NMR study of rat diaphragm exposed to metabolic and compensated metabolic acidosis

When exposed to hypercapnia, several muscles deteriorate with respect to their mechanical performance. Exposure to metabolic acidosis and, perhaps surprisingly, to compensated metabolic acidosis has the same effect on the diaphragm. The mechanisms involved in these effects remain unclear. If the diaphragmatic intracellular pH (pHi) is assumed to decrease with hypercapnia, to remain unchanged during metabolic acidosis, and to increase during compensated metabolic acidosis, it would appear that different mechanisms must be responsible for the depreciation in the diaphragm's mechanical performance. The present experiments using 31P nuclear magnetic resonance (31P-NMR) spectroscopy were undertaken to determine the effect of metabolic acidosis and compensated metabolic acidosis on pHi and on high-energy phosphate metabolites in the resting rat diaphragm. A whole diaphragm was slightly stretched while being stitched onto a fiberglass mesh. The area approximated that at functional residual capacity. It was superfused in the NMR sample tube with a phosphate-free Krebs-Ringer bicarbonate solution [( HCO3-] = 6 meqO equilibrated with either 95% O2-5% CO2 or 98.75% O2-1.25% CO2). Spectra were acquired during 15-min intervals for control (30 min of normal Krebs-Ringer bicarbonate superfusate, equilibrated with 95% O2-5% CO2), for 120 min of exposure to either form of acidosis and for 60 min of recovery with normal superfusate. The pHi decreased rapidly during metabolic acidosis but did not change significantly during compensated metabolic acidosis. In both forms of acidosis, phosphocreatine declined gradually but not significantly, whereas ATP and inorganic phosphate did not change at all. The results suggest that HCO3- passes freely through the diaphragmatic sarcolemma, very much like the cardiac sarcolemma.(ABSTRACT TRUNCATED AT 250 WORDS)     

Comparison of metabolic states using genome-scale metabolic models

Genome-scale metabolic models (GEMs) are comprehensive knowledge bases of cellular metabolism and serve as mathematical tools for studying biological phenotypes and metabolic states or conditions in various organisms and cell types. Given the sheer size and complexity of human metabolism, selecting parameters for existing analysis methods such as metabolic objective functions and model constraints is not straightforward in human GEMs. In particular, comparing several conditions in large GEMs to identify condition- or disease-specific metabolic features is challenging. In this study, we showcase a scalable, model-driven approach for an in-depth investigation and comparison of metabolic states in large GEMs which enables identifying the underlying functional differences. Using a combination of flux space sampling and network analysis, our approach enables extraction and visualisation of metabolically distinct network modules. Importantly, it does not rely on known or assumed objective functions. We apply this novel approach to extract the biochemical differences in adipocytes arising due to unlimited vs blocked uptake of branched-chain amino acids (BCAAs, considered as biomarkers in obesity) using a human adipocyte GEM (iAdipocytes1809). The biological significance of our approach is corroborated by literature reports confirming our identified metabolic processes (TCA cycle and Fatty acid metabolism) to be functionally related to BCAA metabolism. Additionally, our analysis predicts a specific altered uptake and secretion profile indicating a compensation for the unavailability of BCAAs. Taken together, our approach facilitates determining functional differences between any metabolic conditions of interest by offering a versatile platform for analysing and comparing flux spaces of large metabolic networks.     

Algebraic comparison of metabolic networks, phylogenetic inference, and metabolic innovation

Background  

Comparison of metabolic networks is typically performed based on the organisms' enzyme contents. This approach disregards functional replacements as well as orthologies that are misannotated. Direct comparison of the structure of metabolic networks can circumvent these problems.     

