• Journal of Microbiology and Biotechnology
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• v.27 no.7
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• pp.1345-1358
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• 2017

The impact of overproduction of a heterologous protein on the metabolic system of host Lactococcus lactis was investigated. The protein expression profiles of L. lactis IL1403 containing two near-identical plasmids that expressed high- and low-level of the green fluorescent protein (GFP) were examined via shotgun proteomics. Analysis of the two strains via high-throughput LC-MS/MS proteomics identified the expression of 294 proteins. The relative amount of each protein in the proteome of both strains was determined by label-free quantification using the spectral counting method. Although expression level of most proteins were similar, several significant alterations in metabolic network were identified in the high GFP-producing strain. These changes include alterations in the pyruvate fermentation pathway, oxidative pentose phosphate pathway, and de novo synthesis pathway for pyrimidine RNA. Expression of enzymes for the synthesis of dTDP-rhamnose and N-acetylglucosamine from glucose was suppressed in the high GFP strain. In addition, enzymes involved in the amino acid synthesis or interconversion pathway were downregulated. The most noticeable changes in the high GFP-producing strain were a 3.4-fold increase in the expression of stress response and chaperone proteins and increase of caseinolytic peptidase family proteins. Characterization of these host expression changes witnessed during overexpression of GFP was might suggested the metabolic requirements and networks that may limit protein expression, and will aid in the future development of lactococcal hosts to produce more heterologous protein.

• Genomics & Informatics
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• v.12 no.4
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• pp.187-194
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• 2014

Metabolic syndrome (METS) is a disorder of energy utilization and storage and increases the risk of developing cardiovascular disease and diabetes. To identify the genetic risk factors of METS, we carried out a genome-wide association study (GWAS) for 2,657 cases and 5,917 controls in Korean populations. As a result, we could identify 2 single nucleotide polymorphisms (SNPs) with genome-wide significance level p-values (< $5{\times}10^{-8}$), 8 SNPs with genome-wide suggestive p-values ($5{\times}10^{-8}{\leq}$ p < $1{\times}10^{-5}$), and 2 SNPs of more functional variants with borderline p-values ($5{\times}10^{-5}{\leq}$ p < $1{\times}10^{-4}$). On the other hand, the multiple correction criteria of conventional GWASs exclude false-positive loci, but simultaneously, they discard many true-positive loci. To reconsider the discarded true-positive loci, we attempted to include the functional variants (nonsynonymous SNPs [nsSNPs] and expression quantitative trait loci [eQTL]) among the top 5,000 SNPs based on the proportion of phenotypic variance explained by genotypic variance. In total, 159 eQTLs and 18 nsSNPs were presented in the top 5,000 SNPs. Although they should be replicated in other independent populations, 6 eQTLs and 2 nsSNP loci were located in the molecular pathways of LPL, APOA5, and CHRM2, which were the significant or suggestive loci in the METS GWAS. Conclusively, our approach using the conventional GWAS, reconsidering functional variants and pathway-based interpretation, suggests a useful method to understand the GWAS results of complex traits and can be expanded in other genomewide association studies.

• BMB Reports
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• v.54 no.9
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• pp.464-469
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• 2021

Cardiomyocyte differentiation occurs through complex and finely regulated processes including cardiac lineage commitment and maturation from pluripotent stem cells (PSCs). To gain some insight into the genome-wide characteristics of cardiac lineage commitment, we performed transcriptome analysis on both mouse embryonic stem cells (mESCs) and human induced PSCs (hiPSCs) at specific stages of cardiomyocyte differentiation. Specifically, the gene expression profiles and the protein-protein interaction networks of the mESC-derived platelet-derived growth factor receptor-alpha (PDGFRα)⁺ cardiac lineage-committed cells (CLCs) and hiPSC-derived kinase insert domain receptor (KDR)⁺ and PDGFRα⁺ cardiac progenitor cells (CPCs) at cardiac lineage commitment were compared with those of mesodermal cells and differentiated cardiomyocytes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that the genes significantly upregulated at cardiac lineage commitment were associated with responses to organic substances and external stimuli, extracellular and myocardial contractile components, receptor binding, gated channel activity, PI3K-AKT signaling, and cardiac hypertrophy and dilation pathways. Protein-protein interaction network analysis revealed that the expression levels of genes that regulate cardiac maturation, heart contraction, and calcium handling showed a consistent increase during cardiac differentiation; however, the expression levels of genes that regulate cell differentiation and multicellular organism development decreased at the cardiac maturation stage following lineage commitment. Additionally, we identified for the first time the protein-protein interaction network connecting cardiac development, the immune system, and metabolism during cardiac lineage commitment in both mESC-derived PDGFRα⁺ CLCs and hiPSC-derived KDR⁺PDGFRα⁺ CPCs. These findings shed light on the regulation of cardiac lineage commitment and the pathogenesis of cardiometabolic diseases.

