• Journal of Microbiology and Biotechnology
• /
• 제19권1호
• /
• pp.23-36
• /
• 2009

In the present work, the metabolic network of primary metabolism of the slow-growing myxobacterium Sorangium cellulosum was reconstructed from the annotated genome sequence of the type strain So ce56. During growth on glucose as the carbon source and asparagine as the nitrogen source, So ce56 showed a very low growth rate of $0.23\;d^{-1}$, equivalent to a doubling time of 3 days. Based on a complete stoichiometric and isotopomer model of the central metabolism, $^{13}C$ metabolic flux analysis was carried out for growth with glucose as carbon and asparagine as nitrogen sources. Normalized to the uptake flux for glucose (100%), cells recruited glycolysis (51%) and the pentose phosphate pathway (48%) as major catabolic pathways. The Entner-Doudoroff pathway and glyoxylate shunt were not active. A high flux through the TCA cycle (118%) enabled a strong formation of ATP, but cells revealed a rather low yield for biomass. Inspection of fluxes linked to energy metabolism revealed that S. cellulosum utilized only 10% of the ATP formed for growth, whereas 90% is required for maintenance. This explains the apparent discrepancy between the relatively low biomass yield and the high flux through the energy-delivering TCA cycle. The total flux of NADPH supply (216%) was higher than the demand for anabolism (156%), indicating additional reactions for balancing of NADPH. The cells further exhibited a highly active metabolic cycle, interconverting $C_3$ and $C_4$ metabolites of glycolysis and the TCA cycle. The present work provides the first insight into fluxes of the primary metabolism of myxobacteria, especially for future investigation on the supply of cofactors, building blocks, and energy in myxobacteria, producing natural compounds of biotechnological interest.

• Journal of Microbiology and Biotechnology
• /
• 제33권10호
• /
• pp.1351-1360
• /
• 2023

Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.

• Journal of Microbiology and Biotechnology
• /
• 제19권11호
• /
• pp.1301-1305
• /
• 2009

The evolution of living organisms occurs via a combination of highly complicated processes that involve modification of various features such as appearance, metabolism and sensing systems. To understand the evolution of life, it is necessary to understand how each biological feature has been optimized in response to new environmental conditions and interrelated with other features through evolution. To accomplish this, we constructed contents-based trees for a two-component system (TCS) and metabolic network to determine how the environmental communication mechanism and the intracellular metabolism have evolved, respectively. We then conducted a comparative analysis of the two trees using ARACNE to evaluate the evolutionary and functional relationship between TCS and metabolism. The results showed that such integrated analysis can give new insight into the study of bacterial evolution.

• Journal of Microbiology and Biotechnology
• /
• 제11권3호
• /
• pp.384-388
• /
• 2001

The metabolic pathway synthesis algorithm was applied to estimate the maximum ethanol yield from xylose in a model recombinant Saccharomyces cerevisiae strain containing the genes involved in xylose metabolism. The stoichiometrically independent pathways were identified by constructing a biochemical reaction network for conversion of xylose to ethanol in the recombinant S. cerevisiae. Two independent pathways were obtained in xylose-assimilating recombinant S. cerevisiae as opposed to six independent pathways for conversion of glucose to ethanol. The maximum ethanol yield from xylose was estimated to be 0.46 g/g, which was lower than the known value of 0.51 g/g for glucose-fermenting and wild-type xylose-fermenting yeasts.

• IMMUNE NETWORK
• /
• 제23권1호
• /
• pp.9.1-9.15
• /
• 2023

Cancer immunotherapies continue to face numerous obstacles in the successful treatment of solid malignancies. While immunotherapy has emerged as an extremely effective treatment option for hematologic malignancies, it is largely ineffective against solid tumors due in part to metabolic challenges present in the tumor microenvironment (TME). Tumor-infiltrating CD8⁺ T cells face fierce competition with cancer cells for limited nutrients. The strong metabolic suppression in the TME often leads to impaired T-cell recruitment to the tumor site and hyporesponsive effector functions via T-cell exhaustion. Growing evidence suggests that mitochondria play a key role in CD8⁺ T-cell activation, migration, effector functions, and persistence in tumors. Therefore, targeting the mitochondrial metabolism of adoptively transferred T cells has the potential to greatly improve the effectiveness of cancer immunotherapies in treating solid malignancies.

• Journal of Ginseng Research
• /
• 제47권2호
• /
• pp.302-310
• /
• 2023

Background: The most common type of dementia, Alzheimer's disease (AD), is marked by the formation of extracellular amyloid beta (Aβ) plaques. The impairments of axons and synapses appear in the process of Aβ plaques formation, and this damage could cause neurodegeneration. We previously reported that non-saponin fraction with rich polysaccharide (NFP) from Korean Red Ginseng (KRG) showed neuroprotective effects in AD. However, precise molecular mechanism of the therapeutic effects of NFP from KRG in AD still remains elusive. Methods: To investigate the therapeutic mechanisms of NFP from KRG on AD, we conducted proteomic analysis for frontal cortex from vehicle-treated wild-type, vehicle-treated 5XFAD mice, and NFP-treated 5XFAD mice by using nano-LC-ESI-MS/MS. Metabolic network analysis was additionally performed as the effects of NFP appeared to be associated with metabolism according to the proteome analysis. Results: Starting from 5,470 proteins, 2,636 proteins were selected for hierarchical clustering analysis, and finally 111 proteins were further selected for protein-protein interaction network analysis. A series of these analyses revealed that proteins associated with synapse and mitochondria might be linked to the therapeutic mechanism of NFP. Subsequent metabolic network analysis via genome-scale metabolic models that represent the three mouse groups showed that there were significant changes in metabolic fluxes of mitochondrial carnitine shuttle pathway and mitochondrial beta-oxidation of polyunsaturated fatty acids. Conclusion: Our results suggested that the therapeutic effects of NFP on AD were associated with synaptic- and mitochondrial-related pathways, and they provided targets for further rigorous studies on precise understanding of the molecular mechanism of NFP.

