Metabolic design based on a coupled gene expression—metabolic network model of tryptophan production in Escherichia coli

Automated adjustment of metabolic niches enables the control of natural and engineered microbial co-cultures

Much attention has focused on understanding microbial interactions leading to stable co-cultures. In this work, substrate pulsing was performed to promote better control of the metabolic niches (MNs) corresponding to each species, leading to the continuous co-cultivation of diverse microbial organisms. We used a cell-machine interface, which allows adjustment of the temporal profile of two MNs according to a rhythm, ensuring the successive growth of two species, in our case, a yeast and a bacterium. The resulting approach, called 'automated adjustment of metabolic niches' (AAMN), was effective for stabilizing both cooperative and competitive co-cultures. AAMN can be considered an enabling technology for the deployment of co-cultures in bioprocesses, demonstrated here based on the continuous bioproduction of p-coumaric acid. The data accumulated suggest that AAMN could be used not only for a wider range of biological systems, but also to gain fundamental insights into microbial interaction mechanisms.

Melatonin disturbed rumen microflora structure and metabolic pathways in vitro

IMPORTANCE

In in vitro studies, it has been found that the effects of MLT on rumen microorganisms and metabolites can change the rumen flora structure, significantly inhibit the relative abundance of harmful Acinetobacter, and improve the relative abundance of beneficial bacteria. MLT may regulate the "arginine-glutathione" pathway, "phenylalanine, tyrosine and tryptophan biosynthesis-tryptophan generation" branch, "tryptophan-kynurenine" metabolism, and "tryptophan-tryptamine-serotonin" pathway through microorganisms.

Synthetic mutualism in engineered E. coli mutant strains as functional basis for microbial production consortia

In nature, microorganisms often reside in symbiotic co-existence providing nutrition, stability, and protection for each partner by applying "division of labor." This principle may also be used for the overproduction of targeted compounds in bioprocesses. It requires the engineering of a synthetic co-culture with distributed tasks for each partner. Thereby, the competition on precursors, redox cofactors, and energy-which occurs in a single host-is prevented. Current applications often focus on unidirectional interactions, that is, the product of partner A is used for the completion of biosynthesis by partner B. Here, we present a synthetically engineered Escherichia coli co-culture of two engineered mutant strains marked by the essential interaction of the partners which is achieved by implemented auxotrophies. The tryptophan auxotrophic strain E. coli ANT-3, only requiring small amounts of the aromatic amino acid, provides the auxotrophic anthranilate for the tryptophan producer E. coli TRP-3. The latter produces a surplus of tryptophan which is used to showcase the suitability of the co-culture to access related products in future applications. Co-culture characterization revealed that the microbial consortium is remarkably functionally stable for a broad range of inoculation ratios. The range of robust and functional interaction may even be extended by proper glucose feeding which was shown in a two-compartment bioreactor setting with filtrate exchange. This system even enables the use of the co-culture in a parallel two-level temperature setting which opens the door to access temperature sensitive products via heterologous production in E. coli in a continuous manner.

A Molecular Dynamic Model of Tryptophan Overproduction in Escherichia coli

Several deterministic models simulate the main molecular biology interactions among the numerous mechanisms controlling the dynamics of the tryptophan operon in native strains. However, no models exist to investigate bacterial tryptophan production from a biotechnological point of view. Here, we modified tryptophan models for native production to propose a biotechnological working model that incorporates the activity of tryptophan secretion systems and genetic modifications made in two reported E. coli strains. The resultant deterministic model could emulate the production of tryptophan in the same order of magnitude as those quantified experimentally by the genetically engineered E. coli strains GPT1001 and GPT1002 in shake flasks. We hope this work may contribute to the rational development of biological models that define and include the main parameters and molecular components for designing and engineering efficient biotechnological chassis to produce valuable chemicals.

Combined metabolic analyses for the biosynthesis pathway of l-threonine in Escherichia coli

Currently, industrial production of l-threonine (Thr) is based on direct fermentation with microorganisms such as Escherichia coli, which has the characteristics of low cost and high productivity. In order to elucidate the key metabolic features of the synthesis pathway of Thr in E. coli to provide clues for metabolic regulation or engineering of the strain, this study was carried out on an l-threonine over-producing strain, in terms of analyses of metabolic flux, enzyme control and metabonomics. Since environmental disturbance and genetic modification are considered to be two important methods of metabolic analysis, addition of phosphate in the media and comparison of strains with different genotypes were selected as the two candidates due to their significant influence in the biosynthesis of Thr. Some important targets including key nodes, enzymes and biomarkers were identified, which may provide target sites for rational design through engineering the Thrproducing strain. Finally, metabolic regulation aimed at one biomarker identified in this study was set as an example, which confirms that combined metabolic analyses may guide to improve the production of threonine in E. coli.