• Journal of Microbiology and Biotechnology
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• v.16 no.11
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• pp.1661-1677
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• 2006

Rhizobium and related genera are soil bacteria with great metabolic plasticity. These microorganisms survive in many different environments and are capable of eliciting the formation of nitrogen-fixing nodules on legumes. The successful establishment of symbiosis is precisely regulated and requires a series of signal exchanges between the two partners. Quorum sensing (QS) is a prevalent form of population density-dependent gene regulation. Recently, increasing evidence indicates that rhizobial quorum sensing provides a pervasive regulatory network, which plays a more generalized role in the physiological activity of free-living rhizobia, as well as during symbiosis. Several rhizobia utilize multiple, overlapping quorum sensing systems to regulate diverse properties, including conjugal transfer and copy number control of plasmids, exopolysaccharide biosynthesis, rhizosphere-related functions, and cell growth. Genomic and proteomic analyses have begun to reveal the wide range of functions under quorum-sensing control.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.292-294
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• 2005

대사증후군은 당뇨병, 고혈압, 복부 비만, 고지혈증 등의 질병이 한 개인에게 동시에 발현하는 것을 말한다. 미국에서는 $25\%$ 이상의 성인이 대사성 증후군인 것으로 알려져 있으며, 경제 여건의 향상 및 식생활 습관의 변화와 함께 최근 우리나라에서도 심각한 문제가 되고 있다. 한편 불확실성의 처리를 위해 많이 사용되고 있는 베이지안 네트워크는 사람이 분석 가능한 확률 기반의 모델로 최근 의학 분야에서 지식 발견, 데이터 마이닝을 위한 도구로 유용하게 사용되고 있다. 본 논문에 서 는 대사증후군을 예측하는 문제를 다루며, 베이지안 네트워크와 의학 지식을 이용한 대사증후군의 예측 모델을 제안한다. 제안하는 모델을 통해 1993년의 데이터를 가지고 1995년의 상태를 예측하는 분류 실험을 수행하였으며, 실험 결과 다층 신경망, k-최근접 이웃 등의 분류기 보다 높은 $81.5\%$의 예측율을 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.1-3
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• 2006

대사증후군은 당뇨병, 고혈압, 복부 비만, 고지혈증 등의 질병이 한 개인에게 동시에 발현하는 것을 말하며, 최근 경제여건의 향상 및 식생활 습관의 변화와 함께 우리나라에서도 심각한 문제가 되고 있다. 한편 불확실성의 처리를 위해 많이 사용되는 베이지안 네트워크는 사람이 분석 가능한 확률 기반의 모델로 최근 의학분야에서 질병의 진단이나 예측모델을 구성하기 위한 방법으로 유용하게 사용되고 있다. 베이지안 네트워크의 구조를 학습하는 대표적인 알고리즘인 K2 알고리즘은 속성이 입력되는 순서의 영향을 받으며, 따라서 이 또한 하나의 주제로써 연구되어 왔다. 본 논문에서는 유전자 알고리즘을 이용하여 베이지안 네트워크에 입력되는 속성 순서를 최적화하며 이 과정에서 의학지식을 적용해 효율적인 최적화가 가능하도록 하였다. 제안하는 모델을 통해 1993년의 데이터를 가지고 1995년의 상태를 예측하는 분류 실험을 수행한 결과 속성 순서 최적화 후에 이전보다 향상된 예측율을 보였으며 또한 다층 신경망, k-최근접 이웃 등을 이용한 다른 모델보다 더 높은 예측율을 보였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.349-352
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• 2005

