Functional Casein-Poly saccharide Conjugates Prepared by Controlled Dry Heating

Casein was conjugated with dextran and galactomannan in a controlled dry state at a relative humidity of 79% and at 60°C for 24 hr. The covalent attachment of polysaccharides to casein was confirmed by SDS-PAGE and HPLC. The emulsifying activity of the casein-dextran and casein-galactomannan conjugates was 1.5 times higher than that of casein. The emulsion stability of the casein-dextran and casein-galactomannan conjugates was 10 times higher than that of casein. The improvement in these emulsifying properties reached a steady state when the conjugation of casein with polysaccharide was done for 24 hr in a controlled dry state, suggesting the rapid formation of conjugates through a Maillard reaction in the case of casein. Compared to commercial emulsifiers, the casein-polysaccharide conjugates showed better emulsifying properties in acidic and high-salt concentration systems.     

Modeling speciation effects on biodegradation in mixed metal/chelate systems

A new model, CCBATCH, comprehensively couples microbially catalyzed reactions to aqueous geochemistry. The effect of aqueous speciation on biodegradation reactions and the effect of biological reactions on the concentration of chemical species (e.g. H₂CO₃, NH ₄ ⁺ , O₂) are explicitly included in CCBATCH, allowing systematic investigation of kinetically controlled biological reactions. Bulk-phase chemical speciation reactions including acid/base and complexation are modeled as thermodynamically controlled, while biological reactions are modeled as kinetically controlled. A dual-Monod kinetic formulation for biological degradation reactions is coupled with stoichiometry for the degradation reaction to predict the rate of change of all biological and chemical species affected by the biological reactions. The capability of CCBATCH to capture pH and speciation effects on biological reactions is demonstrated by a series of modeling examples for the citrate/Fe(III) system. pH controls the concentration of potentially biologically available forms of citrate. When the percentage of the degradable substrate is low due to complexation or acid/base speciation, degradation rates may be slow despite high concentrations of substrate Complexation reactions that sequester substratein non-degradable forms may prevent degradation or stopdegradation reactions prior to complete substrate utilization. The capability of CCBATCH to couple aqueous speciation changes to biodegradation reaction kinetics and stoichiometry allows prediction of these key behaviors in mixed metal/chelate systems.     

Refining predictions of climate change impacts on plant species distribution through the use of local statistics

Bioclimate envelope models are often used to predict changes in species distribution arising from changes in climate. These models are typically based on observed correlations between current species distribution and climate data. One limitation of this basic approach is that the relationship modelled is assumed to be constant in space; the analysis is global with the relationship assumed to be spatially stationary. Here, it is shown that by using a local regression analysis, which allows the relationship under study to vary in space, rather than conventional global regression analysis it is possible to increase the accuracy of bioclimate envelope modelling. This is demonstrated for the distribution of Spotted Meddick in Great Britain using data relating to three time periods, including predictions for the 2080s based on two climate change scenarios. Species distribution and climate data were available for two of the time periods studied and this allowed comparison of bioclimate envelope model outputs derived using the local and global regression analyses. For both time periods, the area under the receiver operating characteristics curve derived from the analysis based on local statistics was significantly higher than that from the conventional global analysis; the curve comparisons were also undertaken with an approach that recognised the dependent nature of the data sets compared. Marked differences in the future distribution of the species predicted from the local and global based analyses were evident and highlight a need for further consideration of local issues in modelling ecological variables.     

