Origin and evolution of operons and metabolic pathways

The emergence and evolution of metabolic pathways represented a crucial step in molecular and cellular evolution, allowing primitive organisms to become less dependent on exogenous sources of organic compounds. This work will review the main theories accounting for their assembly and for the origin and evolution of prokaryotic operons.     

Biomedical applications of cell- and tissue-specific metabolic network models

The essential goal of biomedical research is to understand the underlying mechanism of disease development. Unfortunately, achieving this goal requires expensive and time-consuming efforts in medical biotechnology. This review focuses on how context-specific genome-scale metabolic network models may facilitate reaching this goal. Such models provide an in silico framework for computational simulation of cellular metabolism, predicting the outcome of experiments. Therefore, by using these models at the initial stages of experimental design, time and cost in biomedical researches may be reduced. Furthermore, with the availability of such models, not only important pathways involved in cell dysfunction may be better understood, but also drug targets predicted based on these models can be seen as novel targets for in vivo validation. The main point of this review is that metabolic modeling can predict drug targets and biomarkers without the need for kinetics data. We provide a comprehensive review of human metabolic models and their applications, in addition to the methods used for analyzing models. We discuss how these models have been used in analyzing metabolic capabilities of different cells and tissues, in identifying disease-related metabolic pathways and biomarkers, and in understanding the human-microbe interaction.     

Effects of exposure to a simulated altitude of 5500 m on energy metabolic pathways in rats

We examined the effect of exposure to 5500 m on three closely related metabolic pathways: anaerobic glycolysis, the pentose phosphate shunt (PPS), and fatty acid metabolism. Rats were exposed to simulated altitude of 5500 m for up to 3 months. The maximal rate of lactate production in tissue homogenates, tissue lactic acid dehydrogenase and blood lactate levels were measured to evaluate the capacity for anaerobic glycolysis. The uptake of 14C-1-palmitate, oxidation of 14C-1-palmitate to 14CO2, incorporation of 14C-1-palmitate into tissue lipids, plasma and tissue free fatty acids (FFA) levels and total lipid contents were measured to assess the magnitude of lipid metabolism. Activities of glucose-6-phosphate dehydrogenase (G-6-PD) and 6-phophogluconate dehydrogenase (6-PGD) in the PPS pathway were measured to assess the capacity to generate reducing power. Acute and chronic hypoxia did not affect most of the measurements of anaerobic glycolysis, but depressed lactate production in liver and kidney. Chronic hypoxia enhanced all aspects of lipid metabolism in liver and enhanced the uptake and oxidation to CO2 of palmitate in skeletal muscle. Chronic hypoxia did not alter the activity of the G-6-PD in any tissue studied, but the activity of 6-PGD was depressed in heart, kidney, thymus and adrenal gland. The lack of major changes in the capacities of anaerobic glycolytic pathways and the activities of the PPS dehydrogenases is consistent with the maintenance of normal aerobic metabolism in rats at 5500 m. We found no evidence that anaerobic metabolic processes were upregulated to sustain energy consumption during chronic hypoxia. On the other hand, enhanced fatty acid metabolism may spare carbohydrate for metabolic fuel under conditions of extreme hypoxic limitation.     

Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02

We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02.     

Associations among work‐related stress,cortisol, inflammation,and metabolic syndrome

This cross‐sectional study examined the relationship between work‐related stress, cortisol, and C‐reactive protein (CRP) in predicting metabolic syndrome (MtS). Self‐reported work stress measured by the effort reward imbalance ratio (ERI), anthropometric data, CRP, and saliva cortisol were collected from 204 healthy Jordanian male workers. ERI and cortisol were significantly associated with the presence of MtS (OR = 4.74, 95% CI: 2.13–10.55; OR = 3.03, 95% CI: 2.08–4.40; OR = 11.50, 95% CI: 2.16–59.14, respectively). The odds of MtS in men with high ERI and high cortisol were significantly higher than that of men with low ERI and low cortisol (OR = 11.50, 95% CI: 2.16–59.14). CRP was significantly associated with MtS (OR = 2.51, 95% CI: 1.50–4.20). The odds of MtS were significantly higher in centrally obese men with both high ERI and CRP level. Thus, high ERI along with high cortisol or high CRP increases the risk for MtS, especially among centrally obese men.     

Prediction of metabolic syndrome using artificial neural network system based on clinical data including insulin resistance index and serum adiponectin

Objective

This study aimed to predict the 6-year incidence of metabolic syndrome (MetS) using an artificial neural network (ANN) system and multiple logistic regression (MLR) analysis based on clinical factors, including the insulin resistance index calculated by homeostasis model assessment (HOMA-IR).

