RESUMEN
The present work mainly deals with biological oxidation, which was tested using the bacterium Thiobacillus thioparus in semi-batch bioreactor systems to evaluate the removal efficiencies and optimal conditions for the biodegradation of methanethiol (MT) in order to treat the natural gas and refinery output streams. The efficiency of this method is analysed by evaluating the concentration of MT in a bioreactor. The effect of operational parameters, such as initial concentration of MT, pH, temperature, dissolved oxygen (DO), initial concentration of bacteria and reaction time on the degradation of MT, were studied. In this process, MT is converted into elemental sulphur particles as an intermediate in the oxidation process of MT to sulphate. The obtained results showed that the highest degradation rate occurred during the first 300 minutes of reaction time. The optimal conditions of the different initial MT concentrations with 0.3-0.6 bacteria OD, DO of 0.5 ppm, acidic pH value of 6.2 and temperature of 300C are obtained. Acidic pH and oxygen-limiting conditions were applied to obtain 80-85% selectivity for elemental sulphur formation in products. Under the optimal conditions, and for the highest (8.51 mM) and the lowest (0.53 mM) concentration of MT, the biological removal was about 89% and 94%, respectively.
Asunto(s)
Contaminantes Atmosféricos/metabolismo , Compuestos de Sulfhidrilo/metabolismo , Azufre/metabolismo , Thiobacillus/metabolismo , Contaminantes Químicos del Agua/metabolismo , Reactores Biológicos , Concentración de Iones de Hidrógeno , Oxidación-Reducción , Compuestos de Sulfhidrilo/aislamiento & purificación , Temperatura , Contaminantes Químicos del Agua/aislamiento & purificaciónRESUMEN
Rhamnolipids (RLs) produced by the opportunistic human pathogen Pseudomonas aeruginosa are considered as potential candidates for the next generation of surfactants. Large-scale production of RLs depends on progress in strain engineering, medium design, operating strategies, and purification procedures. In this work, the rhlAB genes extracted from a mono_RLs_producing strain of P. aeruginosa (ATCC 9027) were introduced to an appropriate safety host Pseudomonas putida KT2440. The capability of the recombinant strain was evaluated in various media. As a prerequisite for optimal medium design, a set of 32 experiments was performed in two steps for screening a number of macro-nutritional compounds. In the experiments, a two-level fractional factorial design resolution IV was followed by a two-level full factorial one. By means of this approach, it was observed that glycerol, yeast extract, and peptone have significant positive influence on recombinant RLs production while the yeast extract/peptone two-factor and glycerol/yeast extract/peptone three-factor interactions have considerable negative effects. A wide range of variation from 0 to 570 mg/l was obtained for RLs production during the screening experiments indicating the importance of medium optimization. The results point out the opportunity for possible higher yields of RLs through further screening, mixture/combined mixture designs, and high-cell-density cultivations.
Asunto(s)
Medios de Cultivo/química , Glucolípidos/biosíntesis , Pseudomonas aeruginosa/metabolismo , Pseudomonas putida/metabolismo , Proteínas Bacterianas/genética , Proteínas Bacterianas/metabolismo , Medios de Cultivo/farmacología , Glicerol/farmacología , Peptonas/farmacología , Pseudomonas putida/genéticaRESUMEN
In this study, biological sulfide removal from natural gas in a continuous bioreactor is investigated for estimation of the optimal operational parameters. According to the carried out reactions, sulfide can be converted to elemental sulfur, sulfate, thiosulfate, and polysulfide, of which elemental sulfur is the desired product. A mathematical model is developed and was used for investigation of the effect of various parameters on elemental sulfur selectivity. The results of the simulation show that elemental sulfur selectivity is a function of dissolved oxygen, sulfide load, pH, and concentration of bacteria. Optimal parameter values are calculated for maximum elemental sulfur selectivity by using genetic algorithm as an adaptive heuristic search. In the optimal conditions, 87.76% of sulfide loaded to the bioreactor is converted to elemental sulfur.