Control analysis is a powerful method to quantify the regulation of metabolic pathways. We have applied it to lipid biosynthesis for the first time by using model tissue culture systems from the important oil crops, olive ( Olea europaea L.) and oil palm ( Elaeis guineensis Jacq.). By the use of top-down control analysis, fatty acid biosynthesis has been shown to exert more control than lipid assembly under different experimental conditions. However, both parts of the lipid biosynthetic pathway are important, so that attempts to alter oil yield by manipulating the activity of a single enzyme step are very unlikely to produce significant increases.
The purification of thermo-acidic amylase enzyme from red pitaya (Hylocereus polyrhizus) peel for the first time was investigated using a novel aqueous two-phase system (ATPS) consisting of a thermo-separating copolymer and an organic solvent. The effectiveness of different parameters such as molecular weight of the thermo-separating ethylene oxide-propylene oxide (EOPO) copolymer and type and concentration of organic solvent on the partitioning behavior of amylase was investigated. In addition, the effects of phase components, volume ratio (VR), pH and crude load of purification factor and yield of amylase were evaluated to achieve the optimum partition conditions of the enzyme. In the novel ATPS method, the enzyme was satisfactorily partitioned into the polymer-rich top phase in the system composed of 30% (w/w) EOPO 2500 and 15% (w/w) 2-propanol, at a volume ratio of 1.94 and with a crude load scale of 25% (w/w) at pH 5.0. Recovery and recycling of components was also measured in each successive step of the ATPS process. The enzyme was successfully recovered by the method with a high purification factor of 14.3 and yield of 96.6% and copolymer was also recovered and recycled at a rate above 97%, making the method was more economical than the traditional ATPS method.
The phage N15 protelomerase enzyme (TelN) is essential for the replication of its genome by resolution of its telRL domain, located within a telomerase occupancy site (tos), into hairpin telomeres. Isolation of TelN for in vitro processing of tos, however, is a highly complex process, requiring multiple purification steps. In this study a simplified protocol for crude total protein extraction is described that retains the tos-cleaving activity of TelN for at least 4 weeks, greatly simplifying in vitro testing of its activity. This protocol may be extended for functional analysis of other phage and bacterial proteins, particularly DNA-processing enzymes.
Box-Wilson design (BWD) model was applied to determine the optimum values of influencing parameters in anaerobic fermentation to produce hydrogen using Clostridium saccharoperbutylacetonicum N1-4 (ATCC 13564). The main focus of the study was to find the optimal relationship between the hydrogen yield and three variables including initial substrate concentration, initial medium pH and reaction temperature. Microbial growth kinetic parameters for hydrogen production under anaerobic conditions were determined using the Monod model with incorporation of a substrate inhibition term. The values of micro(max) (maximum specific growth rate) and K, (saturation constant) were 0.398 h(-1) and 5.509 g L(-1), respectively, using glucose as the substrate. The experimental substrate and biomass-concentration profiles were in good agreement with those obtained by the kinetic-model predictions. By varying the conditions of the initial substrate concentration (1-40 g L(-1)), reaction temperature (25-40 degrees C) and initial medium pH (4-8), the model predicted a maximum hydrogen yield of 3.24 mol H2 (mol glucose)(-1). The experimental data collected utilising this design was successfully fitted to a second-order polynomial model. An optimum operating condition of 10 g L(-1) initial substrate concentration, 37 degrees C reaction temperature and 6.0 +/- 0.2 initial medium pH gave 80% of the predicted maximum yield of hydrogen where as the experimental yield obtained in this study was 77.75% exhibiting a close accuracy between estimated and experimental values. This is the first report to predict bio-hydrogen yield by applying Box-Wilson Design in anaerobic fermentation while optimizing the effects of environmental factors prevailing there by investigating the effects of environmental factors.
Nitrates in different water and wastewater streams raised concerns due to severe impacts on human and animal health. Diverse methods are reported to remove nitrate from water streams which almost fail to entirely treat nitrate, except biological denitrification which is capable of reducing inorganic nitrate compounds to harmless nitrogen gas. Review of numerous studies in biological denitrification of nitrate containing water resources, aquaculture wastewaters and industrial wastewater confirmed the potential of this method and its flexibility towards the remediation of different concentrations of nitrate. The denitrifiers could be fed with organic and inorganic substrates which have different performances and subsequent advantages or disadvantages. Review of heterotrophic and autotrophic denitrifications with different food and energy sources concluded that autotrophic denitrifiers are more effective in denitrification. Autotrophs utilize carbon dioxide and hydrogen as the source of carbon substrate and electron donors, respectively. The application of this method in bio-electro reactors (BERs) has many advantages and is promising. However, this method is not so well established and documented. BERs provide proper environment for simultaneous hydrogen production on cathodes and appropriate consumption by immobilized autotrophs on these cathodes. This survey covers various designs and aspects of BERs and their performances.
A natural shift is taking place in the approaches being adopted by plant scientists in response to the accessibility of systems-based technology platforms. Metabolomics is one such field, which involves a comprehensive non-biased analysis of metabolites in a given cell at a specific time. This review briefly introduces the emerging field and a range of analytical techniques that are most useful in metabolomics when combined with computational approaches in data analyses. Using cases from Arabidopsis and other selected plant systems, this review highlights how information can be integrated from metabolomics and other functional genomics platforms to obtain a global picture of plant cellular responses. We discuss how metabolomics is enabling large-scale and parallel interrogation of cell states under different stages of development and defined environmental conditions to uncover novel interactions among various pathways. Finally, we discuss selected applications of metabolomics.