Electrode Kinetics of Vanadium Flow Batteries: Contrasting Responses of V\u3csup\u3eII\u3c/sup\u3e-V\u3csup\u3eIII\u3c/sup\u3e and V\u3csup\u3eIV\u3c/sup\u3e-V\u3csup\u3eV\u3c/sup\u3e to Electrochemical Pretreatment of Carbon

Electrochemical impedance spectroscopy and cyclic voltammetry were used to investigate the electrode kinetics of VII-VIII and VIV-VV in H2SO4 on glassy carbon, carbon paper, carbon xerogel, and carbon fibers. It was shown that, for all carbon materials investigated, the kinetics of VII-VIII is enhanced by anodic, and inhibited by cathodic, treatment of the electrode; in contrast, the kinetics of VIV-VV is inhibited by anodic, and enhanced by cathodic, treatment. The potential region for each of these effects varied only slightly with carbon material. Rate constants were always greater for VIV-VV than for VII-VIII except when anodized electrodes were compared, which may explain discrepancies in the literature. The observed effects are attributed to oxygen-containing functional-groups on the electrode surface. The considerable differences between the potentials at which enhancement of VII-VIII and inhibition of VIV-VV occur indicates that they do not correspond to a common oxidized state of the electrode. Likewise inhibition of VII-VIII and enhancement of VIV-VV do not correspond to a common reduced state of the electrode. It is possible that enhancement of both VII-VIII and VIV-VV is due to the same (active) state of the electrode

Computationally efficient flux variability analysis

<p>Abstract</p> <p>Background</p> <p>Flux variability analysis is often used to determine robustness of metabolic models in various simulation conditions. However, its use has been somehow limited by the long computation time compared to other constraint-based modeling methods.</p> <p>Results</p> <p>We present an open source implementation of flux variability analysis called fastFVA. This efficient implementation makes large-scale flux variability analysis feasible and tractable allowing more complex biological questions regarding network flexibility and robustness to be addressed.</p> <p>Conclusions</p> <p>Networks involving thousands of biochemical reactions can be analyzed within seconds, greatly expanding the utility of flux variability analysis in systems biology.</p

OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models

Quantitative characterization of metabolism and metabolic shifts during growth of the new human cell line AGE1.HN using time resolved metabolic flux analysis

For the improved production of vaccines and therapeutic proteins, a detailed understanding of the metabolic dynamics during batch or fed-batch production is requested. To study the new human cell line AGE1.HN, a flexible metabolic flux analysis method was developed that is considering dynamic changes in growth and metabolism during cultivation. This method comprises analysis of formation of cellular components as well as conversion of major substrates and products, spline fitting of dynamic data and flux estimation using metabolite balancing. During batch cultivation of AGE1.HN three distinct phases were observed, an initial one with consumption of pyruvate and high glycolytic activity, a second characterized by a highly efficient metabolism with very little energy spilling waste production and a third with glutamine limitation and decreasing viability. Main events triggering changes in cellular metabolism were depletion of pyruvate and glutamine. Potential targets for the improvement identified from the analysis are (i) reduction of overflow metabolism in the beginning of cultivation, e.g. accomplished by reduction of pyruvate content in the medium and (ii) prolongation of phase 2 with its highly efficient energy metabolism applying e.g. specific feeding strategies. The method presented allows fast and reliable metabolic flux analysis during the development of producer cells and production processes from microtiter plate to large scale reactors with moderate analytical and computational effort. It seems well suited to guide media optimization and genetic engineering of producing cell lines

On the orders of magnitude of epigenic dynamics and monoclonal antibody production

The hybridoma cell's maximum capacity for monoclonal antibody ( MAb ) production is estimated to be 2300–8000 MAb molecules/cell/s, using measured rates of transcription and translation, and the limitations imposed by the size of the polymerase molecule and the ribosome. Nearly all the production rates reported in the literature fall into or below this range of production rates. Data from batch cultures of hybridomas demonstrate a constant specific rate of MAb production until the time integral of the viable cell concentration reaches about 10 8 cells · h/cm 3 . At this point, some essential nutrients from the standard media are depleted, causing MAb production to decline.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47810/1/449_2004_Article_BF00369177.pd