Biology subjects

Moon, H.

Publications and source records attributed to Moon, H..

13 recordsLinked to original sources

bioRxiv2026

Generation of Human Taste Bud Organoids as a Human-Mimetic Platform for Modeling Taste Perception

We established a human taste bud organoid system derived from circumvallate papillae. This model has been highly anticipated in the field of taste research, where feasible approaches for validating taste biology discovered in rodent models have been limited. Through a stepwise exploratory strategy, we systematically identified and optimized the niche factors required to maintain taste bud organoids and promote their differentiation. This human taste bud organoid system comprises Type I-IV taste receptor cells (TRCs) as well as stem/progenitor cells, and its sensory receptor cells exhibit calcium responses to taste stimuli. Using this system, we identified robust Wnt signaling as a requirement for optimal TRC fate progression, uncovered a human-specific transcriptional program in LGR5 cells, and identified previously unrecognized molecular markers for Type I TRCs. By recapitulating native human taste bud cell diversity and function, this organoid provides a tractable platform for studying human taste biology and dysfunction.

developmental biology↗

bioRxiv2026

High-variance phenome database reveals important roles of WD40 proteins in the plant pathogenic fungus Fusarium graminearum

WD40 is a highly conserved protein domain in eukaryotes, playing a critical role in various cellular process. We conducted genome-wide functional analysis of WD40 genes in Fusarium graminearum-a phytopathogenic fungus that causes severe yield loss and mycotoxin contamination in major cereal crops. Comprehensive phenome analysis of 119 WD40 gene deletion mutants across 22 distinct phenotypic traits revealed phenotypic divergence within the phenome, establishing a strong correlation between virulence and sexual reproduction. Notably, 21 core WD40 genes were identified, offering valuable insights into divergent biological processes. Pilot interactome studies of Fgwd101 and Fgwd133 provided further insights into their potential pathobiological functions. Our investigation contributes to broadening our knowledge of the biological mechanisms underlying fungal pathogenesis and may assist in the identification of targets for antifungal agents.

molecular biology↗

bioRxiv2026

Label-free quantitative phenotyping of hepatic stellate cell activation using holotomography with AI-enabled subcellular segmentation

Hepatic stellate cell (HSC) activation is a central driver of liver fibrosis, yet its quantitative characterization in living cells remains limited by endpoint assays that rely on fixation and labeling. Here we introduce a label-free framework that combines three-dimensional holotomography (HT) with automated, AI-assisted analysis to study HSC activation dynamics in live cells. Using refractive index tomography, we non-invasively visualize hallmark structural features of HSC activation, including lipid droplet depletion, cytoskeletal remodeling, and changes in cellular morphology. Correlative fluorescence imaging validates the biological relevance of HT-derived features, while longitudinal imaging reveals continuous activation trajectories at single-cell resolution. Automated segmentation of whole cells and subcellular organelles enables scalable extraction of multi-parametric biophysical descriptors, defining a quantitative phenotypic fingerprint that distinguishes quiescent and activated states. Together, this work establishes holotomography-based quantitative phenotyping as a powerful approach for studying HSC activation and, more broadly, dynamic cell-state transitions in living systems.

cell biology↗

bioRxiv2025

A framework to infer de novo exonic variants when parental genotypes are missing enhances association studies of autism

MotivationGene-damaging mutations are highly informative for studies seeking to discover genes underlying developmental disorders. Traditionally, these de novo variants are recognized by evaluating high-quality DNA sequence from affected offspring and parents. However, when parental sequence is unavailable, methods are required to infer de novo status and use this inference for association studies. ResultsWe use data from autism spectrum disorder to illustrate and evaluate methods. Separating de novo from rare inherited variants is challenging because the latter are far more common. Using a classifier for unbalanced data and variants of known inheritance class, we build an inheritance model and then a de novo score for variants when parental data are missing. Next, we propose a new Random Draw (RD) model to use this score for gene discovery. Built into an existing inferential framework, RD produces a more powerful gene-based association test and controls the false discovery rate. Availability and ImplementationThe implementation code and publicly available data are provided at: https://github.com/HaeunM/TADA-RD.

bioinformatics↗

bioRxiv2025

Adaptive selection of p53 mutation metaplastic phenotypes in estrogen-independent progression of ER+ tumors: A mechanism for acquired resistance to hormonal therapy.