Tryptophan Production Maximization in a Fed-Batch Bioreactor with Modified E. coli Cells, by Optimizing Its Operating Policy Based on an Extended Structured Cell Kinetic Model

Hybrid kinetic models, linking structured cell metabolic processes to the dynamics of macroscopic variables of the bioreactor, are more and more used in engineering evaluations to derive more precise predictions of the process dynamics under variable operating conditions. Depending on the cell model complexity, such a math tool can be used to evaluate the metabolic fluxes in relation to the bioreactor operating conditions, thus suggesting ways to genetically modify the microorganism for certain purposes. Even if development of such an extended dynamic model requires more experimental and computational efforts, its use is advantageous. The approached probative example refers to a model simulating the dynamics of nanoscale variables from several pathways of the central carbon metabolism (CCM) of Escherichia coli cells, linked to the macroscopic state variables of a fed-batch bioreactor (FBR) used for the tryptophan (TRP) production. The used E. coli strain was modified to replace the PTS system for glucose (GLC) uptake with a more efficient one. The study presents multiple elements of novelty: (i) the experimentally validated modular model itself, and (ii) its efficiency in computationally deriving an optimal operation policy of the FBR.

An antiphage Escherichia coli mutant for higher production of L-threonine obtained by atmospheric and room temperature plasma mutagenesis

Phage infection is common during the production of L-threonine by E. coli, and low L-threonine production and glucose conversion percentage are bottlenecks for the efficient commercial production of L-threonine. In this study, 20 antiphage mutants producing high concentration of L-threonine were obtained by atmospheric and room temperature plasma (ARTP) mutagenesis, and an antiphage E. coli variant was characterized that exhibited the highest production of L-threonine Escherichia coli ([E. coli] TRFC-AP). The elimination of fhuA expression in E. coli TRFC-AP was responsible for phage resistance. The biomass and cell growth of E. coli TRFC-AP showed no significant differences from those of the parent strain (E. coli TRFC), and the production of L-threonine (159.3 g L^-1 ) and glucose conversion percentage (51.4%) were increased by 10.9% and 9.1%, respectively, compared with those of E. coli TRFC. During threonine production (culture time of 20 h), E. coli TRFC-AP exhibited higher activities of key enzymes for glucose utilization (hexokinase, glucose phosphate dehydrogenase, phosphofructokinase, phosphoenolpyruvate carboxylase, and PYK) and threonine synthesis (glutamate synthase, aspartokinase, homoserine dehydrogenase, homoserine kinase and threonine synthase) compared to those of E. coli TRFC. The analysis of metabolic flux distribution indicated that the flux of threonine with E. coli TRFC-AP reached 69.8%, an increase of 16.0% compared with that of E. coli TRFC. Overall, higher L-threonine production and glucose conversion percentage were obtained with E. coli TRFC-AP due to increased activities of key enzymes and improved carbon flux for threonine synthesis.

Central metabolic pathway modification to improve L-tryptophan production in Escherichia coli

Tryptophan, an aromatic amino acid, has been widely used in food industry because it participates in the regulation of protein synthesis and metabolic network in vivo. In this study, we obtained a strain named TRP03 by enhancing the tryptophan synthesis pathway, which could accumulate tryptophan at approximately 35 g/L in a 5 L bioreactor. We then modified the central metabolic pathway of TRP03, to increase the supply of the precursor phosphoenolpyruvate (PEP), the genes related to PEP were modified. Furthermore, citric acid transport system and TCA were upregulated to effectively increase cell growth. We observed that strain TRP07 that could accumulate tryptophan at approximately 49 g/L with a yield of 0.186 g tryptophan/g glucose in a 5 L bioreactor. By-products such as glutamate and acetic acid were reduced to 0.8 g/L and 2.2 g/L, respectively.

Metabolic Engineering and Fermentation Process Strategies for L-Tryptophan Production by Escherichia coli

L-tryptophan is an essential aromatic amino acid that has been widely used in medicine, food, and animal feed. Microbial biosynthesis of L-tryptophan through metabolic engineering approaches represents a sustainable, cost-effective, and environmentally friendly route compared to chemical synthesis. In particular, metabolic pathway engineering allows enhanced product titers by inactivating/blocking the competing pathways, increasing the intracellular level of essential precursors, and overexpressing rate-limiting enzymatic steps. Based on the route of the L-tryptophan biosynthesis pathway, this review presents a systematic and detailed summary of the contemporary metabolic engineering approaches employed for L-tryptophan production. In addition to the engineering of the L-tryptophan biosynthesis pathway, the metabolic engineering modification of carbon source uptake, by-product formation, key regulatory factors, and the polyhydroxybutyrate biosynthesis pathway in L-tryptophan biosynthesis are discussed. Moreover, fermentation bioprocess optimization strategies used for L-tryptophan overproduction are also delineated. Towards the end, the review is wrapped up with the concluding remarks, and future strategies are outlined for the development of a high L-tryptophan production strain.

