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- 검색키워드
- 저자 : ( Jo Jihoon Park ) (검색결과 36 건)
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Jo, Jihoon,Heon, Seok,Kim, Myung Jong,Son, Gi Hoon,Park, Yunkyung,Henley, Jeremy M.,Weiss, Jamie L.,Sheng, Morgan,Collingridge, Graham L.,Cho, Kwangwook Elsevier 2008 Neuron Vol.60 No.6
<P><B>Summary</B></P><P>There are two major forms of long-term depression (LTD) of synaptic transmission in the central nervous system that require activation of either N-methyl-D-aspartate receptors (NMDARs) or metabotropic glutamate receptors (mGluRs). In synapses in the perirhinal cortex, we have directly compared the Ca<SUP>2+</SUP> signaling mechanisms involved in NMDAR-LTD and mGluR-LTD. While both forms of LTD involve Ca<SUP>2+</SUP> release from intracellular stores, the Ca<SUP>2+</SUP> sensors involved are different; NMDAR-LTD involves calmodulin, while mGluR-LTD involves the neuronal Ca<SUP>2+</SUP> sensor (NCS) protein NCS-1. In addition, there is a specific requirement for IP3 and PKC, as well as protein interacting with C kinase (PICK-1) in mGluR-LTD. NCS-1 binds directly to PICK1 via its BAR domain in a Ca<SUP>2+</SUP>-dependent manner. Furthermore, the NCS-1-PICK1 association is stimulated by activation of mGluRs, but not NMDARs, and introduction of a PICK1 BAR domain fusion protein specifically blocks mGluR-LTD. Thus, NCS-1 plays a distinct role in mGluR-LTD.</P>
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Jo, Jihoon,Lee, Hyun-Gwan,Kim, Kwang Young,Park, Chungoo The Korean Society of Phycology 2019 ALGAE Vol.34 No.1
DNA metabarcoding is currently used for large-scale taxonomic identification to understand the community composition in various marine ecosystems. However, before being widely used in this emerging field, this experimental and analytic approach still has several technical challenges to overcome, such as polymerase chain reaction (PCR) bias, and lack of well-established metabarcoding markers, a task which is difficult but not impossible to achieve. In this study, we present an adapted PCR-free small-organelles enriched metagenomics (SoEM) method for marine biodiversity assessment. To avoid PCR bias and random artefacts, we extracted target DNA sequences without PCR amplification from marine environmental samples enriched with small organelles including mitochondria and plastids because their genome sequences provide a valuable source of molecular markers for phylogenetic analysis. To experimentally enrich small organelles, we performed subcellular fractionation using modified differential centrifugation for marine environmental DNA samples. To validate our SoEM method, two marine environmental samples from the coastal waters were tested the taxonomic capturing capacity against that of traditional DNA metabarcoding method. Results showed that, regardless of taxonomic levels, at least 3-fold greater numbers of taxa were identified in our SoEM method, compared to those identified by the conventional multi-locus DNA metabarcoding method. The SoEM method is thus effective and accurate for identifying taxonomic diversity and presents a useful alternative approach for evaluating biodiversity in the marine environment.
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Jihoon Jo,오주성,Chungoo Park 한국미생물학회 2020 The journal of microbiology Vol.58 No.3
Microbial communities present in diverse environments from deep seas to human body niches play significant roles in the complex ecosystem and human health. Characterizing their structural and functional diversities is indispensable, and many approaches, such as microscopic observation, DNA fingerprinting, and PCR-based marker gene analysis, have been successfully applied to identify microorganisms. Since the revolutionary improvement of DNA sequencing technologies, direct and high-throughput analysis of genomic DNA from a whole environmental community without prior cultivation has become the mainstream approach, overcoming the constraints of the classical approaches. Here, we first briefly review the history of environmental DNA analysis applications with a focus on profiling the taxonomic composition and functional potentials of microbial communities. To this end, we aim to introduce the shotgun metagenomic sequencing (SMS) approach, which is used for the untargeted (“shotgun”) sequencing of all (“meta”) microbial genomes (“genomic”) present in a sample. SMS data analyses are performed in silico using various software programs; however, in silico analysis is typically regarded as a burden on wet-lab experimental microbiologists. Therefore, in this review, we present microbiologists who are unfamiliar with in silico analyses with a basic and practical SMS data analysis protocol. This protocol covers all the bioinformatics processes of the SMS analysis in terms of data preprocessing, taxonomic profiling, functional annotation, and visualization.
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Jihoon Jo,Hyun-Gwan Lee,Kwang Young Kim,Chungoo Park 한국조류학회I 2019 ALGAE Vol.34 No.1
DNA metabarcoding is currently used for large-scale taxonomic identification to understand the community compositionin various marine ecosystems. However, before being widely used in this emerging field, this experimental andanalytic approach still has several technical challenges to overcome, such as polymerase chain reaction (PCR) bias, andlack of well-established metabarcoding markers, a task which is difficult but not impossible to achieve. In this study, wepresent an adapted PCR-free small-organelles enriched metagenomics (SoEM) method for marine biodiversity assessment. To avoid PCR bias and random artefacts, we extracted target DNA sequences without PCR amplification from marineenvironmental samples enriched with small organelles including mitochondria and plastids because their genomesequences provide a valuable source of molecular markers for phylogenetic analysis. To experimentally enrich smallorganelles, we performed subcellular fractionation using modified differential centrifugation for marine environmentalDNA samples. To validate our SoEM method, two marine environmental samples from the coastal waters were tested thetaxonomic capturing capacity against that of traditional DNA metabarcoding method. Results showed that, regardless oftaxonomic levels, at least 3-fold greater numbers of taxa were identified in our SoEM method, compared to those identifiedby the conventional multi-locus DNA metabarcoding method. The SoEM method is thus effective and accuratefor identifying taxonomic diversity and presents a useful alternative approach for evaluating biodiversity in the marineenvironment.
