Biology subjects

Kim, J. H.

Publications and source records attributed to Kim, J. H..

11 recordsLinked to original sources

bioRxiv2018

Diagnosis and Prognosis Using Machine Learning Trained on BrainMorphometry and White Matter Connectomes

Accurate, reliable prediction of risk for Alzheimers disease (AD) is essential for early, disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of the multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping--morphometry and structural connectomics--and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (National Health Insurance Service-Ilsan Hospital [NHIS-IH]; N=211; 110 AD, 64 mild cognitive impairment [MCI], and 37 cognitively normal with subjective memory complaints [SMC]) to test the diagnostic models; and, secondly, Alzheimers Disease Neuroimaging Initiative (ADNI)-2 to test the generalizability. Our machine learning models trained on the morphometric and connectome estimates (number of features=34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) in NHIS-IH cohort, outperforming a benchmark model (FLAIR-based white matter hyperintensity volumes). In ADNI-2 data, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) compared with the CSF biomarker model (t-tau, p-tau, and Amyloid {beta}, and ratios). In predicting MCI to AD progression in a smaller cohort of ADNI-2 (n=60), the morphometry model showed similar performance with 69% accuracy compared with CSF biomarker model with 70% accuracy. Our comparison of classifiers trained on structural MRI, diffusion MRI, FLAIR, and CSF biomarkers show the promising utility of the white matter structural connectomes in classifying AD and MCI in addition to the widely used structural MRI-based morphometry, when combined with machine learning.\n\nHighlightsO_LIWe showed the utility of multimodal MRI, combining morphometry and white matter connectomes, to classify the diagnosis of AD and MCI using machine learning.\nC_LIO_LIIn predicting the progression from MCI to AD, the morphometry model showed the best performance.\nC_LIO_LITwo independent clinical datasets were used in this study: one for model building, the other for generalizability testing.\nC_LI

neuroscience↗

bioRxiv2018

The tumor suppressor p53 promotes carcinoma invasion and collective cellular migration

SummaryLoss of function of the tumor suppressor p53 is generally thought to increase cell motility and invasiveness. Using 2-D confluent and 3-D spheroidal cell motility assays with bladder carcinoma cells and colorectal carcinoma cells, we report, to the contrary, that loss of p53 can decrease cell motility and invasion.\n\nAbstractFor migration of the single cell studied in isolation, loss of function of the tumor suppressor p53 is thought to increase cell motility. Here by contrast we used the 2-D confluent cell layer and the 3-D multicellular spheroid to investigate how p53 impacts dissemination and invasion of cellular collectives. We used two human carcinoma cell lines, the bladder carcinoma EJ and the colorectal carcinoma HCT116. We began by replicating single cell invasion in the traditional Boyden chamber assay, and found that the number of invading cells increased with loss of p53, as expected. In the confluent 2-D cell layer, however, for both EJ and HCT, speeds and effective diffusion coefficients for the p53 null types compared to their p53 expressing counterparts were significantly smaller. Compared to p53 expressers, p53 null cells exhibited more organized cortical actin rings together with reduced front-rear cell polarity. Furthermore, loss of p53 caused cells to exert smaller traction forces upon their substrates, and reduced formation of cryptic lamellipodia. In a 3-D collagen matrix, p53 consistently promoted invasion of the multicellular spheroids into surrounding matrix. Together, these results show that p53 expression in these carcinoma model systems increases collective cellular migration and invasion. As such, these studies point to paradoxical contributions of p53 in single cell versus collective cellular migration.

cancer biology↗

bioRxiv2018

Climate Change Influences the Japanese Cedar (Cryptomeria japonica) Pollen Count and Sensitization Rate in South Korea

BackgroundJapanese cedar pollen (JCP) is the major outdoor allergen for spring pollinosis and seasonal allergic rhinitis (SAR) caused by JCP is the most common disease in Jeju Island, South Korea and in Japan. Prior to our research, JCP counts were strongly temperature dependent and were significantly associated with the JCP sensitization rate and JC pollinosis. This event may still be ongoing due to the effects of global climate change, such as increasing temperature.\n\nMethods and FindingFor these reasons, we are studying the correlation among increasing temperatures, the JCP counts in the atmosphere and the JCP sensitization rate.\n\nConclusionsIn this study, our data show that increasing temperatures in January and April might lead to earlier and longer JCP seasons and that earlier and longer JCP seasons lead to an increase in the JCP sensitization rate, which influences the prevalence of JC pollinosis.

