Biology subjects

Kim, Y. W.

Publications and source records attributed to Kim, Y. W..

6 recordsLinked to original sources

bioRxiv2025

Vitamin K-dependent carboxylation in osteoblasts regulates bone resorption through GAS6

Studies in humans suggest that vitamin K is involved in the regulation of bone remodeling, but the precise mechanism at play remains unknown. In cells, vitamin K functions as a co-factor for the {gamma}-glutamyl carboxylase (GGCX), an enzyme responsible for the conversion of glutamic acid residues (Glu) into {gamma}-carboxyglutamic acid (Gla) residues in secreted proteins. We aim here at determining the role of {gamma}-carboxylation in bone remodeling and at identifying the Gla protein(s) involved. We show that male mice lacking {gamma}-carboxylation specifically in osteoblasts (Ggcxflox/flox;OCN-Cre) have increased bone mass at 6 months of age due to a reduced number of multinucleated bone resorbing osteoclasts. In co-culture experiments, Ggcx-deficient osteoblasts were less effective than control osteoblasts at supporting osteoclast formation. Among known Gla proteins, we identify GAS6 as an osteoblast-secreted {gamma}-carboxylated factor which signals to differentiating osteoclasts. The GAS6 receptors MerTK and AXL are expressed in pre-osteoclasts and pharmacological inhibitors of AXL and MerTK block osteoclast generation in co-culture. Conversely, recombinant {gamma}-carboxylated GAS6 dose-dependently increases the size of osteoclasts and the number of nuclei per osteoclast in culture. GAS6 marginally affected the induction of osteoclast-specific genes during osteoclast differentiation but significantly increased pre-osteoclast fusion. Finally, increasing bone marrow GAS6 level in transgenic male mice was sufficient to increase the number and size of osteoclasts and to decrease bone mass. This work identifies GAS6 as a novel osteoblast-derived vitamin K-dependent protein regulating osteoclast maturation.

cell biology↗

bioRxiv2021

Histone H3K4me1 and H3K27ac play roles in nucleosome depletion and eRNA transcription, respectively, at enhancers

Histone H3K4me1 and H3K27ac are enhancer specific modifications and are required for enhancers to activate transcription of target genes. However the reciprocal effects of these histone modifications on each other and their roles in enhancers are not clear. Here to comparatively analyze the role of these modifications, we inhibited H3K4me1 and H3K27ac by deleting SET domain of histone methyltransferases MLL3 and MLL4 and HAT domain of histone acetyltransferase p300, respectively, in erythroid K562 cells. The loss of H3K4me1 reduced H3K27ac at the {beta}-globin enhancer LCR HSs, but H3K27ac reduction did not affect H3K4me1. This unequal relationship between two modifications was revealed in putative enhancers by genome-wide analysis using ChIP-seq. Histone H3 depletion at putative enhancers was weakened by the loss of H3K4me1 but not by the loss of H3K27ac. Chromatin remodeling complexes were recruited into the {beta}-globin LCR HSs in a H3K4me1-dependent manner. In contrast, H3K27ac was required for enhancer RNA (eRNA) transcription, and H3K4me1 was not enough for it. Forced H3K27ac induced eRNA transcription without affecting H3K4me1 at the {beta}-globin LCR HSs. These results indicate that H3K4me1 and H3K27ac affect each other in different ways and play more direct roles in nucleosome depletion and eRNA transcription, respectively, at enhancers.

molecular biology↗

bioRxiv2020

Aggregation of Cohorts for Histopathological Diagnosis with Deep Morphological Analysis

