3 resultados para anaerobic strain


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Desulfovibrio desulfuricans was the first species of a sulphatereducing bacterium to be isolated, in 1895. Since that time, many questions were raised in the scientific community regarding the metabolic and ecological aspects of these bacteria. At present, there is still a myriad of open questions remaining to be answered to enlarge our knowledge of the metabolic pathways operative in these bacteria that have implications in the sulfur cycle, in biocorrosion, namely in sewers and in oil and gas systems, and in bioremediation of several toxic metals. The work presented in this dissertation aimed at contributing with new insights of enzymes involved in two different metabolic systems on Desulfovibrio species, namely enzymes that play a role in the response to oxidative stress and that are involved in the haem biosynthetic pathway.(...)

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Energy conservation in chemotrophic anaerobic bacteria is achieved by two possible processes, substrate level phosphorylation (SLP) and electron transfer phosphorylation (ETP). This second mechanism, also known as respiration, involves chemiosmotic coupling. However, a third mechanism for energy coupling was recently proposed: the flavin-based electron bifurcation (FBEB). (...)

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Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.