• Horticultural Science & Technology
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• v.33 no.1
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• pp.114-123
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• 2015

Plants can respond and adapt to cold stress through regulation of gene expression in various biochemical and physiological processes. Cold stress triggers decreased rates of metabolism, modification of cell walls, and loss of membrane function. Hence, this study was conducted to construct coexpression networks for time-based expression pattern analysis of genes related to cold stress in Chinese cabbage (Brassica rapa ssp. pekinensis). B. rapa cold stress networks were constructed with 2,030 nodes, 20,235 edges, and 34 connected components. The analysis suggests that similar genes responding to cold stress may also regulate development of Chinese cabbage. Using this network model, it is surmised that cold tolerance is strongly related to activation of chitinase antifreeze proteins by WRKY transcription factors and salicylic acid signaling, and to regulation of stomatal movement and starch metabolic processes for systemic acquired resistance in Chinese cabbage. Moreover, within 48 h, cold stress triggered transition from vegetative to reproductive phase and meristematic phase transition. In this study, we demonstrated that this network model could be used to precisely predict the functions of cold resistance genes in Chinese cabbage.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.337-338
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• 2015

알츠하이머병은 뇌에 비이상적으로 베타아밀로이드 단백질의 축적으로 인해 신경세포가 손상되는 질병으로 아직까지 명확한 질병의 메커니즘이 밝혀지지 않고 있다. 새로운 알츠하이머병의 생물학적 모델을 제시하기 위해, KEGG의 알츠하이머병의 신호전달패스웨이와 문헌정보를 기반으로 구축된 신호전달 네트워크를 병합함으로써 새로운 질병의 모델을 생성하였다. 분석결과 로바스타틴하부경로를 포함하는 새로운 알츠하이머 생물학적 경로 모델을 제시하고자 한다. 향후 메디컬 페스웨이의 병합기술을 통해 보다 다양한 질병의 원인 기작을 연구하는데 활용하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.11-16
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• 2006

세포의 활동은 단순히 하나의 유전자의 발현으로 설명되기보다 여러 유전자와 그로 인해 생성된 단백질의 상호 작용에 의해 나타난다. 또한 마이크로어레이 실험을 통해 세포 내의 유전자 발현에 대한 정보를 알 수 있게 되고, Chromatin IP 마이크로어레이 실험을 통해 신뢰도가 높은 유전자 발현 조절 관계 데이터를 얻을 수 있게 되면서, 유사한 기능과 유사한 발현 패턴을 보이는 유전자들을 그룹으로 묶어 유전자 모듈로 규정하고 이를 하나의 유전자 조절 네트워크로 구성하고, 분석하는 연구들이 진행되고 있다. 본 논문에서는 ChIP 실험 데이터와 유전자 발현 데이터를 이용하여 지역 정렬을 수행해 하나의 유전자 모듈을 조절하는 조절 프로그램을 예측하는 알고리즘에 대해 기술한다. 조절 프로그램은 유전자 조절 모듈을 조절하는 조절자들의 역할 및 발현 여부에 따른 유전자 조절 모듈 내 유전자들의 발현을 설명할 수 있는 것이다.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.265-271
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• 2004

The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

• Korean Journal of Microbiology
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• v.45 no.1
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• pp.10-16
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• 2009

A diverse range of stresses such as heat, cold, salt, ethanol, oxygen starvation or nutrient starvation induces same stress-responsive proteins. This general stress response enhances bacterial survival significantly. In Bacillus subtilis and closely related Gram-positive bacteria Listeria monocytogenes, the general stress response is controlled by the alternative transcription factor ${\sigma}^B$. The activity of ${\sigma}^B$ is regulated post-translationally by a signal transduction network that has been extensively studied in B. subtilis, and serve as a model for L. monocytogenes. The proposed model of L. monocytogenes signal transduction network is similar to that of B. subtilis, but the energy stress pathway is missing. More than 150 general stress proteins belong to ${\sigma}^B$ regulon of B. subtilis and L. monocytogenes. In both bacteria, ${\sigma}^B$ function is primarily important for resistance to diverse stresses. In addition, ${\sigma}^B$ function contributes to the control of important virulence genes in food-borne pathogen L. monocytogenes. Therefore, understanding of the general stress response is important not only for bacterial physiology, but also for pathogenicity.