Estrogen receptor positive (ER+) subtypes of mammary adenocarcinoma comprise 79% of all breast cancer diagnosis and 67% of all breast cancer mortality. The paucity of models of ER+ mammary cancer that mimic human disease and response to treatment has limited critical preclinical study of mechanisms and new therapies for ER+ breast cancer. The Stat1 knockout, 129S6/SvEvTac-Stat1tm1Rds (Stat1-/-), females develop luminal type FoxA1+, ER+, and PR+ mammary carcinomas after prolonged latencies. Initial studies showed that a cell line derived from a Stat1-/- mammary carcinoma was tumorigenic in syngeneic mice, but non-tumorigenic in ovariectomized (Ovx) mice. Here, data shows that Ovx performed after SSM2 tumors establish growth results in ovarian hormone independent growth. The viable post-Ovx tumors were primarily composed of metaplastic CK14+ basal type cells with a high percentage p53 immunohistochemistry (IHC) positive "mutation pattern", rather than the original luminal type tumors with low percent "wild type" pattern p53. Comparing whole exome sequences of ER+ Stat1-/- mammary tumors before and after Ovx, revealed basal keratins, mesenchymal (EMT) phenotypes, and unique mutation profiles in genes, including Trp53 and Prlr, in the estrogen-independent tumors. Our experimental findings are consistent with the clinical evidence of tumor heterogeneity of ER+ breast cancers in patients in recent whole genome sequencing studies. Similarly, spontaneous Stat1-/- tumors with high percentage p53 "mutation pattern" were more basaloid and grew rapidly after Ovx, while retaining high expression of ER and FoxA1. This study demonstrates that the STAT1-/-, ER+ estrogen dependent breast cancers can become resistant to through clonal selection of mammary cells comprised of metaplastic p53+/CK14+ basaloid cells.

cancer biology↗

bioRxiv2024

Putative neofunctionalization of a Poales-specific EXO70 clade

EXO70s are uniquely expanded in land plants compared to all other eukaryotic lineages. The functional implications of this expansion and diversification on the conserved role of EXO70 as a subunit of the octameric exocyst complex have remained unresolved. We previously demonstrated barley (Hordeum vulgare) EXO70FX12, a member of the monocot-specific EXO70FX clade, is required for resistance to wheat stripe rust in conjunction with the leucine-rich repeat receptor kinase (LRR-RK) HvPUR1. Through phylogenetic analysis, we identified unique features of the EXO70FX clade, leading us to hypothesize that this clade experienced neofunctionalization. Using structural predictions and protein-protein interaction assays, we demonstrate that HvEXO70FX12 lost the ability to serve as a subunit within the exocyst complex. We predict that the EXO70FX clade has largely lost exocyst association and represents a novel acquisition that emerged during Poales diversification for immunity.

plant biology↗

bioRxiv2024

Molecular tension authenticates apoptotic cells being phagocytosed.

Profound cytoskeletal reorganization and plasma membrane deformation in phagocytes is indispensable for phagocytosis of massive apoptotic cells, but whether these dynamics accompany a mechanical signal modulating signaling during efferocytosis remains largely unexplored. Here, we report that tension between phosphatidylserine (PS) and PS receptors (PSR) generated at the phagocytic synapse serves as a signal to determine whether PS-exposing cells should be phagocytosed. Mechanistically, increased membrane tension of phagocytes via Rac1-dependent actin polymerization and membrane stiffness of apoptotic cells caused tension between PS and PSRs, leading to phosphoinositide 3-kinase recruitment to PSRs, which resulted in Rac1 inactivation and myosin II phosphorylation required for phagocytic cup closure. Our observations imply that tension between PS and PSRs acts as a mechanical fail-safe to prevent removal of all PS-exposing cells for the integrity of efferocytosis. One-Sentence SummaryTension between phosphatidylserine and its receptors acts as a final decision-maker determining phagocytosis of apoptotic cells.