Design

Subjects were recruited from participants in annual health check-ups in both 2000 and 2006. A total of 410 Japanese male teachers and other workers at Keio University, 30–59 years of age at baseline, participated in this retrospective cohort study.

Measurements

Clinical parameters were randomly divided into a training dataset and a validation dataset, and the ANN system and MLR analysis were applied to predict individual incidences. The leave some out cross validation method was used for validation.

Results

The sensitivity of the prediction was 0.27 for the MLR model and 0.93 for the ANN system, while specificities were 0.95 and 0.91, respectively. Sensitivity analysis employing the ANN system identified BMI, age, diastolic blood pressure, HDL-cholesterol, LDL-cholesterol and HOMA-IR as important predictors, suggesting these factors to be non-linearly related to the outcome.

Conclusion

We successfully predicted the 6-year incidence of MetS using an ANN system based on clinical data, including HOMA-IR and serum adiponectin, in Japanese male subjects.     

Measurement of endothelial metabolic functions in vivo

Lung metabolic functions include the interaction of microvascular endothelium with blood-borne substances such as physiologically important amine, eicosanoid, and peptide hormones and drugs. This activity is mediated by endothelial transport systems and enzymes which either synthesize or degrade these substances. Because they can alter the hormone content of aortic blood, these functions play a role in homeostasis, and their disturbance has been implicated in the pathogenesis of several forms of lung injury and disease. Both steady-state infusion and single injection, multiple indicator dilution techniques have been applied to measure endothelial metabolic functions in the intact lung. Considerable progress has been made in development of mathematical models for the processes, and their application has been tested both under normal conditions and also when the lung is perturbed experimentally. Unique experimental challenges are presented by measurement of metabolic functions in vivo, when steadystate infusion techniques cannot be used because systemic toxicity could result. In this case, the bolus injection approach has been used, with some success, both in laboratory animals and man. Although major challenges remain, their solution is essential if we are to apply knowledge of endothelial cell function in vitro to understanding lung microvascular physiology and pathophysiology in the intact animal.     

Adequacy of measurements in compartmental modelling of metabolic systems

The adequacy of present-day measurement techniques for the compartmental modelling of metabolic systems is investigated using numerical examples and analysis of experimentally-obtained plasma clearance curves. It is concluded that the model parameters obtained are often of questionable accuracy. The situation can be improved by careful monitoring of experimental conditions and judicious spacing of data points on the response curve, but the work shows a clear need for a continuous (or semicontinuous) method of monitoring plasma concentration. To resolve ambiguities between models equally plausible on physiological grounds, it is necessary to monitor the dynamics of internal variables, for example, of the concentration in the liver (which is nowadays possible noninvasively).     

Association of COVID-19 with hepatic metabolic dysfunction

The coronavirus disease 2019 (COVID-19) pandemic continues to be a global problem with over 438 million cases reported so far. Although it mostly affects the respiratory system, the involvement of extrapulmonary organs, including the liver, is not uncommon. Since the beginning of the pandemic, metabolic com-orbidities, such as obesity, diabetes, hypertension, and dyslipidemia, have been identified as poor prognostic indicators. Subsequent metabolic and lipidomic studies have identified several metabolic dysfunctions in patients with COVID-19. The metabolic alterations appear to be linked to the course of the disease and inflammatory reaction in the body. The liver is an important organ with high metabolic activity, and a significant proportion of COVID-19 patients have metabolic comorbidities; thus, this factor could play a key role in orchestrating systemic metabolic changes during infection. Evidence suggests that metabolic dysregulation in COVID-19 has both short- and long-term metabolic implications. Furthermore, COVID-19 has adverse associations with metabolic-associated fatty liver disease. Due to the ensuing effects on the renin-angiotensin-aldosterone system and ammonia metabolism, COVID-19 can have significant implications in patients with advanced chronic liver disease. A thorough understanding of COVID-19-associated metabolic dysfunction could lead to the identification of important plasma biomarkers and novel treatment targets. In this review, we discuss the current understanding of metabolic dysfunction in COVID-19, focusing on the liver and exploring the underlying mechanistic pathogenesis and clinical implications.     

