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The concept of Elementary Flux Modes (EFMs) has been of central importance in a number of studies involving the analysis of metabolism. In Provost and Bastin (2007) this concept is used to translate the metabolic networks of the different phases of CHO cell cultures into macroscopic bioreactions linking extracellular substrates to products. However, a critical issue concerns the calculation of these elementary flux vectors, as their number combinatorially increases with the size of the metabolic network. In this study, a detailed metabolic network of CHO cells is considered, where the above-mentioned combinatorial explosion makes the computation of the elementary flux modes impossible. To alleviate this problem, a methodology proposed in Jungers et al. (2011) is used to compute a decomposition of admissible flux vectors in a minimal number of elementary flux modes without explicitly enumerating all of them. As a result, a set of macroscopic bioreactions linking the extracellular measured species is obtained at a very low computational expense. The procedure is repeated for the several cell culture phases and a global model is built using a multi-model approach, which is able to successfully predict the evolution of experimental data.

The concept of elementary flux vector is valuable in a number of applications of metabolic engineering. For instance, in metabolic flux analysis, each admissible flux vector can be expressed as a non-negative linear combination of a small number of elementary flux vectors. However a critical issue concerns the total number of elementary flux vectors which may be huge because it combinatorially increases with the size of the metabolic network. In this paper we present a fast algorithm that randomly computes a decomposition of admissible flux vectors in a minimal number of elementary flux vectors without explicitly enumerating all of them.

The flux distribution in a detailed metabolic network of CHO-320 cells is evaluated using Metabolic Flux Analysis. As in many practical situations, the available information is not sufficient to completely define the metabolic fluxes, and so, the mass balance system of equations is underdetermined. However, the measurements of the time evolution of a number of extracellular components can provide a set of constraints on the metabolic network, so that a range of possible (non-negative) solutions for each metabolic reaction can be computed instead. In this way, metabolic flux intervals can be established for each intra-extracellular flux in the metabolic network. Moreover, the incorporation of simple theoretical assumptions or the addition of further extracellular measurements, result in the determination of certain metabolic fluxes and the delimitation of quite narrow intervals for the others, so providing a good guess of the real flux distribution in CHO-320 cells. A unique flux distribution can also be computed through linear optimization and the definition of some optimality criteria. In this article, several of the above-mentioned situations are discussed, highlighting the importance of specific measurements and comparing the flux intervals under some particular assumptions such as optimal biomass growth or no Threonine catabolism. In addition, the influence of the measurement errors on the numerical results is explored using Monte Carlo techniques.

The presence of organic cosolvents was previously considered necessary to obtain high conversion yields in the synthesis of β-lactam antibiotics with immobilized penicillin acylase, and it is so when working at moderate substrate concentrations. Conversion yields close to stoichiometric and high productivities were recently reported for the synthesis of cephalexin at high substrate concentrations in ethylene glycol medium. Under such conditions, the effect of cosolvent concentration on yield is not significant so we raised the hypothesis that stoichiometric yields and high productivities are attainable at very high substrate concentrations in fully aqueous medium leading to substantial process improvement in terms of costs and environment. To test the hypothesis, the kinetically controlled synthesis of cephalexin with immobilized penicillin acylase was conducted in aqueous medium at substrates concentrations up to and beyond their solubilities at varying temperature, pH, enzyme to substrate and acyl donor to nucleophile ratios. At the best conditions, 99% conversion yield was attained with volumetric productivity of 300 mM/h and specific productivity of 7.8 mmol/h g cat . These values are slightly higher than those previously obtained under optimized conditions in organic medium so that the hypothesis has been confirmed, which opens up the possibility of efficiently produce the antibiotic through an environmentally friendly process.

In this article the metabolic flux analysis of growing CHO-320 cells is performed for a detailed metabolic network which involves 100 reactions and embraces all the significant pathways describing the metabolism of CHO cells. The purpose is to investigate the efficiency of the flux analysis when it is based on a relatively small set of extracellular measurements that can be easily achieved in most laboratories. In this case the flux analysis problem leads to a generally underdetermined mass balance system, as data are not sufficient to uniquely define the metabolic fluxes. Our main contribution is to show that, provided the system of mass balance equations is well-posed, although it is underdetermined, very narrow intervals may be found for most fluxes. The importance of checking the well-posedness of the problem is emphasized and the influence of the number of available measurements on the accuracy of the metabolic flux intervals is systematically investigated. In all cases the computed flux intervals are bounded and a single well defined value is obtained for the formation rates of the cellular macromolecules (proteins, DNA, RNA, lipids) that are not measured. The potential gain of a simple theoretical assumption regarding the metabolism of Threonine is also discussed and compared with an optimal solution calculated by maximizing the biomass formation rate. Alternative network structures obtained by inverting the direction of reversible reactions are also considered. Finally, the results of the metabolic flux analysis are exploited to estimate the total energy production resulting from the metabolism of growing CHO-320 cells.