epidemiology↗

bioRxiv2018

LADL: Light-activated dynamic looping for endogenous gene expression control

Mammalian genomes are folded into tens of thousands of long-range looping interactions1,2. The cause and effect relationship between looping and genome function is poorly understood, and the extent to which chromatin loops are dynamic on short time scales remains a fundamental unanswered question. Currently available strategies for loop engineering involve synthetic transcription factors tethered to dCas93,4 or zinc fingers5,6, which are constitutively expressed5,6 or induced on long time scales by the presence of a small molecule3. Here we report a new class of 3-D optoepigenetic tools for the directed rearrangement of 3-D chromatin looping on short time scales using blue light. We create synthetic architectural proteins by fusing the CIBN protein subunit from Arabidopsis thaliana with enzymatically dead Cas9 (dCas9). We target our light-activated dynamic looping system (LADL) to two genomic anchors with CRISPR guide RNAs and engineer their spatial co-localization via light-induced heterodimerization of the cryptochrome 2 (CRY2) protein with dCas9-CIBN. We apply LADL to redirect a stretch enhancer (SE) away from its endogenous Klf4 target gene and to the Zfp462 promoter. Looping changes occur as early as four hours after light induction. Using single molecule RNA FISH, we observe a LADL-induced increase in the total nascent Zfp462 transcripts and the number of Zfp462 alleles expressing simultaneously per cell. Moreover, LADL also increased synchronous Sox2 expression after reinforcement of a known Sox2-SE looping interaction. LADL facilitates loop synchronization across a large population of cells without exogenous chemical cofactors and can enable future efforts to engineer reversible and oscillatory looping on short time scales.

molecular biology↗

bioRxiv2018

S100A8/A9 mediate the reprograming of normal mammary epithelial cells induced by dynamic cell-cell interactions with adjacent breast cancer cells.

To understand the potential effects of cancer cells on surrounding normal mammary epithelial cells, we performed direct co-culture of non-tumorigenic mammary epithelial MCF10A cells and various breast cancer cells. Firstly, we observed dynamic cell-cell interactions between the MCF10A cells and breast cancer cells including lamellipodia or nanotube-like contacts and transfer of extracellular vesicles. Co-cultured MCF10A cells exhibited features of epithelial-mesenchymal transition, and showed increased capacity of cell proliferation, migration, colony formation, and 3-dimensional sphere formation. Transcriptome analysis and phosphor-protein array suggested that several cancer-related pathways are significantly dysregulated in MCF10A cells after the direct co-culture with breast cancer cells. S100A8 and S100A9 showed distinct up-regulation in the co-cultured MCF10A cells and their microenvironmental upregulation was also observed in the orthotropic xenograft of syngeneic mouse mammary tumors. When S100A8/A9 overexpression was induced in MCF10A cells, the cells showed phenotypic features of directly co-cultured MCF10A cells in terms of in vitro cell behaviors and signaling activities suggesting a S100A8/A9-mediated transition program in non-tumorigenic epithelial cells. This study suggests the possibility of dynamic cell-cell interactions between non-tumorigenic mammary epithelial cells and breast cancer cells that could lead to a substantial transition in molecular and functional characteristics of mammary epithelial cells.

cancer biology↗

bioRxiv2018

DUSP28 is a novel biomarker responsible for aggravating malignancy via the autocrine signaling pathways in metastatic pancreatic cancer

Pancreatic cancer remains one of the most dangerous cancers with a grave prognosis. We previously reported that pancreatic cancer cells can secrete dual specificity phosphatise 28 (DUSP28) to the cultured medium. However, its biological function is poorly understood. Here, we have identified the function of DUSP28 in human metastatic pancreatic cancer. Treatment with recombinant DUSP28 (rDUSP28) significantly increased the migration, invasion, and viability of metastatic pancreatic cancer cells through the activation of CREB, AKT, and ERK1/2 signaling pathways. Furthermore, rDUSP28 acted as an oncogenic reagent through the interaction with integrin 1 in metastatic pancreatic cancer cells. In addition, rDUSP28 induced pro-angiogenic effects in human umbilical vein endothelial cells (HUVECs). Administration of rDUSP28 also produced tumor growth in vivo. Notably, sDUSP28 can easily be detected by immunoassay. The results establish the rationale for sDUSP28 as a promising therapeutic target and biomarker for metastatic pancreatic cancer patients.

cancer biology↗

bioRxiv2018

Accurate Prediction of Alzheimer’s Disease Using Multi-Modal MRI and High-Throughput Brain Phenotyping

Accurate, reliable prediction of risk for Alzheimers disease (AD) is essential for early, disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of commonly available multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping--morphometry and connectomics--and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (study 1: Ilsan Dementia Cohort; N=211; 110 AD, 64 mild cognitive impairment [MCI], and 37 subjective memory complaints [SMC]) to test and validate the diagnostic models; and, secondly, Alzheimers Disease Neuroimaging Initiative (ADNI)-2 (study 2) to test the generalizability of the approach and the prognostic models with longitudinal follow up data. Our machine learning models trained on the morphometric and connectome estimates (number of features=34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) with iterative nested cross-validation in a single-site study, outperforming the benchmark model (FLAIR-based white matter hyperintensity volumes). In a generalizability study using ADNI-2, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) as CSF biomarker model (t-tau, p-tau, and Amyloid {beta}, and ratios). We also predicted MCI to AD progression with 69% accuracy, compared with the 70% accuracy using CSF biomarker model. The optimal classification accuracy in a single-site dataset and the reproduced results in multi-site dataset show the feasibility of the high-throughput imaging analysis of multimodal MRI and data-driven machine learning for predictive modeling in AD.

neuroscience↗

bioRxiv2018

5C-ID: Increased resolution Chromosome-Conformation-Capture-Carbon-Copy with in situ 3C and double alternating primer design