Glial perspectives of metabolic states during cerebral hypoxia--calcium regulation and metabolic energy

Cooperation between astrocytes and neurons is a unique interaction between two highly specialized cell types of the brain. Therefore, lack of nutrient supply during ischemia requires tight coordination of metabolism between astrocytes and neurons to keep the brain functions intact. To understand the impact of energy limitation on astrocytes, the functions of astrocytes have to be considered: (i) supplementation of neuronal cells, (ii) modulation of the extracellular milieu, mainly of the glutamate level, and (iii) elimination of reactive oxygen species (ROS). In cultured astrocytes and neurons inhibition of oxidative phosphorylation, using rotenone, was tested. Interestingly, this had only a negligible effect on Ca2+ homeostasis in astrocytes, even in combination with a severe glutamate stress. In contrast, in neurons glutamate in the presence of rotenone induced Ca2+ deregulation. Ca2+ homeostasis is very critical for cell survival. A massive and prolonged Ca2+ rise will lead to deregulation of many processes in such a way that the cells affected can hardly survive. Ca2+ homeostasis depends on the energy-consuming processes, which maintain the steep gradient between intracellular and extracellular Ca2+ concentration. Deprivation of oxygen and glucose during ischemia leads to a depletion of ATP in the brain, due to inhibited glycolytic and mitochondrial activity, whereas energy-consuming processes like ion pumps drain the ATP pools. On the other hand, specific mechanisms can protect brain structures against the massive insult of ischemia. Glycogen, stored in astrocytes, can maintain both neurons and astrocytes alive during short limitation of oxygen and glucose. Moreover, astrocytes can fuel ATP generation by providing lactate for neurons.     

Leptin and metabolic syndrome

Obesity is characterized by increased concentration of leptin and disturbance of the feedback between hyperleptinaemia and enhanced appetite. The hyperleptinaemia is often combined with hyperglycaemia and arterial hypertension and seems to be a predictor of acute cardiovascular events. Leptin inhibitors might be used in the future for therapy in case of the metabolic syndrome.     

Thioredoxin and metabolic regulation

The regulatory function of thioredoxin, discovered in studies on carbon dioxide assimilation in photosynthesis, was extended to enzymes of related biosynthetic reactions of chloroplasts early on. More recently, thioredoxin was found to perform a range of regulatory functions—from the germination of seeds to the division and development of animal cells. The renaissance in knowledge relating to its activity suggests that thioredoxin will, on the hand, emerge as a principal regulator of fundamental processes in the major forms of life and, on the other, find application in technology and medicine.     

The hierarchical structure of metabolic networks and the construction of efficient metabolic simulators

Methods are presented for the efficient simulation of large scale metabolic networks based upon the hierarchical structure of such networks and the formation of steady-state aggregations. The methods are dynamic and result in a varying time scale which is always consonant with the response of the network. An algorithm for the generation of reduced equivalent networks is presented. Problems of accuracy and stability are discussed. Special methods such as cascading and telescoping are presented for speeding the solution of the steady-state aggregations.     

Nutrition and metabolic development

Perinatal changes in metabolic processes owing to a change from a high carbohydrate to a high fat (milk) diet at birth are described. It is pointed out that early changes in food composition may have permanent effects and it is suggested that, in the rat, this may be due to structural alterations in the brain at a time when it is still differentiating. Such changes are irreversible.     

Diet and metabolic development

For many years, investigators have been concerned with mechanisms that control and alter genetically regulated development. An intriguing aspect of these mechanisms is the ability of environmental factors to induce certain metabolic processes. Animal studies have shown that dietary manipulation of cholesterol and fatty acid metabolism during development can have persistent and permanent effects. In addition, there appears to be a critical period when changes in the diet can have lasting consequences. The changes in the control exerted by nutritional factors on metabolic development coincide with three phases of development: prenatal, suckling, and weaning. The effects of diet on cholesterol and fatty acid metabolism throughout these three phases of development will be addressed in this review.     

