Among the potential candidate sequences, we pinpointed both a PETase-like and MHETase-like enzyme within the bacterium Pseudomonas stutzeri. Using plate clearing assays, we demonstrated that P. stutzeri is capable of degrading both polyurethane (Impranil(R)) and polycaprolactone (PCL). Pseudomonas stutzeri also grew on carbon-free agar supplemented with polystyrene, suggesting this organism can utilize synthetic polymers as a carbon source. Overall, our integrated bioinformatics and experimental approach provides a rapid and low-cost solution to identify and test novel polymer-degrading enzymes for use in the development of plastic bioremediation technologies.

microbiology↗

bioRxiv2023

ONeSAMP 3.0: Effective Population Size via SNP Data for One Population Sample

O_LIThe genetic effective size (Ne) is arguably one of the most important characteristics of a population as it impacts the rate of loss of genetic diversity. Genetic estimators of (Ne) increasingly popular tools in population and conservation genetic studies. Yet there are very few methods that can estimate the Ne from data from a single population and without extensive information about the genetics of the population, such as a linkage map, or a reference genome of the species of interest. C_LIO_LIWe present ONeSAMP 3.0, an algorithm for estimating Ne from single nucleotide polymorphism (SNP) data collected from a single population sample using Approximate Bayesian Computation and local linear regression. C_LIO_LIWe demonstrate the utility of this approach using simulated Wright-Fisher populations, and empirical data from five endangered Channel Island fox (Urocyon littoralis) populations to evaluate the performance of ONeSAMP 3.0 compared to a commonly used Ne estimator. Our results show that ONeSAMP 3.0 is robust to the number of individual samples and number of loci included in and appears accurate even if the range of true Ne values is large. C_LIO_LIThis method is broadly applicable to natural populations and is flexible enough that future versions could easily include summary statistics appropriate for a suite of biological and sampling conditions. ONeSAMP 3.0 is publicly available under the GNU license at https://github.com/AaronHong1024/ONeSAMP_3 and also available with Bioconda (https://bioconda.github.io/index.html). C_LI

bioinformatics↗

bioRxiv2023

Transcriptional profiling of skin cancer NK cells reveals the elevated glucocorticoid signaling switches their anti-tumor characteristics to a homeostatic feature

Natural killer (NK) cells are potent mediators of anti-tumor immunity, yet their functions are frequently subverted by tumor microenvironment-driven immunosuppression. Here, we dissect the molecular mechanisms underlying NK cell dysfunction in cutaneous malignancies and identify a paradoxical cytokine shift in tumor-associated NK cells-reduced production of IFN-{gamma} and TNF- alongside elevated amphiregulin (AREG), an EGFR ligand linked to tumor progression. Single-cell transcriptomic analysis indicates that this reprogramming correlates with elevated glucocorticoid receptor (GR/NR3C1) pathway activity in tumor-infiltrating NK cells. Functional validation demonstrated that glucocorticoids specifically induce AREG production in NK cells, with tumor-associated prostaglandin E2 (PGE2) augmenting this response. Genetic ablation or pharmacological inhibition of NR3C1 abolished glucocorticoid-driven AREG induction. Moreover, primary GR activation established persistent chromatin accessibility at the AREG locus, sensitizing NK cells to enhanced AREG production upon secondary glucocorticoid exposure. Functionally, AREG counteracts NK cell-mediated tumor apoptosis, while adoptive transfer of AREG-deficient human NK cells significantly suppressed melanoma, cutaneous squamous cell carcinoma (cSCC), and hepatocellular carcinoma growth in NCG mice. These findings establish the GR-AREG axis as a multi-layered therapeutic target for restoring NK cell anti-tumor function. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/557530v3_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1ef982forg.highwire.dtl.DTLVardef@f036a7org.highwire.dtl.DTLVardef@941abborg.highwire.dtl.DTLVardef@1670d23_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2023

Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet

Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimers disease cases and 149 controls.

