• KSBB Journal
• /
• 제24권3호
• /
• pp.287-290
• /
• 2009

최근 미생물을 이용하여 기존에 화학산업을 통하여 생산되어지던 여러 화학물질 혹은 대사산물을 생산하려는 연구가 활발히 이루어지고 있다. 이러한 연구를 통하여 미생물의 대사특성을 개량하기 위하여는, 미생물의 대사 특성을 분석하는 연구가 일차적으로 수행되어져야 한다. 본 연구에서는 대사network간의 기능적 연관성을 분석하기 위하여 transcriptome 연구에 주로 활용되던 ARACNE 기법이 활용되었다. 특정 대사 subpathway들이 미생물 균주들 사이에 존재하는 패턴이 유사하다면 그 대사 subpathway들이 서로 기능적 상관관계를 가지고 있을 가능성이 높다는 가정 하에, ARACNE를 활용하여 미생물들의 subrathway들의 존재 패턴을 분석함으로서 각 subpathway 사이의 기능적 상관관계를 분석하여 보았다. 본 연구에 활용된 새로운 대사network 분석기법을 활용한다면 더욱 효율적인 대사network 분석연구가 수행될 수 있을 것이라 기대된다.

• Journal of Microbiology and Biotechnology
• /
• 제16권7호
• /
• pp.1139-1143
• /
• 2006

Various techniques and strategies have been developed for the identification of intracellular metabolic conditions, and among them, isotope balance-based flux analysis with gas chromatography/mass spectrometry (GC/ MS) has recently become popular. Even though isotope balance-based flux analysis allows a more accurate estimation of intracellular fluxes, its application has been restricted to relatively small metabolic systems because of the limited number of measurable metabolites. In this paper, a strategy for incorporating isotope balance-based flux data obtained for a small network into metabolic flux analysis was examined as a feasible alternative allowing more accurate quantification of intracellular flux distribution in a large metabolic system. To impose GC/MS based data into a large metabolic network and obtain optimum flux distribution profile, data reconciliation procedure was applied. As a result, metabolic flux values of 308 intracellular reactions could be estimated from 29 GC/ MS based fluxes with higher accuracy.

• Genomics & Informatics
• /
• 제4권3호
• /
• pp.118-124
• /
• 2006

For the direct understanding of flow, pathway data are usually represented as directed graphs in biological journals and texts. Databases of metabolic pathways or signal transduction pathways inevitably contain these kinds of graphs to show the flow. KEGG, one of the representative pathway databases, uses the manually drawn figure which can not be easily maintained. Graph layout algorithms are applied for visualizing metabolic pathways in some databases, such as EcoCyc. Although these can express any changes of data in the real time, it exponentially increases the edge crossings according to the increase of nodes. For the understanding of genome scale flow of metabolism, it is very important to reduce the unnecessary edge crossings which exist in the automatic graph layout. We propose a metabolic pathway drawing algorithm for reducing the number of edge crossings by considering the fact that metabolic pathway graph is scale-free network. The experimental results show that the number of edge crossings is reduced about $37{\sim}40%$ by the consideration of scale-free network in contrast with non-considering scale-free network. And also we found that the increase of nodes do not always mean that there is an increase of edge crossings.

• 제어로봇시스템학회논문지
• /
• 제11권10호
• /
• pp.823-829
• /
• 2005

We have newly constructed an in silico model of fermentative metabolism for Lactococcus lactis in order to analyze the characteristics of metabolite flux for dynamic network. A rigorous mathematical model for metabolic flux has been developed and simulation researches have been performed by using GEPASI program. In this simulation task, we were able to predict the whole flux distribution trend for lactate metabolism and analyze the flux ratio on the pyruvate branch point by using metabolic flux analysis(MFA). And we have studied flux control coefficients of key reaction steps in the model by using metabolic control analysis(MCA). The role of pyruvate branch seems to be essential for the secretion of lactate and other organic byproducts. Then we have made an effort to elucidate its metabolic regulation characteristics and key reaction steps, and find an optimal condition for the production of lactate.

• 지역사회간호학회지
• /
• 제30권3호
• /
• pp.271-280
• /
• 2019

Purpose: This study evaluates the efficacy of a Self-Care Reinforcement Program (SCRP) based on the Selection Optimization Compensation (SOC) model, in socially vulnerable elderly women with metabolic syndrome. Methods: This study adopts a pretest-posttest nonequivalent control group design. The participants were 64 socially vulnerable elderly Korean women with metabolic syndrome (experimental group: 31, control group: 33). Participants' body composition analysis, nutrient intake, risk factors of metabolic syndrome, depressive symptoms, and social network were measured. Data were analyzed with an independent t-test; statistical significance levels were set at p<.05. The SCRP, including metabolic syndrome education, nutritional education, exercise, and social network, was performed three times a week for 8 weeks. Results: There were statistically significant differences between the experimental and control groups in terms of systolic blood pressure, diastolic pressure, fasting blood sugar, triglycerides, sodium intake, depressive symptoms, and social networks. Conclusion: The SCRP is effective and can be recommended as a community health nursing intervention for socially vulnerable elderly women with metabolic syndrome.