Shiftwork and metabolic dysfunction

Many of the health problems that are more prevalent among shiftworkers are thought to be linked to their heightened susceptibility to metabolic syndrome, i.e., the association of even moderate degrees of visceral obesity, dyslipidemia, abnormal blood pressure, and serum glucose levels in the same individual. Although previous studies have identified associations between shiftwork and metabolic syndrome, there is relatively little evidence to date of how the risk of developing it varies as a function of exposure to shiftwork. The current study seeks to confirm earlier findings of an association between shiftwork exposure and metabolic dysfunction, and to examine the impact of exposure duration, while adjusting for a number of covariates in the analyses. The analyses were based on data from VISAT, a study involving the measurement of physiological, behavioral, and subjective outcomes from 1757 participants, 989 being current or former shiftworkers. The sample comprised employed and retired wage earners, male and female, who were 32, 42, 52, and 62 yrs old. The first analysis sought to confirm previous findings of an association between exposure to shiftwork and the risk of developing metabolic syndrome. It indicated that participants who were or who had previously been shiftworkers (i.e., working schedules that involved rotating shifts; not being able to go to bed before midnight; having to get up before 05:00 h; or being prevented from sleeping during the night) were more likely to exhibit symptoms of metabolic syndrome, after adjusting for age, sex, socioeconomic status, smoking, alcohol intake, perceived stress, and sleep difficulty (odds ratio [OR] 1.78; 95% confidence interval [CI] 1.03-3.08). The results suggest the association between shiftwork and metabolic syndrome cannot be fully accounted for by either higher levels of strain or increased sleep difficulty among shiftworkers, although it remains a possibility that either one or both of these factors may have played a contributing role. The second analysis addressed the issue of duration of exposure to shiftwork. Participants with >10 yrs' experience of working rotating shifts were more likely to exhibit symptoms of metabolic syndrome than participants without exposure to shiftwork, i.e., dayworkers, even after adjusting for age and sex (OR 1.96; 95% CI 1.03-3.75). Thus, the current study confirms the association between shiftwork exposure and metabolic syndrome. It also provides new information regarding the time course of the development of the illness as function of exposure duration, although this was only examined in relation to rotating shiftwork. It is concluded that those responsible for monitoring workers' health should pay particular attention to indices of metabolic dysfunction in workers who have been exposed to shiftwork for >10 yrs.     

OptORF: Optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains

Background  

Computational modeling and analysis of metabolic networks has been successful in metabolic engineering of microbial strains for valuable biochemical production. Limitations of currently available computational methods for metabolic engineering are that they are often based on reaction deletions rather than gene deletions and do not consider the regulatory networks that control metabolism. Due to the presence of multi-functional enzymes and isozymes, computational designs based on reaction deletions can sometimes result in strategies that are genetically complicated or infeasible. Additionally, strains might not be able to grow initially due to regulatory restrictions. To overcome these limitations, we have developed a new approach (OptORF) for identifying metabolic engineering strategies based on gene deletion and overexpression.     

Butanol production from renewable biomass: rediscovery of metabolic pathways and metabolic engineering

Biofuel from renewable biomass is one of the answers to help solve the problems associated with limited fossil resources and climate change. Butanol has superior liquid-fuel characteristics, with similar properties to gasoline, and thus, has the potential to be used as a substitute for gasoline. Clostridia are recognized as a good butanol producers and are employed in the industrial-scale production of solvents. Due to the difficulty of performing genetic manipulations on clostridia, however, strain improvement has been rather slow. Furthermore, complex metabolic characteristics of acidogenesis followed by solventogenesis in this strain have hampered the development of engineered clostridia strains with highly efficient and selective butanol-production capabilities. In recent years, the butanol-producing characteristics in clostridia have been further characterized and alternative pathways discovered. More recently, systems-level metabolic engineering approaches were taken to develop superior strains. Herein, we review recent discoveries of metabolic pathways for butanol production and the metabolic engineering strategies being developed.     

MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis

SUMMARY: MetaFluxNet is a program package for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes in an interactive and customized way. It allows users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications. As a result, quantitative in silico simulations of metabolic pathways can be carried out to understand the metabolic status and to design the metabolic engineering strategies. The main features of the program include a well-developed model construction environment, user-friendly interface for metabolic flux analysis (MFA), comparative MFA of strains having different genotypes under various environmental conditions, and automated pathway layout creation. AVAILABILITY: http://mbel.kaist.ac.kr/ Supplementary information: A manual for MetaFluxNet is available as PDF file.