genomics↗

bioRxiv2021

Contribution of linear and nonlinear mechanisms to predictive motion estimation

Successful behavior relies on the ability to use information obtained from past experience to predict what is likely to occur in the future. A salient example of predictive encoding comes from the vertebrate retina, where neural circuits encode information that can be used to estimate the trajectory of a moving object. Predictive computations should be a general property of sensory systems, but the features needed to identify these computations across neural systems are not well understood. Here, we identify several properties of predictive computations in the primate retina that likely generalize across sensory systems. These features include calculating the derivative of incoming signals, sparse signal integration, and delayed response suppression. These findings provide a deeper understanding of how the brain carries out predictive computations and identify features that can be used to recognize these computations throughout the brain.

neuroscience↗

bioRxiv2020

Predictive encoding of motion begins in the primate retina

Survival in the natural environment often relies on an animals ability to quickly and accurately predict the trajectories of moving objects. Motion prediction is primarily understood in the context of translational motion, but the environment contains other types of behaviorally salient motion, such as that produced by approaching or receding objects. However, the neural mechanisms that detect and predictively encode these motion types remain unclear. Here, we address these questions in the macaque monkey retina. We report that four of the parallel output pathways in the primate retina encode predictive information about the future trajectory of moving objects. Predictive encoding occurs both for translational motion and for higher-order motion patterns found in natural vision. Further, predictive encoding of these motion types is nearly optimal with transmitted information approaching the theoretical limit imposed by the stimulus itself. These findings argue that natural selection has emphasized encoding of information that is relevant for anticipating future properties of the environment.

neuroscience↗

bioRxiv2020

Biomimetic system design for engineering biofidelic 3-D respiratory tissues in vitro

Objective The structural and functional complexity of the respiratory system present significant challenges to capturing conditions vital for maintaining phenotypic cellular functions in vitro. Here we report a unique tissue engineering system that enables respiratory constructs to be cultured under physiological loading at an air-liquid interface (ALI).Methods The system consists of a porous poly-e-caprolactone scaffold mounted in a well insert, which articulates via magnetic coupling with a linear actuator device to strain attached scaffolds through a sterile barrier. For proof of concept, NCI-H460 human carcinoma cells were seeded on scaffold inserts which were subjected to 5-15% cyclic tensile strain at 0.2Hz within a six well plate. The dynamic constructs were cultured at an ALI in a standard incubator for up to 10 days along with unstimulated (static) ALI and static submerged control groups.Results High (near-100%) cell seeding efficiency was achieved within the scaffold-strain device. Both dynamic and static ALI groups yielded higher cell densities compared to the submerged control for all time points. Distinctly different patterns in cellular growth and behaviour between dynamic air-liquid interface and conventional static submerged culture groups were revealed by nuclei staining, where the actuated group displayed more uniform cellular distribution throughout the construct compared to both static controls.Conclusion Air-liquid interface culture and physiological strain are important for engineering respiratory tissue models.Significance The system described allows scalable and replicable culture of 3-D tissue engineered respiratory models under biologically-relevant conditions.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioengineering↗

bioRxiv2019

Discoidan Domain Receptor 1 (DDR1) Tyrosine Kinase is Upregulated in PKD Kidneys But Does Not Play a Role in the Pathogenesis of Polycystic Kidney Disease

Tolvaptan is the only drug approved to slow cyst growth and preserve kidney function in patients with autosomal dominant polycystic kidney disease (ADPKD). However, its limited efficacy combined with significant side effects underscores the need to identify new and safe therapeutic drug targets to slow progression to end stage kidney disease. We identified DDR1 as receptor tyrosine kinase upregulated in vivo in 3 mouse models of ADPKD using a novel mass spectrometry approach to identify kinases upregulated in ADPKD. Previous studies demonstrating critical roles for DDR1 to cancer progression, its potential role in the pathogenesis of a variety of other kidney disease, along with the possibility that DDR1 could provide new insight into how extracellular matrix impacts cyst growth led us to study the role of DDR1 in ADPKD pathogenesis. However, genetic deletion of DDR1 using CRISPR/Cas9 failed to slow cyst growth or preserve kidney function in both a rapid and slow mouse model of ADPKD demonstrating that DDR1 does not play a role in PKD pathogenesis and is thus a not viable drug target. In spite of the negative results, our studies will be of interest to the nephrology community as it will prevent others from potentially conducting similar experiments on DDR1 and reinforces the potential of performing unbiased screens coupled with in vivo gene editing using CRISPR/Cas9 to rapidly identify and confirm new potential drug targets for ADPKD.

cell biology↗