• BMB Reports
• /
• 제54권6호
• /
• pp.323-328
• /
• 2021

Periodontal diseases have been reported to have a multidirectional association with metabolic disorders. We sought to investigate the correlation between periodontitis and diabetes or fatty liver disease using HFD-fed obese mice inoculated with P. gingivalis. Body weight, alveolar bone loss, serological biochemistry, and glucose level were determined to evaluate the pathophysiology of periodontitis and diabetes. For the evaluation of fatty liver disease, hepatic nonalcoholic steatohepatitis (NASH) was assessed by scoring steatosis, inflammation, hepatocyte ballooning and the crucial signaling pathways involved in liver metabolism were analyzed. The C-reactive protein (CRP) level and NASH score in P. gingivalis-infected obese mice were significantly elevated. Particularly, the extensive lobular inflammation was observed in the liver of obese mice infected with P. gingivalis. Moreover, the expression of metabolic regulatory factors, including peroxisome proliferator-activated receptor γ (Pparγ) and the fatty acid transporter Cd36, was up-regulated in the liver of P. gingivalis-infected obese mice. However, inoculation of P. gingivalis had no significant influence on glucose homeostasis, insulin resistance, and hepatic mTOR/AMPK signaling. In conclusion, our results indicate that P. gingivalis can induce the progression of fatty liver disease in HFD-fed mice through the upregulation of CD36-PPARγ axis.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권10호
• /
• pp.1266-1275
• /
• 2004

'생물정보학'이란 생물학적 데이타를 처리, 가공하여 정보를 얻어내는 연구 분야로 이 중 대사 체학은 대사 경로 네트워크를 가시화하여 생명 활동을 이해하고자 하는 분야로, 대사 경로 내의 흐름을 한 눈에 알 수 있도록 가시화하여 보여 줄 수 있는 도구가 반드시 필요하다. 따라서 본 논문에서는 새로운 '대사 경로 드로잉 알고리즘'을 제안하였다. 대사 경로 그래프의 구조로는 이분 그래프를 이용하여 가독성을 높였으며, 이 그래프가 척도 없는(scale-free) 네트워크 구조라는 것과 구조적으로 환형, 계층적, 선형 컴포넌트를 가진다는 것을 고려하여 사이즈가 큰 그래프도 적절하게 드로잉 하도록 하였다.

• BMB Reports
• /
• 제41권8호
• /
• pp.609-614
• /
• 2008

The concentrations and catalytic activities of enzymes control metabolic rates. Previous studies have focused on enzyme concentrations because there are no genome-wide techniques used for the measurement of enzyme activity. We propose a method for evaluating the significance of enzyme activity by integrating metabolic network topologies and genome-wide microarray gene expression profiles. We quantified the enzymatic activity of reactions and report the 388 significant reactions in five perturbation datasets. For the 388 enzymatic reactions, we identified 70 that were significantly regulated (P-value < 0.001). Thirty-one of these reactions were part of anaerobic metabolism, 23 were part of low-pH aerobic metabolism, 8 were part of high-pH anaerobic metabolism, 3 were part of low-pH aerobic reactions, and 5 were part of high-pH anaerobic metabolism.

• Journal of Microbiology and Biotechnology
• /
• 제31권4호
• /
• pp.621-629
• /
• 2021

Shigella flexneri is a facultative intracellular pathogen that causes bacillary dysentery in humans. Infection with S. flexneri can result in more than a million deaths yearly and most of the victims are children in developing countries. Therefore, identifying novel and unique drug targets against this pathogen is instrumental to overcome the problem of drug resistance to the antibiotics given to patients as the current therapy. In this study, a comparative analysis of the metabolic pathways of the host and pathogen was performed to identify this pathogen's essential enzymes for the survival and propose potential drug targets. First, we extracted the metabolic pathways of the host, Homo sapiens, and pathogen, S. flexneri, from the KEGG database. Next, we manually compared the pathways to categorize those that were exclusive to the pathogen. Further, all enzymes for the 26 unique pathways were extracted and submitted to the Geptop tool to identify essential enzymes for further screening in determining the feasibility of the therapeutic targets that were predicted and analyzed using PPI network analysis, subcellular localization, druggability testing, gene ontology and epitope mapping. Using these various criteria, we narrowed it down to prioritize 5 novel drug targets against S. flexneri and one vaccine drug targets against all strains of Shigella. Hence, we suggest the identified enzymes as the best putative drug targets for the effective treatment of S. flexneri.