The terrestrial evolution of metabolism and life – by the numbers

Background  

Allometric scaling relating body mass to metabolic rate by an exponent of the former (Kleiber's Law), commonly known as quarter-power scaling (QPS), is controversial for claims made on its behalf, especially that of its universality for all life. As originally formulated, Kleiber was based upon the study of heat; metabolic rate is quantified in watts (or calories per unit time). Techniques and technology for metabolic energy measurement have been refined but the math has not. QPS is susceptible to increasing deviations from theoretical predictions to data, suggesting that there is no single, universal exponent relevant to all of life. QPS's major proponents continue to fail to make good on hints of the power of the equation for understanding aging.     

Supply-demand balance in outward-directed networks and Kleiber's law

Background  

Recent theories have attempted to derive the value of the exponent α in the allometric formula for scaling of basal metabolic rate from the properties of distribution network models for arteries and capillaries. It has recently been stated that a basic theorem relating the sum of nutrient currents to the specific nutrient uptake rate, together with a relationship claimed to be required in order to match nutrient supply to nutrient demand in 3-dimensional outward-directed networks, leads to Kleiber's law (b = 3/4).     

Application of Petri net based analysis techniques to signal transduction pathways

Background  

Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed.     

Anti‐Helicobacter pylori therapy in localized gastric mucosa‐associated lymphoid tissue lymphoma: A prospective,nationwide, multicenter study in Japan

Background

Helicobacter pylori eradication therapy was approved in Japan for the first‐line, standard treatment of H. pylori‐positive gastric mucosa‐associated lymphoid tissue (MALT) lymphoma. Although several retrospective studies or small‐scale single‐center studies have been reported, a prospective, large‐scale, nationwide, multicenter study has not been reported from Japan.

Materials and Methods

We conducted a prospective, nationwide, multicenter study to evaluate the clinical efficacy of rabeprazole‐based triple H. pylori eradication therapy for patients with localized gastric MALT lymphoma in practice‐based clinical trial. A total of 108 H. pylori‐positive patients with stage I/II₁ gastric MALT lymphoma underwent H. pylori eradication therapy. The primary endpoints were complete remission (CR) rate and the rate of transfer to secondary treatment. The secondary endpoints were CR maintenance duration and overall survival (OS).

Results

CR of lymphoma was achieved in 84 of 97 patients (86.6%), during the period 2.0‐44.7 months (median, 5.3 months) after starting H. pylori eradication treatment. CR was maintained in 77 of 81 patients (95.1%) for 0.4‐53.2 months (median, 33.1 months). Secondary treatments (radiotherapy, rituximab, or gastrectomy) for gastric MALT lymphoma were needed in 10 of the 97 patients (10.31%). During follow‐up, OS rate was 96.9% (94/97) and the causes of 3 deaths were not related to lymphoma.

Conclusions

Rabeprazole‐based H. pylori eradication therapy demonstrated a high CR rate, long CR maintenance, and a good OS for patients with localized gastric MALT lymphoma in this prospective, practice‐based, multicenter study.     

Antibacterial and antifungal activities of pyroligneous acid from wood of Eucalyptus urograndis and Mimosa tenuiflora

Aims

This work aimed to evaluate the antibacterial and antifungal activities of two types of pyroligneous acid (PA) obtained from slow pyrolysis of wood of Mimosa tenuiflora and of a hybrid of Eucalyptus urophylla × Eucalyptus grandis.

Methods and Results

Wood wedges were carbonized on a heating rate of 1·25°C min^?1 until 450°C. Pyrolysis smoke was trapped and condensed to yield liquid products. Crude pyrolysis liquids were bidistilled under 5 mmHg vacuum yielding purified PA. Multi‐antibiotic‐resistant strains of Escherichia coli, Pseudomonas aeruginosa (ATCC 27853) and Staphylococcus aureus (ATCC 25923) had their sensitivity to PA evaluated using agar diffusion test. Two yeasts were evaluated as well, Candida albicans (ATCC 10231) and Cryptococcus neoformans. GC‐MS analysis of both PAs was carried out to obtain their chemical composition. Regression analysis was performed, and models were adjusted, with diameter of inhibition halos and PA concentration (100, 50 and 20%) as parameters. Identity of regression models and equality of parameters in polynomial orthogonal equations were verified. Inhibition halos were observed in the range 15–25 mm of diameter.

Conclusions

All micro‐organisms were inhibited by both types of PA even in the lowest concentration of 20%.

Significance and Impact of the Study

The feasibility of the usage of PAs produced with wood species planted in large scale in Brazil was evident and the real potential as a basis to produce natural antibacterial and antifungal agents, with real possibility to be used in veterinary and zootechnical applications.     

Improving the <Emphasis Type="Italic">i</Emphasis>MM904 <Emphasis Type="Italic">S. cerevisiae</Emphasis> metabolic model using essentiality and synthetic lethality data

Background  

Saccharomyces cerevisiae is the first eukaryotic organism for which a multi-compartment genome-scale metabolic model was constructed. Since then a sequence of improved metabolic reconstructions for yeast has been introduced. These metabolic models have been extensively used to elucidate the organizational principles of yeast metabolism and drive yeast strain engineering strategies for targeted overproductions. They have also served as a starting point and a benchmark for the reconstruction of genome-scale metabolic models for other eukaryotic organisms. In spite of the successive improvements in the details of the described metabolic processes, even the recent yeast model (i.e., i MM904) remains significantly less predictive than the latest E. coli model (i.e., i AF1260). This is manifested by its significantly lower specificity in predicting the outcome of grow/no grow experiments in comparison to the E. coli model.     

