• 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.

• 제어로봇시스템학회논문지
• /
• 제11권10호
• /
• pp.843-850
• /
• 2005

FBA(flux balance analysis) with Boolean rules for representing regulatory events has correctly predicted cellular behaviors, such as optimal flux distribution, maximal growth rate, metabolic by-product, and substrate concentration changes, with various environmental conditions. However, until now, since FBA has not taken into account a hierarchical regulatory network, it has limited the representation of the whole transcriptional regulation mechanism and interactions between specific regulatory proteins and genes. In this paper, in order to solve these problems, we describe the construction of hierarchical regulatory network with defined symbols and the introduction of a weight for representing interactions between symbols. Finally, the whole cellular behaviors with time were simulated through the linkage of a hierarchical regulatory network module and dynamic simulation module including FBA. The central metabolic network of E. coli was chosen as the basic model to identify our suggested modeling method.

• Biotechnology and Bioprocess Engineering:BBE
• /
• 제7권5호
• /
• pp.237-251
• /
• 2002

The recent progress on metabolic systems engineering was reviewed based on our recent research results in terms of (1) metabolic signal flow diagram approach, (2) metabolic flux analysis (MFA) in particular with intracellular isotopomer distribution using NMR and/or GC-MS, (3) synthesis and optimization of metabolic flux distribution (MFD), (4) modification of MFD by gene manipulation and by controlling culture environment, (5) metabolic control analysis (MCA), (6) design of metabolic regulation structure, and (7) identification of unknown pathways with isotope tracing by NMR. The main characteristics of metabolic engineering is to treat metabolism as a network or entirety instead of individual reactions. The applications were made for poly-3-hydroxybutyrate (PHB) production using Ralstonia eutropha and recombinant Escherichia coli, lactate production by recombinant Saccharomyces cerevisiae, pyruvate production by vitamin auxotrophic yeast Toluropsis glabrata, lysine production using Corynebacterium glutamicum, and energetic analysis of photosynthesic microorganisms such as Cyanobateria. The characteristics of each approach were reviewed with their applications. The approach based on isotope labeling experiments gives reliable and quantitative results for metabolic flux analysis. It should be recognized that the next stage should be toward the investigation of metabolic flux analysis with gene and protein expressions to uncover the metabolic regulation in relation to genetic modification and/ or the change in the culture condition.

• Molecules and Cells
• /
• 제28권2호
• /
• pp.75-80
• /
• 2009

The cyclic environmental conditions brought about by the 24 h rotation of the earth have allowed the evolution of endogenous circadian clocks that control the temporal alignment of behaviour and physiology, including the uptake and processing of nutrients. Both metabolic and circadian regulatory systems are built upon a complex feedback network connecting centres of the central nervous system and different peripheral tissues. Emerging evidence suggests that circadian clock function is closely linked to metabolic homeostasis and that rhythm disruption can contribute to the development of metabolic disease. At the same time, metabolic processes feed back into the circadian clock, affecting clock gene expression and timing of behaviour. In this review, we summarize the experimental evidence for this bimodal interaction, with a focus on the molecular mechanisms mediating this exchange, and outline the implications for clock-based and metabolic diseases.

• IMMUNE NETWORK
• /
• 제20권6호
• /
• pp.46.1-46.13
• /
• 2020

Neutrophils are innate immune cells that constitute the first line of defense against invading pathogens. Due to this characteristic, they are exposed to diverse immunological environments wherein sources for nutrients are often limited. Recent advances in the field of immunometabolism revealed that neutrophils utilize diverse metabolic pathways in response to immunological challenges. In particular, neutrophils adopt specific metabolic pathways for modulating their effector functions in contrast to other immune cells, which undergo metabolic reprogramming to ensure differentiation into distinct cell subtypes. Therefore, neutrophils utilize different metabolic pathways not only to fulfill their energy requirements, but also to support specialized effector functions, such as neutrophil extracellular trap formation, ROS generation, chemotaxis, and degranulation. In this review, we discuss the basic metabolic pathways used by neutrophils and how these metabolic alterations play a critical role in their effector functions.

• Genomics & Informatics
• /
• 제9권4호
• /
• pp.143-151
• /
• 2011

In this study, we propose a novel, intuitive method of constructing an expression quantitative trait (eQT) network that is related to the metabolic syndrome using LOD scores and peak loci for selected eQTs, based on the concept of gene-gene interactions. We selected 49 eQTs that were related to insulin resistance. A variance component linkage analysis was performed to explore the expression loci of each of the eQTs. The linkage peak loci were investigated, and the "support zone" was defined within boundaries of an LOD score of 0.5 from the peak. If one gene was located within the "support zone" of the peak loci for the eQT of another gene, the relationship was considered as a potential "directed causal pathway" from the former to the latter gene. SNP markers under the linkage peaks or within the support zone were searched for in the database to identify the genes at the loci. Two groups of gene networks were formed separately around the genes IRS2 and UGCGL2. The findings indicated evidence of networks between genes that were related to the metabolic syndrome. The use of linkage analysis enabled the construction of directed causal networks. This methodology showed that characterizing and locating eQTs can provide an effective means of constructing a genetic network.