Obesity and the metabolic syndrome in Korean adolescents

This study evaluated the prevalence of metabolic syndrome and investigated its association with being overweight in Korean adolescents. Data were obtained from 1,393 students between 12 and 13 yr of age in a cross-sectional survey. We defined the metabolic syndrome using criteria analogous to the Third Report of the Adult Treatment Panel (ATP III) as having at least three of the following: fasting triglycerides > or =100 mg/dL; HDL <50 mg/dL; fasting glucose > or =110 mg/dL; waist circumference >75th percentile for age and gender; and systolic blood pressure >90th percentile for age, gender, and height. Weight status was assessed using the age- and gender-specific body mass index (BMI), and a BMI > or =85th percentile was classified as overweight. Of the adolescents, 5.5% met the criteria for the metabolic syndrome, and the prevalence increased with weight status; it was 1.6% for normal weight and 22.3% in overweight (p<0.001). In multivariate logistic regression analyses among adolescents, overweight status was independently associated with the metabolic syndrome (odds ratio, 17.7; 95% confidence interval, 10.0-31.2). Since childhood metabolic syndrome and obesity likely persist into adulthood, early identification helps target interventions to improve future cardiovascular health.     

An evolutionary approach for searching metabolic pathways

Searching metabolic pathways that relate two compounds is a common task in bioinformatics. This is of particular interest when trying, for example, to discover metabolic relations among compounds clustered with a data mining technique. Search strategies find sequences to relate two or more states (compounds) using an appropriate set of transitions (reactions). Evolutionary algorithms carry out the search guided by a fitness function and explore multiple candidate solutions using stochastic operators. In this work we propose an evolutionary algorithm for searching metabolic pathways between two compounds. The operators and fitness function employed are described and the effect of mutation rate is studied. Performance of this algorithm is compared with two classical search strategies. Source code and dataset are available at http://sourceforge.net/projects/sourcesinc/files/eamp/     

Shared genetic variance between the features of the metabolic syndrome: heritability studies

Heritability estimates of MetS range from approximately 10%-30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation in common, by reviewing the literature regarding genetic correlation coefficients. Identification of features, that have much genetic variation in common, may eventually facilitate the search for pleitropic genetic variants that may explain the clustering of MetS features.A PubMed search with the search terms “(metabolic syndrome OR insulin resistance syndrome) and (heritability OR genetic correlation OR pleiotropy)” was performed. Studies published before 7th July 2011, which presented genetic correlation coefficients between the different MetS features and genetic correlation coefficients of MetS and its features with adipose tissue-, pro-inflammatory and pro-thrombotic biomarkers were included.Nine twin and 19 family studies were included in the review. Genetic correlations varied, but were strongest between waist circumference and HOMA-IR (r²: 0.36 to 0.79, median: 0.50), HDL cholesterol and triglycerides (r²: − 0.05 to − 0.59, median − 0.45), adiponectin and MetS (r²: − 0.32 to − 0.43; median − 0.38), adiponectin and insulin (r²: − 0.10 to − 0.60; median − 0.30) and between adiponectin and HDL-cholesterol (r²: − 0.22 to − 0.51, median − 0.29).In conclusion, heritability studies suggest that genetic pleiotropy exist especially between certain MetS features, as well as between MetS and adiponectin. Further research on actual genetic variants responsible for the genetic pleiotropy of these combinations will provide more insight into the etiology of MetS.     

果糖与代谢性疾病

<正>随着社会经济的发展,肥胖、糖尿病、脂肪肝、高血脂和痛风等代谢性疾病的患病率在全球呈现快速上升趋势。这些代谢性疾病可进一步发展为动脉粥样硬化、高血压和冠心病等心血管疾病或肾脏疾病,严重危害人们的身心健康和社会发展。因此,代谢性疾病及其相关心血管疾病已经成为我国公共卫生领域的重大挑战。     

The association of breast arterial calcification and metabolic syndrome

OBJECTIVES:We investigated the relationship between metabolic syndrome and breast arterial calcification detected via mammography in a cohort of postmenopausal subjects.METHODS:Among 837 patients referred to our radiology department for mammographic screening, 310 postmenopausal females (105 patients with and 205 patients without breast arterial calcification) aged 40 to 73 (mean 55.9±8.4) years were included in this study. The groups were compared with respect to clinical characteristics and metabolic syndrome criteria. Univariate and multivariate analyses identified the factors related to breast arterial calcification.RESULTS:Age, postmenopausal duration and the frequencies of diabetes mellitus, hypertension and metabolic syndrome were significantly higher in the subjects with breast arterial calcification than in those without (p<0.05). Multivariate analysis indicated that age (OR = 1.3, 95% CI = 1.1–1.6, p = 0.001) and metabolic syndrome (OR = 4.0, 95% CI = 1.5−10.4, p = 0.005) were independent predictors of breast arterial calcification detected via mammography. The independent predictors among the features of metabolic syndrome were low levels of high-density lipoproteins (OR = 8.1, 95% CI = 1.0−64.0, p = 0.047) and high blood pressure (OR = 8.7, 95% CI = 1.5−49.7, p = 0.014).CONCLUSIONS:The likelihood of mammographic detection of breast arterial calcification increases with age and in the presence of hypertension or metabolic syndrome. For patients undergoing screening mammography who present with breast arterial calcification, the possibility of metabolic syndrome should be considered. These patients should be informed of their cardiovascular risk factors and counseled on appropriate lifestyle changes.     

