Biology subjects

Chun, B.

Publications and source records attributed to Chun, B..

5 recordsLinked to original sources

bioRxiv2026

Multi-omics Characterization of Duck Embryonic Stem Cells for Cultivated Meat

Industrializing cultivated meat requires cell lines with high proliferative capacity, genetic stability, and suspension adaptability. We present a comprehensive multi-omics framework, integrating genomics, transcriptomics, and proteomics, to characterize a commercial duck Embryonic Stem Cell (dESC) line. Our analysis demonstrates continuous proliferation in protein-free suspension media while maintaining a stable genome and a functional conserved transcriptome. Broad-scale transcriptomics confirms the absence of hazardous pathway activation, and targeted assays verify sustained pluripotency marker expression during scale-up. Compositional analysis reveals a low-fat biomass containing all nine essential amino acids with an amino acid profile comparable to conventional duck meat. Furthermore, proteomic profiling demonstrates inter-batch reproducibility and protein distributions comparable to duck breast and liver. This study provides the first detailed molecular characterization of a commercial cultivated meat cell line, establishing a reference for the stability and safety assessment of future cultivated meat cell lines.

cell biology↗

bioRxiv2021

Identifying metabolic adaptations during cardiotoxicity using paired transcriptomics andmetabolomics data integrated with a model of heart metabolism

Improvements in the diagnosis and treatment of cancer has revealed the long-term side effects of chemotherapeutics, particularly cardiotoxicity. Here, we present paired transcriptomics and metabolomics data characterizing in vitro cardiotoxicity to three compounds: 5-fluorouracil, acetaminophen, and doxorubicin. Standard gene enrichment and metabolomics approaches identify some commonly affected pathways and metabolites but are not able to readily identify metabolic adaptations in response to cardiotoxicity. The paired data was integrated with a genome-scale metabolic network reconstruction (GENRE) of the heart to identify shifted metabolic functions, unique metabolic reactions, and changes in flux in metabolic reactions in response to these compounds. Using this approach, we confirm known mechanisms of doxorubicin-induced cardiotoxicity and provide hypotheses for metabolic adaptations in cardiotoxicity for 5-fluorouracil, doxorubicin, and acetaminophen.

bioengineering↗

bioRxiv2021

Live Monitoring of Inflammation Reveals Tissue and Sex-specific Responses to Western Diet and Butyrate treatment

Obesity is a current epidemic, affecting millions of individuals worldwide. Chronic obesity is characterized by a low-grade systemic inflammation besides not being a classic inflammatory disease. Many studies have tried to identify inflammatory insults dysregulated by a Westernized diet - consisted of high fat, high sucrose, and high cholesterol -mainly focusing on production and secretion of inflammatory cytokines. The gut microbiome and derived metabolites, including the short-chain fatty acid butyrate, have received increased attention as underlying some of the obesogenic features. In the present work, we utilized a novel biosensor mouse model capable of monitoring in vivo inflammation. We observed tissue- and sex- specific caspase-1 activation patterns in obese mice and treated with butyrate. Our work utilizing a caspase-1 biosensor mouse model, flow cytometry and computational analyses and offers new mechanistic insights underlying the effect of butyrate in obesity and its complications.

neuroscience↗

bioRxiv2021

High-content live-cell imaging reveals co-regulation of cardiomyocyte decisions of hypertrophy and apoptosis

Cardiomyocyte hypertrophy and apoptosis underlie cardiomyopathies and heart failure. While previous studies have reported both hypertrophy and apoptosis at the population level, how individual cells commit to these distinct analog and digital fates is unclear. To elucidate how individual cells decide to grow and/or die, we developed a high-content microscopy approach to track single-cell cardiomyocyte dynamics. Even untreated cells exhibited substantial single-cell variability in growth and death. Uniform treatments of staurosporine or phenylephrine induced distinctive morphological programs resulting in apoptosis and hypertrophy, respectively, but only in cell subpopulations. Increasing concentrations of the {beta}-adrenergic receptor agonist isoproterenol caused a population-level biphasic induction of hypertrophy and then apoptosis, consistent with either apoptosis in the most hypertrophic cells (a grow-and-die model) or an early decision between hypertrophy and delayed apoptosis (a grow-or-die model). By tracking single-cell fates, we found that when stressed with either isoproterenol or phenylphrine, individual cells that hypertrophy are protected from later apoptosis. Further, caspase 3 inhibition shifted the single-cell probability from apoptosis to hypertrophy fates. Machine learning models found that a cells initial size and DNA content or condensation could predict a cells bias for hypertrophy or apoptosis. Together, these data support a grow-or-die conceptual model for cardiomyocyte decisions. This single-cell profiling method for tracking joint analog-digital cell decisions reveals that despite hypertrophy and apoptosis co-occurring at the population level, individual cardiomyocytes decide early whether to grow or die.

bioinformatics↗

bioRxiv2018

Simulation of P2X-mediated calcium signaling in microglia

Microglia function is orchestrated through highly-coupled signaling pathways that depend on calcium (Ca2+). In response to extracellular adenosine triphosphate (ATP), transient increases in intracellular Ca2+ driven through the activation of purinergic receptors, P2X and P2Y, are sufficient to promote cytokine synthesis and potentially their release. While steps comprising the pathways bridging purinergic receptor activation with transcriptional responses have been probed in great detail, a quantitative model for how these steps collectively control cytokine production has not been established. Here we developed a minimal computational model that quantitatively links extracellular stimulation of two prominent ionotropic puriner-gic receptors, P2X4 and P2X7, with the graded production of a gene product, namely the tumor necrosis factor (TNF) cytokine. In addition to Ca2+ handling mechanisms common to eukaryotic cells, our model includes microglia-specific processes including ATP-dependent P2X4 and P2X7 activation, activation of NFAT transcription factors, and TNF production. Parameters for this model were optimized to reproduce published data for these processes, where available. With this model, we determined the propensity for TNF production in microglia, subject to a wide range of ATP exposure amplitudes, frequencies and durations that the cells could encounter in vivo. Furthermore, we have investigated the extent to which modulation of the signal transduction pathways influence TNF production. Our key findings are that TNF production via P2X4 is maximized at low ATP when subject to high frequency ATP stimulation, whereas P2X7 contributes most significantly at millimolar ATPranges. Given that Ca2+ homeostasis in microglia is profoundly important to its function, this computational model provides a quantitative framework to explore hypotheses pertaining to microglial physiology.

systems biology↗