• Biotechnology and Bioprocess Engineering:BBE
• /
• 제10권5호
• /
• pp.425-431
• /
• 2005

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution resides in silico genome-scale metabolic model, In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.

• Biotechnology and Bioprocess Engineering:BBE
• /
• 제10권5호
• /
• pp.462-469
• /
• 2005

A top-down approach is known to be a useful and effective technique for the design and analysis of metabolic systems. In this Study, we have constructed a grouped metabolic network for Lactococcus lactis under aerobic conditions using grouped enzyme kinetics. To test the usefulness of grouping work, a non-grouped system and grouped systems were compared quantitatively with each other. Here, grouped Systems were designed as two groups according to the extent of grouping. The overall simulated flux values in grouped and non-grouped models had pretty similar distribution trends, but the details on flux ratio at the pyruvate branch point showed a little difference. This result indicates that our grouping technique can be used as a good model for complicated metabolic networks, however, for detailed analysis of metabolic network, a more robust mechanism Should be considered. In addition to the data for the pyruvate branch point analysis, Some major flux control coefficients were obtained in this research.

• 응용통계연구
• /
• 제27권5호
• /
• pp.705-715
• /
• 2014

대사증후군은 뇌졸중이나 심혈관 질환 등 다양한 합병증으로 발전될 수 있어 그 심각성이 커지고 있으며, 우리나라의 유병률이 증가하는 추세를 보이고 있어 연구의 필요성이 강조되고 있다. 본 연구는 베이지안 네트워크를 활용하여 대사증후군과 그 진단기준이 되는 5가지 이상 징후인 복부비만, 고중성지방혈증, 고혈압, 저 HDL 콜레스테롤혈증, 고혈당의 관계에 대한 모델을 구축 하고자 하였다. 추가적으로 대사증후군의 가장 위험한 진단조합을 선별하였고, 개개인의 특성에 따라 대사증후군의 특징도 다르게 나타난다는 것을 확인하였다. 사용된 데이터는 제5기 국민건강영양조사 중 2010년 자료로써 건강설문조사의 모든 문항에 응답한 성인 4,489명의 데이터이다.

• Journal of Microbiology and Biotechnology
• /
• 제15권1호
• /
• pp.161-174
• /
• 2005

Abstract Glycolysis has a main function to provide ATP and precursor metabolites for biomass production. Although glycolysis is one of the most important pathways in cellular metabolism, the details of its regulation mechanism and regulating chemicals are not well known yet. The regulation of the glycolytic pathway is very robust to allow for large fluxes at almost constant metabolite levels in spite of changing environmental conditions and many reaction effectors like inhibitors, activating compounds, cofactors, and related metal ions. These changing environmental conditions and metabolic reaction effectors were focused on to understand their roles in the metabolic networks. In this study, we have investigated for construction of the regulatory map of the glycolytic metabolic network and tried to collect all the effectors as much as possible which might affect the glycolysis metabolic pathway. Using the results of this study, it is expected that a complex metabolic situation can be more precisely analyzed and simulated by using available programs and appropriate kinetic data.

• Interdisciplinary Bio Central
• /
• 제5권2호
• /
• pp.3.1-3.7
• /
• 2013

Recently, the productivity of drug discovery has gradually decreased as the limitations of single-target-based drugs for various and complex diseases become exposed. To overcome these limitations, drug combinations have been proposed, and great efforts have been made to predict efficacious drug combinations by statistical methods using drug databases. However, previous methods which did not take into account biological networks are insufficient for elaborate predictions. Also, increased evidences to support the fact that drug effects are closely related to metabolic enzymes suggested the possibility for a new approach to the study drug combinations. Therefore, in this paper we suggest a novel approach for analyzing drug combinations using a metabolic network in a systematic manner. The influence of a drug on the metabolic network is described using the distance between the drug target and an enzyme. Target-enzyme distances are converted into influence scores, and from these scores we calculated the correlations between drugs. The result shows that the influence score derived from the targetenzyme distance reflects the mechanism of drug action onto the metabolic network properly. In an analysis of the correlation score distribution, efficacious drug combinations tended to have low correlation scores, and this tendency corresponded to the known properties of the drug combinations. These facts suggest that our approach is useful for prediction drug combinations with an advanced understanding of drug mechanisms.