Carcinoembryonic antigen level can be overestimated in metabolic syndrome

Carcinoembryonic antigen (CEA) levels can be affected by many factors and metabolic syndrome is also a candidate. This study examined the relationship between CEA levels and metabolic syndrome using the data of 32,897 healthy Koreans. Fecal occult blood tests were also performed. Subjects with colorectal carcinoma were excluded. Subjects were classified by their smoking status, metabolic syndrome and its components. Prevalence of metabolic syndrome and its all components showed a significant increase according to the quartile of serum CEA concentration (P < 0.001). Increased numbers of metabolic syndrome components showed a positive association with CEA levels (P-trend < 0.001). The odds ratios for the highest CEA quartile vs the lowest serum CEA quartile significantly increased in the presence of metabolic syndrome and its components. After adjusting for age, gender and smoking status, metabolic syndrome, low high density lipoprotein cholesterol and elevated blood pressure had higher odds ratios (OR) of the highest CEA quartile compared with the lowest serum CEA quartile (OR = 1.125, 95% CI = 1.030 to 1.222, P = 0.009; OR = 1.296, 95% CI = 1.195 to 1.405, P < 0.001; OR = 1.334, 95% CI = 1.229 to 1.448, P < 0.001, respectively). These results indicate that metabolic syndrome is associated with CEA value, which may lead to a misunderstanding of the CEA levels.     

非酒精性脂肪性肝病与代谢综合征的关系研究

目的:探讨非酒精性脂肪性肝病患病与代谢综合征的关系。方法:采用横断面调查研究方法,分析810例健康体检者的体重指数、血压、总胆固醇、甘油三酯、空腹血糖和肝脏超声检查相关临床资料。结果:非酒精性脂肪性肝病组中体重指数、血压、总胆固醇、甘油三酯和空腹血糖水平均明显高于对照组(P0.01);多因素Logistic回归分析结果显示,代谢综合征各组分中体重指数、甘油三酯、空腹血糖及舒张压升高是非酒精性脂肪性肝病发病的独立危险因子(P0.05)。结论:非酒精性脂肪性肝病患病与代谢综合征密切相关。     

Serum calcium level is associated with metabolic syndrome in elderly women

Objective

To investigate the association between serum calcium level and metabolic syndrome, defined using the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) definition, in Korean elderly women.

Study design

We conducted a cross-sectional study of 1941 elderly women (mean age: 65.16 ± 4.58 years) who participated in annual health examinations at Korea university Medical Center between January 1, 2006 and December 31, 2009 and had normal serum calcium levels.

Results

Women with metabolic syndrome had higher serum calcium levels than those without metabolic syndrome (9.26 ± 0.35 vs. 9.20 ± 0.33, P < 0.001). In multiple logistic regression analysis, serum calcium level within normal range was positively associated with the risk of having metabolic syndrome (odds ratio 2.12, 95% confidence interval 1.50–2.98). With regard to components of metabolic syndrome, serum calcium level was also positively associated with the risk of having high triglyceride, and high glucose, whereas it was inversely associated with the risk of having low high density lipoprotein. However, there was no association of serum calcium level with abdominal obesity or high blood pressure.

Conclusions

The higher was the level of calcium within normal range, the greater were the odds of metabolic syndrome in healthy and elderly women. Prospective studies are needed to investigate the role of calcium in the development of metabolic syndrome in the future.     

Predicting metabolic cost of level walking

Summary Energy expenditure in walking is usually expressed as a function of walking speed. However, this relationship applies only to freely adopted step length-step rate patterns. Both the step length and the step rate must be used to predict the energy expenditure for any combination of step length and step rate. Evidence on seven subjects indicates that the energy demand for such a combination can be determined by conducting two experiments. In the first, the subject is allowed to freely choose his own walking pattern to achieve a set of prescribed speeds. In the second, the speed is kept constant but the subject is forced to adopt a range of prescribed step rates. The results of the two experiments combined yield enough data to make possible the determination of the energy equation of the pattern, encompassing both free and forced gaits. Results show that the freely chosen step rate requires the least oxygen consumption at any given speed. Any other forced step rate at the same speed increases the oxygen cost over that required for the free step rate.