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Kim, Jihoon,Jo, Songhyun,Park, Kyongsoo,Song, Ha-Joo,Kim, Hyun-Tak,Kim, Bong-Jun,Lee, Yong Wook Optical Society of America 2015 Optics express Vol.23 No.11
<P>By utilizing a CO<sub>2</sub> laser centered at ~10.6 μm as an optical stimulus, we demonstrated bidirectional laser triggering in a two-terminal planar device based on a highly resistive vanadium dioxide (VO<sub>2</sub>) thin film. The break-over voltage of the VO<sub>2</sub>-based device was measured as large as ~294.8 V, which resulted from the high resistivity of insulating VO<sub>2</sub> grains comprising the thin film and the large electrode separation of the device. The bidirectional current switching of up to 20 mA was achieved by harnessing the dramatic resistance variation of the device photo-thermally induced by the laser illumination. The transient responses of laser-triggered currents were also analyzed when laser pulses excited the device at a variety of pulse widths and repetition rates. In the transient responses, a maximum switching contrast between off- and on-state currents was measured as ~7067 with an off-state current of ~2.83 μA, and rising and falling times were measured as ~30 and ~16 ms, respectively, for 100 ms laser pulses.</P>
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Improved memory and reduced anxiety in δ-catenin transgenic mice
Ryu, Taeyong,Park, Hyung Joon,Kim, Hangun,Cho, Young-Chang,Kim, Byeong C.,Jo, Jihoon,Seo, Young-Woo,Choi, Won-Seok,Kim, Kwonseop Academic Press 2019 Experimental neurology Vol.318 No.-
<P><B>Abstract</B></P> <P>δ-Catenin is abundant in the brain and affects its synaptic plasticity. Furthermore, loss of δ-catenin is related to the deficits of learning and memory, mental retardation (cri-du-chat syndrome), and autism. A few studies about δ-catenin deficiency mice were performed. However, the effect of δ-catenin overexpression in the brain has not been investigated as yet. Therefore we generated a δ-catenin overexpressing mouse model. To generate a transgenic mouse model overexpressing δ-catenin in the brain, δ-catenin plasmid having a Thy-1 promotor was microinjected in C57BL/6 mice. Our results showed δ-catenin transgenic mice expressed higher levels of N-cadherin, β-catenin, and p120-catenin than did wild type mice. Furthermore, δ-catenin transgenic mice exhibited better object recognition, better sociability, and lower anxiety than wild type mice. However, both mice groups showed a similar pattern in locomotion tests. Although δ-catenin transgenic mice show similar locomotion, they show improved sociability and reduced anxiety. These characteristics are opposite to the symptoms of autism or mental retardation, which are caused when δ-catenin is deficient. These results suggest that δ-catenin may alleviate symptoms of autism, Alzheimer's disease and mental retardation.</P> <P><B>Highlights</B></P> <P> <UL> <LI> δ-Catenin transgenic mice had improved object recognition. </LI> <LI> δ-Catenin transgenic mice showed improved social interactions. </LI> <LI> δ-Catenin transgenic mice showed less anxiety. </LI> </UL> </P>
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In silico re-identification of properties of drug target proteins
Kim, Baeksoo,Jo, Jihoon,Han, Jonghyun,Park, Chungoo,Lee, Hyunju BioMed Central 2017 BMC bioinformatics Vol.18 No.suppl7
<P><B>Background</B></P><P>Computational approaches in the identification of drug targets are expected to reduce time and effort in drug development. Advances in genomics and proteomics provide the opportunity to uncover properties of druggable genomes. Although several studies have been conducted for distinguishing drug targets from non-drug targets, they mainly focus on the sequences and functional roles of proteins. Many other properties of proteins have not been fully investigated.</P><P><B>Methods</B></P><P>Using the DrugBank (version 3.0) database containing nearly 6,816 drug entries including 760 FDA-approved drugs and 1822 of their targets and human UniProt/Swiss-Prot databases, we defined 1578 non-redundant drug target and 17,575 non-drug target proteins. To select these non-redundant protein datasets, we built four datasets (A, B, C, and D) by considering clustering of paralogous proteins.</P><P><B>Results</B></P><P>We first reassessed the widely used properties of drug target proteins. We confirmed and extended that drug target proteins (1) are likely to have more hydrophobic, less polar, less PEST sequences, and more signal peptide sequences higher and (2) are more involved in enzyme catalysis, oxidation and reduction in cellular respiration, and operational genes. In this study, we proposed new properties (essentiality, expression pattern, PTMs, and solvent accessibility) for effectively identifying drug target proteins. We found that (1) drug targetability and protein essentiality are decoupled, (2) druggability of proteins has high expression level and tissue specificity, and (3) functional post-translational modification residues are enriched in drug target proteins. In addition, to predict the drug targetability of proteins, we exploited two machine learning methods (Support Vector Machine and Random Forest). When we predicted drug targets by combining previously known protein properties and proposed new properties, an F-score of 0.8307 was obtained.</P><P><B>Conclusions</B></P><P>When the newly proposed properties are integrated, the prediction performance is improved and these properties are related to drug targets. We believe that our study will provide a new aspect in inferring drug-target interactions.</P><P><B>Electronic supplementary material</B></P><P>The online version of this article (doi:10.1186/s12859-017-1639-3) contains supplementary material, which is available to authorized users.</P>
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