이 논문에서는 분산된 생물학의 대사 네트워크들이 있을 때, 이를 통합하지 않은 상태에서 경로검색을 하는 분산 알고리즘을 제안한다. 대사 네트워크는 여러 데이터베이스에 존재하며 서로 중복되는 데이터를 가지고 있다. 제안한 방법은 네트워크 사이의 중첩이 있는 부분을 하이퍼 노드로 하고, 네트워크 자체는 하이퍼 에지로 하는 추상 하이퍼 그래프를 만들어서, 이를 이용한 상위수준의 경로를 구축한다. 각 네트워크내의 중첩된 영역간의 경로를 미리 계산해 둔 다음, 상위수준의 경로에 기반하여 분산된 대사네트워크 간에 존재하는 경로를 검색한다. 추상 하이퍼 그래프는 데이터베이스를 하이퍼 노드로 하는 것에 대한 경로탐색을 한 다음, 그 경로에 따라 데이터베이스 내에 존재하는 대사경로를 탐색한다. 이때 존재하는 대사경로가 많기 때문에 각각의 대사경로를 하이퍼 노드로 하는 추상 하이퍼 그래프를 만들어 경로를 탐색하고 나서 그 하위 노드에 대해 경로탐색을 한다. 이는 분산된 네트워크를 통합할 저장 공간 및 탐색시간을 줄일 수 있다는 장점이 있다.

• Molecules and Cells
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• v.39 no.1
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• pp.20-25
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• 2016

Photosynthesis is a highly robust process allowing for rapid adjustment to changing environmental conditions. The efficient acclimation depends on balanced redox metabolism and control of reactive oxygen species release which triggers signaling cascades and potentially detrimental oxidation reactions. Thiol peroxidases of the peroxiredoxin and glutathione peroxidase type, and ascorbate peroxidases are the main peroxide detoxifying enzymes of the chloroplast. They use different electron donors and are linked to distinct redox networks. In addition, the peroxiredoxins serve functions in redox regulation and retrograde signaling. The complexity of plastid peroxidases is discussed in context of suborganellar localization, substrate preference, metabolic coupling, protein abundance, activity regulation, interactions, signaling functions, and the conditional requirement for high antioxidant capacity. Thus the review provides an opinion on the advantage of linking detoxification of peroxides to different enzymatic systems and implementing mechanisms for their inactivation to enforce signal propagation within and from the chloroplast.

• Molecules and Cells
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• v.45 no.10
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• pp.673-684
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• 2022

The past two decades have witnessed an upsurge in the appreciation of adipose tissue (AT) as an immunometabolic hub harbouring heterogeneous cell populations that collectively fine-tune systemic metabolic homeostasis. Technological advancements, especially single-cell transcriptomics, have offered an unprecedented opportunity for dissecting the sophisticated cellular networks and compositional dynamics underpinning AT remodelling. The "re-discovery" of functional brown adipose tissue dissipating heat energy in human adults has aroused tremendous interest in exploiting the mechanisms underpinning the engagement of AT thermogenesis for combating human obesity. In this review, we aim to summarise and evaluate the use of single-cell transcriptomics that contribute to a better appreciation of the cellular plasticity and intercellular crosstalk in thermogenic AT.

• Genomics & Informatics
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• v.6 no.4
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• pp.210-222
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• 2008

Due to the polygenic nature of cancer, it is believed that breast cancer is caused by the perturbation of multiple genes and their complex interactions, which contribute to the wide aspects of disease phenotypes. A systems biology approach for the identification of subnetworks of interconnected genes as functional modules is required to understand the complex nature of diseases such as breast cancer. In this study, we apply a 3-step strategy for the interpretation of microarray data, focusing on identifying significantly perturbed metabolic pathways rather than analyzing a large amount of overexpressed and underexpressed individual genes. The selected pathways are considered to be dysregulated functional modules that putatively contribute to the progression of disease. The subnetwork of protein-protein interactions for these dysregulated pathways are constructed for further detailed analysis. We evaluated the method by analyzing microarray datasets of breast cancer tissues; i.e., normal and invasive breast cancer tissues. Using the strategy of microarray analysis, we selected several significantly perturbed pathways that are implicated in the regulation of progression of breast cancers, including the extracellular matrix-receptor interaction pathway and the focal adhesion pathway. Moreover, these selected pathways include several known breast cancer-related genes. It is concluded from this study that the present strategy is capable of selecting interesting perturbed pathways that putatively play a role in the progression of breast cancer and provides an improved interpretability of networks of protein-protein interactions.