Mammalian genomes are folded in a hierarchy of compartments, topologically associating domains (TADs), subTADs and looping interactions. Currently, there is a great need to evaluate the link between chromatin topology and genome function across many biological conditions and genetic perturbations. Hi-C generates high quality, high resolution maps of looping interactions genome-wide, but is intractable for high-throughput screening of loops across conditions due to the requirement of an enormous number of reads (>6 Billion) per library. Here, we describe 5C-ID, an updated version of Chromosome-Conformation-Capture-Carbon-Copy (5C) with restriction digest and ligation performed in the nucleus (in situ Chromosome-Conformation-Capture (3C)) and ligation-mediated amplification performed with a new double alternating design. 5C-ID reduces spatial noise and enables higher resolution 3D genome folding maps than canonical 5C, allowing for a marked improvement in sensitivity and specificity of loop detection. 5C-ID enables the creation of high-resolution, high-coverage maps of chromatin loops in up to a 30 Megabase subset of the genome at a fraction of the cost of Hi-C.

genomics↗

bioRxiv2017

Computational docking reveals evolutionary conservation of a specific interaction between 15d-Prostaglandin-J2 and eIF4A.

15-deoxy-delta 12,14-prostaglandin J2 (15d-PGJ2) is anti-inflammatory/antineoplastic prostaglandin which functions through covalent binding to cysteine residues of various target proteins. We previously showed that 15d-PGJ2 mediated anti-inflammatory responses are dependent on the translational inhibition through its interaction with eIF4A. Binding of 15d-PGJ2 to eIF4A specifically blocks the interaction between eIF4G and eIF4A leads to the formation of stress granules (SGs), which cluster mRNAs with inhibited translation. Here we show that the binding between 15d-PGJ2 and eIF4A specifically blocks the interaction between the MIF4G domain of eIF4G and eIF4A. To reveal the mechanism of this interaction, we used computational simulation-based docking studies and identified that the carboxyl tail of 15d-PGJ2 could stabilize the binding of 15d-PGJ2 to eIF4A through arginine 295 of eIF4A, which is the first suggestion that the 15d-PGJ2 tail play a physiological role. Interestingly, the putative 15d-PGJ2 binding site on eiF4A is conserved across many species, suggesting a biological role. Our data propose that studying 15d-PGJ2 and its targets will may uncover new therapeutic approaches in anti-inflammatory drug discovery.

molecular biology↗

bioRxiv2017

Polar-angle representation of saccadic eye movements in human superior colliculus

The superior colliculus (SC) is a layered midbrain structure involved in directing eye movements and coordinating visual attention. Electrical stimulation and neuronal recordings in the intermediate layers of monkey SC have shown a retinotopic organization for the mediation of saccadic eye-movements. However, in human SC the topography of saccades is unknown. Here, a novel experimental paradigm and highresolution (1.2-mm) functional magnetic resonance imaging methods were used to measure activity evoked by saccadic eye movements within SC. Results provide three critical observations about the topography of the human SC: (1) saccades along the superior-inferior visual axis are mapped across the medial-lateral anatomy of the SC; (2) the saccadic eye-movement representation is in register with the retinotopic organization of visual stimulation; and (3) activity evoked by saccades occurs deeper within SC than that evoked by visual stimulation. These approaches lay the foundation for studying the organization of human subcortical eye-movement mechanisms.\n\nHighlightsO_LIHigh-resolution functional MRI enabled imaging from intermediate layers of human SC\nC_LIO_LISaccades along superior-inferior visual field are mapped across medial-lateral SC\nC_LIO_LISaccadic eye movement maps lie deeper in SC and are in alignment with retinotopy\nC_LI\n\neTOC BlurbSavjani et al. found the polar angle representation of saccadic eye movements in human SC. The topography is similar in monkey SC, is in register with the retinotopic organization evoked by visual stimulation, but lies within deeper layers. These methods enable investigation of human subcortical eye-movement organization and visual function.

neuroscience↗

bioRxiv2017

Spectrin is a mechanoresponsive protein shaping the architecture of intercellular invasion

Spectrin is a membrane skeletal protein best known for its structural role in maintaining cell shape and protecting cells from mechanical damage1-3. Here, we report that spectrin dynamically accumulates and dissolves at the fusogenic synapse, where an attacking fusion partner mechanically invades its receiving partner with actin-propelled protrusions to promote cell-cell fusion4-7. Using genetics, cell biology, biophysics and mathematical modeling, we demonstrate that unlike myosin II that responds to dilation deformation, spectrin exhibits a mechanosensitive accumulation in response to shear deformation, which is highly elevated at the fusogenic synapse. The accumulated spectrin forms an uneven network, which functions as a \"sieve\" to constrict the invasive fingerlike protrusions, thus putting the fusogenic synapse under high mechanical tension to promote cell membrane fusion. Taken together, our study has revealed a previously unrecognized function of spectrin as a dynamic mechanoresponsive protein that shapes the architecture of intercellular invasion. These findings have general implications for understanding spectrin function in other dynamic cellular processes beyond cell-cell fusion.

cell biology↗