Biology subjects

Hyun, K.

Publications and source records attributed to Hyun, K..

5 recordsLinked to original sources

bioRxiv2026

Development of a Low-cost Extrusion Multi-nozzle 3D Bioprinter for Complex Constructs

Extrusion-based multi-material bioprinting is a promising approach for fabricating complex tissue constructs, but current systems often require expensive hardware or support only one or a few numbers of bioinks. In this study, a low-cost, compact, and versatile multi-nozzle bioprinter (MNB) system was developed for pneumatic extrusion of up to 10 different inks using a rotational head. The system was integrated with a commercial 3D printer platform and controlled using custom G-code commands. Backlash compensation and nozzle-specific calibrations were experimentally determined to minimize positioning errors and airflow misalignment. The developed system showed stable repeatability in both clockwise and counterclockwise movements. Lines and various structures were successfully printed with different nozzle-switching directions and printing sequences. Representative structures including a diamond pattern, a multilayer scaffold, a pyramid structure, and a kidney-like construct were successfully fabricated. These results demonstrate that the proposed MNB system can produce complex 2D and 3D multi-material structures with good positional accuracy and repeatability.

bioengineering↗

bioRxiv2024

A Novel GelMA-OrnMA Electrically Conductive Bioink for Developing Engineered Neural Tissues

Electrical conductivity is a crucial requirement of matrices for developing engineered neural tissues. A conductive matrix not only supports cell growth but also provides potential to stimulate the cells. However, electrically conductive matrices often require inclusion of synthetic polymers, nanomaterials and large number of ionic species. While enhancing electrical conductivity, often properties like transparency, mechanical stiffness and biocompatibility are compromised which can render the resulting matrices partially suitable for neural tissue engineering. Further, the byproducts of matrix degradation can have unforeseen influences. Therefore, electrically active matrices are required which provide a suitable combination of electrical conductivity, mechanical properties and biocompatibility. In this work, a novel biomaterial is described which results in optically transparent, electrically conductive and highly biocompatible matrices along with ability to match the native neural tissue stiffness. Using gelatin methacryloyl (GelMA) as base hydrogel, we covalently incorporated zwitterionic functional groups to obtain a composite matrix. The zwitterion moieties were derived from Ornithine by synthesizing ornithine methacryloyl (OrnMA) and blending with GelMA inks. Through systematic characterization we demonstrated the suitability of GelMA-OrnMA hydrogels in providing mechanical stiffness matching the native neural tissues, supporting proliferation of human astrocytes in 3D culture and electrical conductivity in the range required for electrically active cell types like astrocytes. Owing to their electrical conductivity, these matrices also influenced the growth of astrocytes which manifested as significant changes in their organization and morphology. These findings suggest that GelMA-OrnMA has immense potential as a bioink for developing engineered neural tissues.

bioengineering↗

bioRxiv2024

Machine Learning Driven Optimization for High Precision Cellular Droplet Bioprinting

Controlled volume microliter cell-laden droplet bioprinting is important for precise biologics deposition, reliably replicating 3D microtissue environments for building cell aggregates or organoids. To achieve this, we propose an innovative machine-learning approach to predict cell-laden droplet volumes according to input parameters. We developed a novel bioprinting platform capable of collecting high-throughput droplet images and generating an extensive dataset for training machine learning and deep learning algorithms. Our research compared the performance of three machine learning and two deep learning algorithms that predict droplet volume based on numerous bioprinting parameters. By adjusting bioink viscosity, nozzle size, printing time, printing pressure, and cell concentration as input parameters, we precisely could control droplet sizes, ranging from 0.1 {micro}L to 50 {micro}L in volume. We utilized a hydrogel precursor composed of 5% gelatin methacrylate and a mixture of 0.5% and 1% alginate, respectively. Additionally, we optimized the cell bioprinting process using green fluorescent protein-tagged 3T3 fibroblast cells. These models demonstrated superior predictive accuracy and revealed the interrelationships among parameters while taking minimal time for training and testing. This method promises to advance the mass production of organoids and microtissues with precise volume control for various biomedical applications.

bioengineering↗

bioRxiv2022

Arginine 65 methylation of Neurogenin 3 by PRMT1 is a prerequisite for development of hESCs into pancreatic endocrine cells

In the developing pancreas, Neurogenin 3 (NGN3) is a key transcription factor in the cell fate determination of endocrine progenitors (EPs). Although the activation and stability of NGN3 are regulated by phosphorylation, the role of arginine methylation of NGN3 is poorly understood. Here, we report arginine 65 methylation of NGN3 is absolutely required for the pancreatic lineage development of human embryonic stem cells (hESCs) in vitro. First, we found inducible protein arginine methyltransferase 1 (PRMT1)-knockout (P-iKO) hESCs did not differentiate from EPs to endocrine cells (ECs) in the presence of doxycycline. Loss of PRMT1 caused an accumulation of NGN3 in the cytoplasm of EPs and blocked NGN3s transcriptional activity in PRMT1-KO EPs. We also found that PRMT1 specifically methylates NGN3 arginine 65, and this modification is a prerequisite for ubiquitin-mediated NGN3 degradation. Our findings indicate arginine 65 methylation of NGN3 is a key molecular switch in hESCs in vitro permitting the differentiation into pancreatic endocrine lineages.

developmental biology↗

bioRxiv2021

IPMK physically binds to the SWI/SNF complex and modulates BRG1 occupancy

Inositol polyphosphate multikinase (IPMK), a key enzyme in the inositol polyphosphate (IP) metabolism, is a pleiotropic signaling factor involved in major biological events including transcriptional control. In yeasts, IPMK and its IP products were known to promote the activity of SWI/SNF chromatin remodeling complex, which plays a critical role in gene expression by regulating chromatin accessibility. However, the direct linkage between IPMK and chromatin remodelers remains unclear, raising a question on how IPMK contributes to the transcriptional regulation in mammals. By employing unbiased screenings and in vivo/in vitro immunoprecipitations, here we demonstrated that IPMK physically associates with native mammalian SWI/SNF complexes by directly binding to SMARCB1, BRG1, and SMARCC1. Furthermore, we identified the specific domains required for the IPMK-SMARCB1 binding. Notably, using CUT&RUN and ATAC-seq assays, we discovered that IPMK co-localizes with BRG1 and regulates BRG1 localization as well as BRG1-mediated chromatin accessibility in a genome-wide manner (including promoter-TSS) in mouse embryonic stem cells. Finally, our mRNA-seq analyses revealed that IPMK and SMARCB1 regulate common gene sets, validating a functional link between IPMK and SWI/SNF complex. Together, these findings establish an importance of IPMK in promoter targeting of the SWI/SNF complex, thereby contributing to SWI/SNF-meditated chromatin accessibility and transcription.

molecular biology↗