• Journal of Life Science
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• v.30 no.12
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• pp.1070-1077
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• 2020

Treatment with anticancer drugs changes the expression of multiple genes related to cell proliferation, migration, and drug resistance. These changes in gene expression may be connected to regulatory networks for each other. This study showed that doxorubicin treatment induces the expression of oncogenic FosB and decreases the expression of oncogenic SETDB1 in A549 and H1299 human lung cancer cells, which are different in tumor suppressor p53 status. However, a small difference was detected in the quantitative expression of those proteins in the two kinds of cells. To examine the potential regulation of SETDB1 and FosB by p53, we predicted putative p53 binding sites on the genomic DNA of SETDB1 and FosB using a TF motif binding search program. These putative p53 binding sites were identified as 18 sites in the promoter regions of SETDB1 and 21 sites in the genomic DNA of FosB. A luciferase assay confirmed that p53 negatively regulated the promoter activities of SETDB1 and FosB. Furthermore, the results of RT-PCR, western blot, qPCR, and immunostaining experiments indicated that the transfection of exogenous p53 decreases the expression of SETDB1 and FosB in H1299 cells. This indicates that p53 negatively regulates the expression of SETDB1 and FosB at the transcriptional level. Collectively, the downregulation of SETDB1 and FosB by p53 may provide functional networks for apoptosis and for the survival of cancer cells during anticancer drug treatment.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.467-475
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• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• Journal of Life Science
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• v.30 no.6
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• pp.501-512
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• 2020

Sasa quelpaertensis Nakai leaf has been used as a folk medicine for the treatment of gastric ulcer, dipsosis, and hematemesis based on its anti-inflammatory, antipyretic, and diuretic characteristics. We have previously reported the procedure for deriving a phytochemical-rich extract (PRE) from S. quelpaertensis and how PRE and its ethyl acetate fraction (EPRE) exhibits an anticancer effect by inducing apoptosis in various gastric cancer cells. To explore the molecular targets involved in this apoptosis, we investigated the mRNA and microRNA profiles of EPRE-treated SNU-16 human gastric cancer cells. In total, 2,875 differentially expressed genes were identified by RNA sequencing, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the EPRE-modulated genes are associated with apoptosis, mitogen-activated protein kinase, inflammatory response, tumor necrosis factor signaling, and cancer pathways. Subsequently, protein-protein interaction network analysis confirmed interactions among genes associated with cell death and apoptosis, and 27 differentially expressed microRNAs were identified by further sequencing. Here, GO and KEGG pathway analysis revealed that EPRE modified the expression of microRNAs associated with the cell cycle and cell death, as well as signaling of tropomyosin-receptor-kinase receptor, transforming growth factor-b, nuclear factor kB, and cancer pathways. Taken together, these results provide insight into the mechanisms underlying the anticancer effect of EPRE.

• Journal of Life Science
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• v.28 no.10
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• pp.1244-1253
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• 2018

Rumen microbiome consists of a wide variety of microorganisms, such as bacteria, archaea, protozoa, fungi, and viruses, that are in a symbiotic relationship in a strict anaerobic environment in the rumen. These rumen microbiome, a vital maker, play a significant role in feed fermentation within the rumen and produce different volatile fatty acids (VFAs). VFAs are essential for energy metabolism and protein synthesis of the host animal, even though emission of methane gas after feed fermentation is considered a negative indicator of loss of dietary energy of the host animal. To improve rumen microbial efficiency, a variety of approaches, such as feed formulation, the addition of natural feed additives, dietary feed-microbes, etc., have taken to increase ruminant performance. Recently with the application of high-throughput sequencing or next-generation sequencing technologies, especially for metagenomics and metatranscriptomics of rumen microbiomes, our understanding of rumen microbial diversity and function has significantly increased. The metaproteome and metabolome provide deeper insights into the complicated microbial network of the rumen ecosystem and its response to different ruminant diets to improve efficiency in animal production. This review summarized some recent advances of rumen microbiome techniques, especially "meta-omics," viz. metagenomic, metatranscriptomic, metaproteomic, and metabolomic techniques to increase feed fermentation and utilization in ruminants.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.5
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• pp.738-746
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• 2011

We manufactured rice-whole soybean curd by a microbial transglutaminase (MTGase) with a mixture of hydrolyzed rice and micronized whole soybean powder (MWSP) and analyzed its rheological properties, including texture, viscoelasticity, protein cross-linking, and surface structure. A 40% rice suspension digested with a Termamyl enzyme at $85^{\circ}C$ for 20 min showed a 9.0% reducing sugar and a consistency of $1.27\;Pa{\cdot}s^n$, resulting in a great reduction in consistency. A MWSP suspension with 22% solid content was transformed into a typical tofu texture. MWSP curd fortified with 7.5% rice showed enhanced texture properties, with a hardness of 639.6 dyne/$cm^2$, and a springiness of 0.96. In a MWSP suspension (18~22% w/v) treated with 5% MTGase, viscoelasticity increased dependently with MWSP concentration, and a 22% MWSP indicated a G' value of 5.1 Pa and a G'' value of 9.0 Pa. Furthermore, soybean proteins present in the 22% MWSP curd largely disappeared or formed polymers with a high molecular weight by MTGase reaction within 30 min. MWSP (22%) fortified with 7.5% rice showed similar polymerization patterns on SDS-PAGE. The surface structure of the rice-MWSP curds was more dense and homogeneous network due to the addition of hydrolyzed rice. However, the surface structure of all rice-MWSP curds became rough and showed a non-homogeneous network after cold storage.