Multi-scale modeling of complex neuronal networks: a view towards striatal cholinergic pattern formations

The phenomena related to brain function occur as the interplay of various modules at different spatial and temporal scales. Particularly, the integration of the dynamical behavior of cells within the complex brain topology reveals a heterogeneous multi-scale problem, which has, to date, mainly been addressed by methods of statistical physics such as mean-field approximations. In contrast, the present study introduces an abstract mathematical model of a deterministic nature that provides a robust integral transformation of the microscopic activities into macroscopic spatiotemporal patterns. The existence of the transformation operator is guaranteed by the convergence of a repetitive patching of the network domain with its fundamental domains that express the local topologies of the tissue. Depending on the choice of the local connectivity function, this framework represents a computationally efficient generalization of the classical Kirchhoff’s, Hebbian, and Hopfield’s approaches. The capabilities of this multi-scale method have been evaluated within the structure of the dorsal striatum of rats, a brain region with major involvement in motor and cognitive information processing. Numerical simulations suggest the formation of characteristic spatiotemporal patterns due to the activation of cholinergic interneurons.     

Process-oriented ecological modeling approach and scientific workflow system

A scientific workflow system is designed specifically to organize, manage and execute a series of research steps, or a workflow, in a given runtime environment. The vision for scientific workflow systems is that the scientists around the world can collaborate on designing global-scaled experiments, sharing the data sets, experimental processes, and results on an easy-to-use platform. Each scientist can create and execute their own workflows and view results in real-time, and then subsequently share and reuse workflows among other scientists. Two case studies, using the Kepler system and BioVeL, are introduced in this paper. Ecological niche modeling process, which is a specialized form of scientific workflow system included in both Kepler system and BioVeL, was used to describe and discuss the features, developmental trends, and problems of scientific workflows.     

Novel approach to engineer strains for simultaneous sugar utilization

Use of lignocellulosic biomass as a second generation feedstock in the biofuels industry is a pressing challenge. Among other difficulties in using lignocellulosic biomass, one major challenge is the optimal utilization of both 6-carbon (glucose) and 5-carbon (xylose) sugars by industrial microorganisms. Most industrial microorganisms preferentially utilize glucose over xylose owing to the regulatory phenomenon of carbon catabolite repression (CCR). Microorganisms that can co-utilize glucose and xylose are of considerable interest to the biofuels industry due to their ability to simplify the fermentation processes. However, elimination of CCR in microorganisms is challenging due to the multiple coordinating mechanisms involved. We report a novel algorithm, SIMUP, which finds metabolic engineering strategies to force co-utilization of two sugars, without targeting the regulatory pathways of CCR. Mutants of Escherichia coli based on SIMUP algorithm showed predicted growth phenotypes and co-utilized glucose and xylose; however, consumed the sugars slower than the wild-type. Some solutions identified by the algorithm were based on stoichiometric imbalance and were not obvious from the metabolic network topology. Furthermore, sequencing studies on the genes involved in CCR showed that the mechanism for co-utilization of the sugars could be different from previously known mechanisms.     

Flux analysis of recombinant Saccharomyces cerevisiae YPB-G utilizing starch for optimal ethanol production

Genetically modified Saccharomyces cerevisiae strain (YPB-G) which secretes a bifunctional fusion protein that contains both Bacillus subtilis -amylase and Aspergillus awamori glucoamylase activities was used for the direct conversion of starch into ethanol. Starch was either supplied initially to different nutrient media or added instantaneously to the reactor at various discrete time instants (pulse feeding). Stoichiometric modeling was used to investigate the effects of initial substrate concentration and growth rate of the recombinant yeast culture on ethanol production. Reaction stoichiometries describing both the anabolism and catabolism of the microorganism were used as an input to flux balance analysis (FBA), the preferred metabolic modeling approach since the constructed stoichiometric network was underdetermined. Experiments for batch and fed-batch systems at different substrate concentrations were analyzed theoretically in terms of flux distributions using ethanol production rate as the maximization criteria. Calculated ethanol rates were in agreement with experimental measurements, suggesting that this recombinant microorganism is sufficiently evolved to optimize its ethanol production. The function of the main pathways of yeast metabolism (PPP, EMP, TCA) are discussed together with the node analyses of glucose-6-P and pyruvate branch points. Theoretical node analysis revealed that if the split ratio in G6P branch point is changed by genetic manipulations, the ethanol yield would be affected considerably.