• Korean Chemical Engineering Research
• /
• 제51권2호
• /
• pp.226-232
• /
• 2013

부탄올을 생산하는 발효반응기에서는 아세톤, 부탄올 그리고 에탄올을 주로 생산하는 Clostridium acetobutylicum이 사용된다. 본 연구에서는 이 미생물을 이용한 발효공정의 개발을 위하여, Clostridium acetobutylicum ATCC824의 대사망의 동적 모델이 제안되었다. 많은 효소기반의 대사반응들로 구성된 대사망의 복잡성과 대사반응속도식의 비선형적 특성 때문에, 유전 알고리듬과 Levenberg-Marquardt 알고리듬이 결합된 효율적인 최적화 기법을 이용하여 회분식 발효반응기의 실험 결과값으로 58개의 반응속도상수들을 결정하였다. 그리고 이 반응속도상수 결정의 정확도를 제고하기 위하여, 유전자 조작을 통해 특정 대사경로를 차단한 미생물을 이용했을 때의 실험과 초기 글루코스의 농도를 다르게 한 실험들을 수행하여 개발된 대사망의 동적모델을 분석하였다. 결과적으로, 본 연구를 통해서 개발된 대사망 모델의 정확도를 확인하였고, 이를 활용하여 발효반응공정의 생산성 향상을 위한 적절한 클로스트리듐의 개발과 발효반응기의 최적화를 위한 연구에 기여할 수 있을 것으로 기대된다.

• IMMUNE NETWORK
• /
• 제22권1호
• /
• pp.13.1-13.14
• /
• 2022

Chronic inflammation plays a critical role in the development of obesity-associated metabolic disorders such as insulin resistance. Obesity alters the microenvironment of adipose tissue and the intestines from anti-inflammatory to pro-inflammatory, which promotes low grade systemic inflammation and insulin resistance in obese mice. Various T cell subsets either help maintain metabolic homeostasis in healthy states or contribute to obesity-associated metabolic syndromes. In this review, we will discuss the T cell subsets that reside in adipose tissue and intestines and their role in the development of obesity-induced systemic inflammation.

• 한국미생물생명공학회:학술대회논문집
• /
• 한국미생물생명공학회 2004년도 Annual Meeting BioExibition International Symposium
• /
• pp.60-61
• /
• 2004

Metabolic engineering is now a well established discipline, used extensively to determine and execute rational strategies of strain development to improve the performance of micro-organisms employed in industrial fermentations. The basic principle of this approach is that performance of the microbial catalyst should be adequately characterised metabolically so as to clearlyidentify the metabolic network constraints, thereby identifying the most probable targets for genetic engineering and the extent to which improvements can be realistically achieved. In order to harness correctly this potential, it is clear that the physiological analysis of each strain studied needs to be undertaken under conditions as close as possible to the physico-chemical environment in which the strain evolves within the full-scale process. Furthermore, this analysis needs to be undertaken throughoutthe entire fermentation so as to take into account the changing environment in an essentially dynamic situation in which metabolic stress is accentuated by the microbial activity itself, leading to increasingly important stress response at a metabolic level. All too often these industrial fermentation constraints are overlooked, leading to identification of targets whose validity within the industrial context is at best limited. Thus the conceptual error is linked to experimental design rather than inadequate methodology. New tools are becoming available which open up new possibilities in metabolic engineering and the characterisation of complex metabolic networks. Traditionally metabolic analysis was targeted towards pre-identified genes and their corresponding enzymatic activities within pre-selected metabolic pathways. Those pathways not included at the onset were intrinsically removed from the network giving a fundamentally localised vision of pathway functionality. New tools from genome research extend this reductive approach so as to include the global characteristics of a given biological model which can now be seen as an integrated functional unit rather than a specific sub-group of biochemical reactions, thereby facilitating the resolution of complexnetworks whose exact composition cannot be estimated at the onset. This global overview of whole cell physiology enables new targets to be identified which would classically not have been suspected previously. Of course, as with all powerful analytical tools, post-genomic technology must be used carefully so as to avoid expensive errors. This is not always the case and the data obtained need to be examined carefully to avoid embarking on the study of artefacts due to poor understanding of cell biology. These basic developments and the underlying concepts will be illustrated with examples from the author's laboratory concerning the industrial production of commodity chemicals using a number of industrially important bacteria. The different levels of possibleinvestigation and the extent to which the data can be extrapolated will be highlighted together with the extent to which realistic yield targets can be attained. Genetic engineering strategies and the performance of the resulting strains will be examined within the context of the prevailing experimental conditions encountered in the industrial fermentor. Examples used will include the production of amino acids, vitamins and polysaccharides. In each case metabolic constraints can be identified and the extent to which performance can be enhanced predicted

• Molecules and Cells
• /
• 제40권9호
• /
• pp.685-695
• /
• 2017

Obesity and the metabolic disorders that constitute metabolic syndrome are a primary cause of morbidity and mortality in the world. Nonetheless, the changes in the proteins and the underlying molecular pathways involved in the relevant pathogenesis are poorly understood. In this study a proteomic analysis of the visceral adipose tissue isolated from metabolically healthy and unhealthy obese patients was used to identify presence of altered pathway(s) leading to metabolic dysfunction. Samples were obtained from 18 obese patients undergoing bariatric surgery and were subdivided into two groups based on the presence or absence of comorbidities as defined by the International Diabetes Federation. Two dimensional difference in-gel electrophoresis coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was carried out. A total of 28 proteins were identified with a statistically significant difference in abundance and a 1.5-fold change (ANOVA, $p{\leq}0.05$) between the groups. 11 proteins showed increased abundance while 17 proteins were decreased in the metabolically unhealthy obese compared to the healthy obese. The differentially expressed proteins belonged broadly to three functional categories: (i) protein and lipid metabolism (ii) cytoskeleton and (iii) regulation of other metabolic processes. Network analysis by Ingenuity pathway analysis identified the $NF{\kappa}B$, IRK/MAPK and PKC as the nodes with the highest connections within the connectivity map. The top network pathway identified in our protein data set related to cellular movement, hematological system development and function, and immune cell trafficking. The VAT proteome between the two groups differed substantially between the groups which could potentially be the reason for metabolic dysfunction.