Iron availability enhances the cellular energetics of aerobic Escherichia coli cultures while upregulating anaerobic respiratory chains.

Aerobic Escherichia coli growth at restricted iron concentrations (≤ 1.75 ± 0.04 µM) is characterized by lower biomass yield, higher acetate accumulation and higher activation of the siderophore iron-acquisition systems. Although iron homeostasis in E. coli has been studied intensively, previous studies focused only on understanding the regulation of the iron import systems and the iron-requiring enzymes. Here, the effect of iron availability on the energy metabolism of E. coli has been investigated. It was established that aerobic cultures growing under limiting iron conditions showed lower ATP yield per glucose, lower growth rate and lower TCA cycle activity and respiration, at the same time as increased glucose consumption, acetate and pyruvate accumulation, practically mimicking microaerobic growth. However, at excess iron, independent of oxygen availability, the cultures showed high cellular energetics (5.8 ATP/mol of glucose) by using pathways requiring iron-rich complex proteins found in the TCA cycle and respiratory chain. In conditions of iron excess, some iron-requiring terminal reductases of the respiratory chain, that were thought to function only under anaerobiosis, were used by the E. coli, when in aerobic conditions, to maintain high respiratory activity. This allowed it to produce more biomass and more reactive oxygen species that were controlled by the higher activity of the antioxidant defenses (SOD, peroxidase and catalase) and the iron-sulfur cluster repair systems.

Energy distribution of the neutron flux measurements at the Chilean Reactor RECH-1 using multi-foil neutron activation and the Expectation Maximization unfolding algorithm.

We present a methodology to obtain the energy distribution of the neutron flux of an experimental nuclear reactor, using multi-foil activation measurements and the Expectation Maximization unfolding algorithm, which is presented as an alternative to well known unfolding methods such as GRAVEL. Self-shielding flux corrections for energy bin groups were obtained using MCNP6 Monte Carlo simulations. We have made studies at the at the Dry Tube of RECH-1 obtaining fluxes of 1.5(4)×1013cm-2s-1 for the thermal neutron energy region, 1.9(5)×1012cm-2s-1 for the epithermal neutron energy region, and 4.3(11)×1011cm-2s-1 for the fast neutron energy region.

Topological analysis of carbon flux during multi-stress adaptation in Halomonas sp. AAD12

Background Osmolytes with their effective stabilizing properties are accumulated as protectants not only against salinity but also against denaturing harsh environmental stresses such as freezing, drying, high temperatures, oxygen radicals and radiation. The present work seeks to understand how Halomonas sp. AAD12 cells redirect carbon flux specifically to replenish reactions for biomass and osmolyte synthesis under changing salinity and temperature. To accomplish this goal, a combined FBA-PCA approach has been utilized. Results Experimental data were collected to supply model constraints for FBA and for the verification of the model predictions, which were satisfactory. With restrictions on the various combinations of selected anaplerotic paths (reactions catalyzed by phosphoenolpyruvate carboxylase, pyruvate carboxylase or glyoxylate shunt), two major phenotypes were found. Moreover, under high salt concentrations, when the glucose uptake rate was over 1.1 mmoL DCW- 1 h- 1, an overflow metabolism that led to the synthesis of ethanol caused a slight change in both phenotypes. Conclusions The operation of the glyoxylate shunt as the major anaplerotic pathway and the degradation of 6-phosphogluconate through the Entner-Doudoroff Pathway were the major factors in causing a distinction between the observed phenotypes.

Comparison and analysis of objective functions in flux balance analysis.

Flux balance analysis (FBA) is currently one of the most important and used techniques for estimation of metabolic reaction rates (fluxes). This mathematical approach utilizes an optimization criterion in order to select a distribution of fluxes from the feasible space delimited by the metabolic reactions and some restrictions imposed over them, assuming that cellular metabolism is in steady state. Therefore, the obtained flux distribution depends on the specific objective function used. Multiple studies have been aimed to compare distinct objective functions at given conditions, in order to determine which of those functions produces values of fluxes closer to real data when used as objective in the FBA; in other words, what is the best objective function for modeling cell metabolism at a determined environmental condition. However, these comparative studies have been designed in very dissimilar ways, and in general, several factors that can change the ideal objective function in a cellular condition have not been adequately considered. Additionally, most of them have used only one dataset for representing one condition of cell growth, and different measuring techniques have been used. For these reasons, a rigorous study on the effect of factors such as the quantity of used data, the number and type of fluxes utilized as input data, and the selected classification of growth conditions, are required in order to obtain useful conclusions for these comparative studies, allowing limiting clearly the application range on any of those results.