Utilizing elementary mode analysis, pathway thermodynamics, and a genetic algorithm for metabolic flux determination and optimal metabolic network design

<p>Abstract</p> <p>Background</p> <p>Microbial hosts offer a number of unique advantages when used as production systems for both native and heterologous small-molecules. These advantages include high selectivity and benign environmental impact; however, a principal drawback is low yield and/or productivity, which limits economic viability. Therefore a major challenge in developing a microbial production system is to maximize formation of a specific product while sustaining cell growth. Tools to rationally reconfigure microbial metabolism for these potentially conflicting objectives remain limited. Exhaustively exploring combinations of genetic modifications is both experimentally and computationally inefficient, and can become intractable when multiple gene deletions or insertions need to be considered. Alternatively, the search for desirable gene modifications may be solved heuristically as an evolutionary optimization problem. In this study, we combine a genetic algorithm and elementary mode analysis to develop an optimization framework for evolving metabolic networks with energetically favorable pathways for production of both biomass and a compound of interest.</p> <p>Results</p> <p>Utilization of thermodynamically-weighted elementary modes for flux reconstruction of <it>E. coli </it>central metabolism revealed two clusters of EMs with respect to their Δ<it>G</it>_<it>p</it>°. For proof of principle testing, the algorithm was applied to ethanol and lycopene production in <it>E. coli</it>. The algorithm was used to optimize product formation, biomass formation, and product and biomass formation simultaneously. Predicted knockouts often matched those that have previously been implemented experimentally for improved product formation. The performance of a multi-objective genetic algorithm showed that it is better to couple the two objectives in a single objective genetic algorithm.</p> <p>Conclusion</p> <p>A computationally tractable framework is presented for the redesign of metabolic networks for maximal product formation combining elementary mode analysis (a form of convex analysis), pathway thermodynamics, and a genetic algorithm to optimize the production of two industrially-relevant products, ethanol and lycopene, from <it>E. coli</it>. The designed algorithm can be applied to any small-scale model of cellular metabolism theoretically utilizing any substrate and applied towards the production of any product.</p

From flavors and pharmaceuticals to advanced biofuels: Production of isoprenoids in Saccharomyces cerevisiae

Isoprenoids denote the largest group of chemicals in the plant kingdom and are employed for a wide range of applications in the food and pharmaceutical industry. In recent years, isoprenoids have additionally been recognized as suitable replacements for petroleum-derived fuels and could thus promote the transition towards a more sustainable society. To realize the biofuel potential of isoprenoids, a very efficient production system is required. While complex chemical structures as well as the low abundance in nature demonstrate the shortcomings of chemical synthesis and plant extraction, isoprenoids can be produced by genetically engineered microorganisms from renewable carbon sources. In this article, we summarize the development of isoprenoid applications from flavors and pharmaceuticals to advanced biofuels and review the strategies to design microbial cell factories, focusing on Saccharomyces cerevisiae for the production of these compounds. While the high complexity of biosynthetic pathways and the toxicity of certain isoprenoids still denote challenges that need to be addressed, metabolic engineering has enabled large-scale production of several terpenoids and thus, the utilization of these compounds is likely to expand in the future

Partial inhibition and bilevel optimization in flux balance analysis

Motivation: Within Flux Balance Analysis, the investigation of complex subtasks, such as finding the optimal perturbation of the network or finding an optimal combination of drugs, often requires to set up a bilevel optimization problem. In order to keep the linearity and convexity of these nested optimization problems, an ON/OFF description of the effect of the perturbation (i.e. Boolean variable) is normally used. This restriction may not be realistic when one wants, for instance, to describe the partial inhibition of a reaction induced by a drug.Results: In this paper we present a formulation of the bilevel optimization which overcomes the oversimplified ON/OFF modeling while preserving the linear nature of the problem. A case study is considered: the search of the best multi-drug treatment which modulates an objective reaction and has the minimal perturbation on the whole network. The drug inhibition is described and modulated through a convex combination of a fixed number of Boolean variables. The results obtained from the application of the algorithm to the core metabolism of E.coli highlight the possibility of finding a broader spectrum of drug combinations compared to a simple ON/OFF modeling.Conclusions: The method we have presented is capable of treating partial inhibition inside a bilevel optimization, without loosing the linearity property, and with reasonable computational performances also on large metabolic networks. The more fine-graded representation of the perturbation allows to enlarge the repertoire of synergistic combination of drugs for tasks such as selective perturbation of cellular metabolism. This may encourage the use of the approach also for other cases in which a more realistic modeling is required. \ua9 2013 Facchetti and Altafini; licensee BioMed Central Ltd

The avian cell line AGE1.CR.pIX characterized by metabolic flux analysis

Lohr V, Haedicke O, Genzel Y, et al. The avian cell line AGE1.CR.pIX characterized by metabolic flux analysis. BMC Biotechnology. 2014;14(1): 72.Background: In human vaccine manufacturing some pathogens such as Modified Vaccinia Virus Ankara, measles, mumps virus as well as influenza viruses are still produced on primary material derived from embryonated chicken eggs. Processes depending on primary cell culture, however, are difficult to adapt to modern vaccine production. Therefore, we derived previously a continuous suspension cell line, AGE1.CR.pIX, from muscovy duck and established chemically-defined media for virus propagation. Results: To better understand vaccine production processes, we developed a stoichiometric model of the central metabolism of AGE1.CR.pIX cells and applied flux variability and metabolic flux analysis. Results were compared to literature dealing with mammalian and insect cell culture metabolism focusing on the question whether cultured avian cells differ in metabolism. Qualitatively, the observed flux distribution of this avian cell line was similar to distributions found for mammalian cell lines (e.g. CHO, MDCK cells). In particular, glucose was catabolized inefficiently and glycolysis and TCA cycle seem to be only weakly connected. Conclusions: A distinguishing feature of the avian cell line is that glutaminolysis plays only a minor role in energy generation and production of precursors, resulting in low extracellular ammonia concentrations. This metabolic flux study is the first for a continuous avian cell line. It provides a basis for further metabolic analyses to exploit the biotechnological potential of avian and vertebrate cell lines and to develop specific optimized cell culture processes, e.g. vaccine production processes

Identifying the Minimal Enzymes Required for Biosynthesis of Epoxyketone Proteasome Inhibitors

Epoxyketone proteasome inhibitors have attracted much interest due to their potential as anti-cancer drugs. While the biosynthetic gene clusters for several peptidyl epoxyketone natural products have recently been identified, the enzymatic logic involved in the formation of the terminal epoxyketone pharmacophore has been relatively unexplored. Here, we report the identification of the minimal set of enzymes from the eponemycin gene cluster necessary for the biosynthesis of novel metabolites containing a terminal epoxyketone pharmacophore in Escherichia coli, a versatile and fast-growing heterologous host. This set of enzymes includes a non-ribosomal peptide synthetase (NRPS), a polyketide synthase (PKS), and an acyl-CoA dehydrogenase (ACAD) homolog. In addition to the in vivo functional reconstitution of these enzymes in E. coli, in vitro studies of the eponemycin NRPS and (13)C-labeled precursor feeding experiments were performed to advance the mechanistic understanding of terminal epoxyketone formation