cell biology↗

bioRxiv2024

Augmented Doubly Robust Post-Imputation Inference for Proteomic data

Quantitative measurements produced by mass spectrometry proteomics experiments offer a direct way to explore the role of proteins in molecular mechanisms. However, analysis of such data is challenging due to the large proportion of missing values. A common strategy to address this issue is to utilize an imputed dataset, which often introduces systematic bias into down-stream analyses if the imputation errors are ignored. In this paper, we propose a statistical framework inspired by doubly robust estimators that offers valid and efficient inference for proteomic data. Our framework combines powerful machine learning tools, such as variational autoencoders, to augment the imputation quality with high-dimensional peptide data, and a parametric model to estimate the propensity score for debiasing imputed outcomes. Our estimator is compatible with the double machine learning framework and has provable properties. Simulation studies verify its empirical superiority over other existing procedures. In application to both single-cell proteomic data and bulk-cell Alzheimers Disease data our method utilizes the imputed data to gain additional, meaningful discoveries and yet maintains good control of false positives.

bioinformatics↗

bioRxiv2023

Metastatic prognostic ability of lung cancer stromal cells from a single-cell RNA-seq perspective

Single-cell RNA sequencing (scRNA-seq) has been widely studied and analyzed to understand cancer heterogeneity. Metastasis and invasion through communication with immune cells have been widely studied; stromal cells are known to change during cancer progression and cause metastasis, but little is known about their inherent metastasis prognostic abilities. This study investigated the abilities of stromal cells by analyzing the scRNA-seq data of adjacent, tumor, and metastasized tissues, biopsied from 15 patients. We considered fibroblast and smooth muscle cells as cell subtypes of stromal cells. We detected decorin (DCN) and insulin-like growth factor-binding protein 7 (IGFBP7) as sub-cell type markers conserved in tumor and metastasis. We found an organic relationship that affects metastasis by assessing the interaction between the expression and related pathways among the assigned stromal cell subtypes. In addition to the interactions of sub-cell-types within stromal cells, we also studied communication between stromal cells and the five assigned lung cancer cell types, and observed its relation with migration and metastasis; the role of DCN as a mediating factor was also studied. Results of our study indicated that DCN and IGFBP7 are factors that can be monitored in the follow-up of prognostic metastasis factors in patients with lung cancer. Therefore, DCN and IGFBP7, which are the assigned sub-cell types marker in lung cancer stromal cells, can be used as potential biomarkers for follow-up in lung cancer metastasis. Our study assigned stromal cell subtypes of lung cancer and detected markers that can be used as monitoring factors during metastasis of lung cancer. This suggests that DCN and IGFBP7 are potential biomarkers to evaluate metastatic ability and follow-up as metastatic prognostic factors in lung cancer patients. Author SummaryLung cancer is known to be a disease with high heterogeneity. In particular, it has been studied that stromal cells of lung cancer are involved in metastasis in cancer. Finding specific markers of stromal cell subtypes can lead to more accurate cancer markers. In this study, we assigned stromal cell subtypes as FB and SMC through scRNA-seq data analysis. DCN and IGFBP7, which are markers specifically expressed in stromal cell sub-cell types of NSCLC and metastatic NSCLC, were found. Whether DCN and IGFBP7 can be used as prognostic factors for metastasis was verified through co-expression analysis of FB and SMC and cell-cell communication. Specific expression as a marker was verified by confirming the role in the hub-gene network and the target genes of communication. Our findings suggest that DCN and IGFBP7 are potential biomarkers for evaluating the metastasis prognostic ability of stromal cells and can be monitored in the follow-up of metastasis prognostic factors in lung cancer patients.

bioinformatics↗

bioRxiv2023

Generative artificial intelligence GPT-4 accelerates knowledge mining and machine learning for synthetic biology

Knowledge mining from synthetic biology journal articles for machine learning (ML) applications is a labor-intensive process. The development of natural language processing (NLP) tools, such as GPT-4, can accelerate the extraction of published information related to microbial performance under complex strain engineering and bioreactor conditions. As a proof of concept, we used GPT-4 to extract knowledge from 176 publications on two oleaginous yeasts (Yarrowia lipolytica and Rhodosporidium toruloides). After integration with a molecule inventory database, the outcome is a total of 2037 data instances and 28 features, which serve as machine learning inputs. The structured datasets enabled ML approaches (e.g., a random forest model) to predict Yarrowia fermentation titers with high accuracy (R2 of 0.86 for unseen test data). Via transfer learning, the trained model could also assess the production capability of the non-conventional yeast, R. toruloides, for which there are fewer published reports. This work demonstrated the potential of generative artificial intelligence to speed up information extraction from research articles, thereby improving design-build-test-learn (DBTL) cycles for commercial biomanufacturing development.