There have been substantial efforts in using deep learning (DL) to diagnose cancer from digital images of pathology slides. Existing algorithms typically operate by training deep neural networks (DNNs) either specialized in specific cohorts or an aggregate of all cohorts when there are only a few images available for the target cohort. A trade-off between decreasing the number of models and their cancer detection performance was evident in our experiments with The Cancer Genomic Atlas (TCGA) dataset, with the former approach achieving higher performance at the cost of having to acquire large datasets from the cohort of interest. Constructing annotated datasets for individual cohorts is extremely time-consuming, with the acquisition cost of such datasets growing linearly with the number of cohorts. Another issue associated with developing cohort-specific models is the difficulty of maintenance: all cohort-specific models may need to be adjusted when a new DL algorithm is to be used, where training even a single model may require a non-negligible amount of computation, or when more data is added to some cohorts. In resolving the sub-optimal behavior of a universal cancer detection model trained on an aggregate of cohorts, we investigated how cohorts can be grouped to augment a dataset without increasing the number of models linearly with the number of cohorts. This study introduces several metrics which measure the morphological similarities between cohort pairs and demonstrates how the metrics can be used to control the trade-off between performance and the number of models.

pathology↗

bioRxiv2020

Multiscale label-free volumetric holographic histopathology of thick-tissue slides with subcellular resolution

Histopathology relies upon the staining and sectioning of biological tissues, which can be laborious and may cause artefacts and distort tissues. Here, we demonstrate label-free volumetric imaging of thick-tissue slides, exploiting refractive index distributions as intrinsic imaging contrast. The present method systematically exploits label-free quantitative phase imaging techniques, volumetric reconstruction of intrinsic refractive index distributions in tissues, and numerical algorithms for the seamless stitching of multiple 3D tomograms and for reducing scattering-induced image distortion. We demonstrate demonstrated label-free volumetric imaging of thick tissues with the field of view of 2 mm x 1.75 mm x 0.2 mm with a spatial resolution of 170 nm x 170 nm x 1200 nm. The number of optical modes, calculated as the reconstructed volume divided by the size of the point spread function, was approximately 20 Giga voxels. We have also demonstrated that different tumour types, and a variety of precursor lesions and pathologies can be visualized with the present method. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/205633v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@dcf15corg.highwire.dtl.DTLVardef@16a05d3org.highwire.dtl.DTLVardef@1a48860org.highwire.dtl.DTLVardef@f57430_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2020

GATA-1-dependent histone H3K27ac mediates erythroid cell-specific interaction between CTCF sites

CTCF sites interact with each other in the chromatin environment, establishing domains. Our previous study showed that interaction between CTCF sites is cell type-specific around the {beta}-globin locus and is dependent on erythroid specific activator GATA-1. To find out molecular mechanisms of the cell type-specific interaction, we directly inhibited GATA-1 binding to the {beta}-globin enhancers by deleting its binding motifs and found that histone H3K27 acetylation (H3K27ac) was decreased at CTCF sites surrounding the {beta}-globin locus, even though CTCF binding itself was maintained at the sites. Forced H3K27ac by TSA treatment or CBP/p300 KD affected the interactions between CTCF sites around the {beta}-globin locus. Analysis of public ChIA-PET data revealed that H3K27ac is higher at CTCF sites forming short chromatin interactions than long interactions. The short interactions contain erythropoiesis-associated genes and GATA-1 binding sites in erythroid K562 cells. Depletion of GATA-1 reduced H3K27ac at CTCF sites near erythroid enhancers. These results indicate that GATA-1-dependent histone H3K27ac at neighboring CTCF sites mediates erythroid specific chromatin interaction between them.

molecular biology↗

bioRxiv2017

Evolutionary Action of de novo missense variants across pathways prioritizes genes linked to autism and predicts patient phenotypic severity

The pathogenicity of individual de novo missense mutations in autism spectrum disorder remains difficult to validate. Here we asked in 2,384 probands whether these variants exhibited collective functional impact biases across pathways. As measured with Evolutionary Action (EA) in 368 gene groupings, we found significant biases in axonogenesis, synaptic transmission, and other neurodevelopmental pathways. Strikingly, both de novo and inherited missense variants in prioritized genes correlated with patient IQ. This general integrative approach thus detects missense variants most likely to contribute to autism pathogenesis and is the first, to our knowledge, to link missense variant impact to autism phenotypic severity.

genomics↗