Allometric scaling of the maximum metabolic rate of mammals: oxygen transport from the lungs to the heart is a limiting step

Background  

The maximum metabolic rate (MMR) of mammals is approximately proportional to M ^0.9 , where M is the mammal's body weight. Therefore, MMR increases with body weight faster than does the basal metabolic rate (BMR), which is approximately proportional to M ^0.7 . MMR is strongly associated with the capacity of the cardiovascular system to deliver blood to capillaries in the systemic circulation, but properties of this vascular system have not produced an explanation for the scaling of MMR.     

Modeling and simulation of the main metabolism in <Emphasis Type="Italic">Escherichia coli</Emphasis> and its several single-gene knockout mutants with experimental verification

Background  

It is quite important to simulate the metabolic changes of a cell in response to the change in culture environment and/or specific gene knockouts particularly for the purpose of application in industry. If this could be done, the cell design can be made without conducting exhaustive experiments, and one can screen out the promising candidates, proceeded by experimental verification of a select few of particular interest. Although several models have so far been proposed, most of them focus on the specific metabolic pathways. It is preferred to model the whole of the main metabolic pathways in Escherichia coli, allowing for the estimation of energy generation and cell synthesis, based on intracellular fluxes and that may be used to characterize phenotypic growth.     

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.     

OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

Background  

The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i) tracer cultivation on ¹³C substrates, (ii) ¹³C labelling analysis by mass spectrometry and (iii) mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis.     

Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

Background  

Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes.     

Genome-scale reconstruction of the metabolic network in Staphylococcus aureus N315: an initial draft to the two-dimensional annotation

Background  

Several strains of bacteria have sequenced and annotated genomes, which have been used in conjunction with biochemical and physiological data to reconstruct genome-scale metabolic networks. Such reconstruction amounts to a two-dimensional annotation of the genome. These networks have been analyzed with a constraint-based formalism and a variety of biologically meaningful results have emerged. Staphylococcus aureus is a pathogenic bacterium that has evolved resistance to many antibiotics, representing a significant health care concern. We present the first manually curated elementally and charge balanced genome-scale reconstruction and model of S. aureus' metabolic networks and compute some of its properties.     

Identification of biomarkers for genotyping <Emphasis Type="Italic">Aspergilli</Emphasis> using non-linear methods for clustering and classification

Background  

In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinantAspergillus nidulans(mutants that produce the 6- methyl salicylic acid polyketide molecule) for application in metabolic engineering.     

Using in silico models to simulate dual perturbation experiments: procedure development and interpretation of outcomes

Background  

A growing number of realistic in silico models of metabolic functions are being formulated and can serve as 'dry lab' platforms to prototype and simulate experiments before they are performed. For example, dual perturbation experiments that vary both genetic and environmental parameters can readily be simulated in silico. Genetic and environmental perturbations were applied to a cell-scale model of the human erythrocyte and subsequently investigated.     

Evolutionary patterns at the <Emphasis Type="Italic">RNase</Emphasis> based gametophytic self - incompatibility system in two divergent Rosaceae groups (Maloideae and <Emphasis Type="Italic">Prunus</Emphasis>)

Background  

Within Rosaceae, the RNase based gametophytic self-incompatibility (GSI) system has been studied at the molecular level in Maloideae and Prunus species that have been diverging for, at least, 32 million years. In order to understand RNase based GSI evolution within this family, comparative studies must be performed, using similar methodologies.     

Identification and bioinformatic analysis of the membrane proteins of synechocystis sp. PCC 6803

Background  

The membranes of Synechocystis sp. PCC 6803 play a central role in photosynthesis, respiration and other important metabolic pathways. Comprehensive identification of the membrane proteins is of importance for a better understanding of the diverse functions of its unique membrane structures. Up to date, approximately 900 known or predicted membrane proteins, consisting 24.5% of Synechocystis sp. PCC 6803 proteome, have been indentified by large-scale proteomic studies.     

The influence of the <Emphasis Type="Italic">PRKAG3</Emphasis> mutation on glycogen,enzyme activities and fibre types in different skeletal muscles of exercise trained pigs

Background  

AMP-activated protein kinase (AMPK) plays an important role in the regulation of glucose and lipid metabolism in skeletal muscle. Many pigs of Hampshire origin have a naturally occurring dominant mutation in the AMPK γ3 subunit. Pigs carrying this PRKAG3 (R225Q) mutation have, compared to non-carriers, higher muscle glycogen levels and increased oxidative capacity in m. longissimus dorsi, containing mainly type II glycolytic fibres. These metabolic changes resemble those seen when muscles adapt to an increased physical activity level. The aim was to stimulate AMPK by exercise training and study the influence of the PRKAG3 mutation on metabolic and fibre characteristics not only in m. longissimus dorsi, but also in other muscles with different functions.