bioengineering↗

bioRxiv2021

Median based absolute quantification of proteins using Fully Unlabelled Generic Internal Standard

By reporting molar abundances of proteins, absolute quantification determines their stoichiometry in complexes, pathways or networks. Typically, absolute quantification relies either on protein-specific isotopically labelled peptide standards or on a semi-empirical calibration against the average abundance of peptides chosen from arbitrary selected proteins. In contrast, a generic protein standard FUGIS (for Fully Unlabelled Generic Internal Standard) requires no isotopic labelling, chemical synthesis or external calibration and is applicable to quantifying proteins of any organismal origin. The median intensity of peptide peaks produced by the digestion of FUGIS is used as a single point calibrant to determine the molar abundance of any co-digested protein. Powered by FUGIS, median based absolute quantification (MBAQ) outperformed other available methods of untargeted proteome-wide absolute quantification.

biochemistry↗

bioRxiv2021

Effect of chronic JUUL aerosol inhalation on inflammatory states of the brain, lung, heart and colon in mice

While health effects of conventional tobacco are well defined, data on vaping devices, including the most popular e-cigarette JUUL, are less established. Prior acute e-cigarette studies demonstrated inflammatory and cardiopulmonary physiology changes while chronic studies demonstrated extra-pulmonary effects, including neurotransmitter alterations in reward pathways. In this study we investigated effects of chronic flavored JUUL aerosol inhalation on inflammatory markers in brain, lung, heart, and colon. JUUL induced upregulation of cytokine and chemokine gene expression and increased HMGB1 and RAGE in the nucleus accumbens. Inflammatory gene expression increased in colon, and cardiopulmonary inflammatory responses to acute lung injury with lipopolysaccharide were exacerbated in the heart. Flavor-dependent changes in several responses were also observed. Our findings raise concerns regarding long-term risks of e-cigarette use as neuroinflammation may contribute to behavioral changes and mood disorders, while gut inflammation has been tied to poor systemic health and cardiac inflammation to development of heart disease. One Sentence SummaryChronic, daily inhalation of pod-based e-cigarette aerosols alters the inflammatory state across multiple organ systems in mice.

immunology↗

bioRxiv2020

Transcriptomic, protein-DNA interaction, and metabolomic studies of VosA, VelB, and WetA in Aspergillus nidulans asexual spores

In filamentous fungi, asexual development involves morphological differentiation and metabolic changes leading to the formation of asexual spores. The process of asexual spore formation in Aspergillus is precisely regulated by multiple transcription factors (TFs), including VosA, VelB, and WetA, and these three TFs are key regulators of the formation and maturation of asexual spores (conidia) in Aspergillus including the model fungus Aspergillus nidulans. To gain a mechanistic insight on the complex regulatory roles of these TFs in asexual spores, we conducted genome-wide studies on the expression, protein-DNA interactions, and primary and secondary metabolism employing A. nidulans conidia. RNA sequencing and chromatin immunoprecipitation-sequencing data have revealed that the three TFs directly or indirectly regulate the expression of genes associated with spore-wall formation/integrity, asexual development, and secondary metabolism. In addition, metabolomics analyses of wild-type and mutant conidia indicate that these three TFs regulate a diverse array of primary and secondary metabolism. In summary, WetA, VosA, and VelB play inter-dependent and distinct roles governing morphological development and primary/secondary metabolic remodeling in Aspergillus conidia. ImportanceFilamentous fungi produce a vast number of asexual spores that act as reproductive and propagator cells. These spores affect humans, due to the infectious or allergenic nature of the propagule. Aspergillus species produce asexual spores called conidia and their formation involves morphological development and metabolic changes, and the associated regulatory systems are coordinated by spore-specific transcription factors. To understand the underlying global regulatory programs and cellular outcomes associated with conidia formation, functional genomic and metabolomic analyses were performed in the model fungus Aspergillus nidulans. Our results show that the fungus specific WetA/VosA/VelB transcription factors govern the coordination of morphological and chemical developments during sporogenesis. The results of this study provide insights into the genetic regulatory networks about how morphological developments and metabolic changes are coordinated in fungi. The findings are relevant for other Aspergillus species such as the major human pathogen Aspergillus fumigatus and the aflatoxin-producer Aspergillus flavus.

microbiology↗