Metabolic network models describing growth of Escherichia coli on glucose, glycerol and acetate were derived from a genome scale model of E. coli. One of the uncertainties in the metabolic networks is the exact stoichiometry of energy generating and consuming processes. Accurate estimation of biomass and product yields requires correct information on the ATP stoichiometry. The unknown ATP stoichiometry parameters of the constructed E. coli network were estimated from experimental data of eight different aerobic chemostat experiments carried out with E. coli MG1655, grown at different dilution rates (0.025, 0.05, 0.1, and 0.3 h(-1)) and on different carbon substrates (glucose, glycerol, and acetate). Proper estimation of the ATP stoichiometry requires proper information on the biomass composition of the organism as well as accurate assessment of net conversion rates under well-defined conditions. For this purpose a growth rate dependent biomass composition was derived, based on measurements and literature data. After incorporation of the growth rate dependent biomass composition in a metabolic network model, an effective P/O ratio of 1.49 +/- 0.26 mol of ATP/mol of O, K(X) (growth dependent maintenance) of 0.46 +/- 0.27 mol of ATP/C-mol of biomass and m(ATP) (growth independent maintenance) of 0.075 +/- 0.015 mol of ATP/C-mol of biomass/h were estimated using a newly developed Comprehensive Data Reconciliation (CDR) method, assuming that the three energetic parameters were independent of the growth rate and the used substrate. The resulting metabolic network model only requires the specific rate of growth, micro, as an input in order to accurately predict all other fluxes and yields.

In this study, we investigated during 400 days the microbial community variations as observed from 16S DNA gene DGGE banding patterns from an aerobic granular sludge pilot plant as well as the from a full-scale activated sludge treatment plant in Epe, the Netherlands. Both plants obtained the same wastewater and had the same relative hydraulic variations and run stable over time. For the total bacterial population, a similarity analysis was conducted showing that the community composition of both sludge types was very dissimilar. Despite this difference, general bacterial population of both systems had on average comparable species richness, entropy, and evenness, suggesting that different bacteria were sharing the same functionality. Moreover, multi-dimensional scaling analysis revealed that the microbial populations of the flocculent sludge system moved closely around the initial population, whereas the bacterial population in the aerobic granular sludge moved away from its initial population representing a permanent change. In addition, the ammonium-oxidizing community of both sludge systems was studied in detail showing more unevenness than the general bacterial community. Nitrosomonas was the dominant AOB in flocculent sludge, whereas in granular sludge, Nitrosomonas and Nitrosospira were present in equal amounts. A correlation analysis of process data and microbial data from DGGE gels showed that the microbial diversity shift in ammonium-oxidizing bacteria clearly correlated with fluctuations in temperature.

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The scale-up of Taylor flow from a single capillary channel to a monolith is a critical step for the industrial application of microchannel reactors in general and monolith catalyst supports in particular. Characteristics of pressure drop in capillaries were used to identify the conditions under which all channels in a monolith behave essentially identically. This eliminated upflow as unstable and posed a criterion for the minimal stable gas and liquid velocity in downflow. The assumption that the pressure drop over all channels is the same allowed the transformation of feed maldistribution into a residence time distribution. The residence time of the bubble train was rather insentitive to feed maldistribution. Experiments confirmed the limited impact of maldistribution on the RTD for different distributors. The E curves in monoliths were described by a piston-dispersion-exchange (PDE) model, where the dispersion term quantified the maldistribution. Industrially relevant observations on distributor design and monoliths blocks stacking are reported. The most important practical conclusion was that monoliths can indeed be scaled-up using physically sound criteria.