Misinterpretation risks of global stochastic optimisation of kinetic models revealed by multiple optimisation runs

One of use cases for metabolic network optimisation of biotechnologically applied microorganisms is the in silico design of new strains with an improved distribution of metabolic fluxes. Global stochastic optimisation methods (genetic algorithms, evolutionary programing, particle swarm and others) can optimise complicated nonlinear kinetic models and are friendly for unexperienced user: they can return optimisation results with default method settings (population size, number of generations and others) and without adaptation of the model. Drawbacks of these methods (stochastic behaviour, undefined duration of optimisation, possible stagnation and no guaranty of reaching optima) cause optimisation result misinterpretation risks considering the very diverse educational background of the systems biology and synthetic biology research community. Different methods implemented in the COPASI software package are tested in this study to determine their ability to find feasible solutions and assess the convergence speed to the best value of the objective function. Special attention is paid to the potential misinterpretation of results. Optimisation methods are tested with additional constraints that can be introduced to ensure the biological feasibility of the resulting optimised design: (1) total enzyme activity constraint (called also amino acid pool constraint) to limit the sum of enzyme concentrations and (2) homeostatic constraint limiting steady state metabolite concentration corridor around the steady state concentrations of metabolites in the original model. Impact of additional constraints on the performance of optimisation methods and misinterpretation risks is analysed.

Effects of betaine supplementation on L-threonine fed-batch fermentation by Escherichia coli

Betaine can act as a stress protectant, methyl donor, or enzyme stabilizer in vitro for the biosynthesis of structurally complex compounds. The performances of betaine type and concentration on the metabolic processes of Escherichia coli JLTHR in a 5-L fermentor were investigated. The results showed that the maximum L-threonine production of 127.3 g/L and glucose conversion percentage of 58.12% was obtained fed with the glucose solution containing 2 g/L betaine hydrochloride, which increased by 14.5 and 6.87% more compared to that of the control, respectively. This study presents an analysis of the metabolic fluxes of E. coli JLTHR for the production of L-threonine with betaine supplementation. When betaine was fed into the fermentation culture medium, the metabolic flux entering into the pentose phosphate pathway (HMP) and biosynthesis route of L-threonine increased by 57.3 and 10.1%, respectively. In conclusion, exogenous addition of betaine was validated to be a feasible and efficacious approach to improve L-threonine production.

Dynamic metabolic control: towards precision engineering of metabolism

Advances in metabolic engineering have led to the synthesis of a wide variety of valuable chemicals in microorganisms. The key to commercializing these processes is the improvement of titer, productivity, yield, and robustness. Traditional approaches to enhancing production use the “push–pull-block” strategy that modulates enzyme expression under static control. However, strains are often optimized for specific laboratory set-up and are sensitive to environmental fluctuations. Exposure to sub-optimal growth conditions during large-scale fermentation often reduces their production capacity. Moreover, static control of engineered pathways may imbalance cofactors or cause the accumulation of toxic intermediates, which imposes burden on the host and results in decreased production. To overcome these problems, the last decade has witnessed the emergence of a new technology that uses synthetic regulation to control heterologous pathways dynamically, in ways akin to regulatory networks found in nature. Here, we review natural metabolic control strategies and recent developments in how they inspire the engineering of dynamically regulated pathways. We further discuss the challenges of designing and engineering dynamic control and highlight how model-based design can provide a powerful formalism to engineer dynamic control circuits, which together with the tools of synthetic biology, can work to enhance microbial production.

Model-based metabolism design: constraints for kinetic and stoichiometric models

The implementation of model-based designs in metabolic engineering and synthetic biology may fail. One of the reasons for this failure is that only a part of the real-world complexity is included in models. Still, some knowledge can be simplified and taken into account in the form of optimization constraints to improve the feasibility of model-based designs of metabolic pathways in organisms. Some constraints (mass balance, energy balance, and steady-state assumption) serve as a basis for many modelling approaches. There are others (total enzyme activity constraint and homeostatic constraint) proposed decades ago, but which are frequently ignored in design development. Several new approaches of cellular analysis have made possible the application of constraints like cell size, surface, and resource balance. Constraints for kinetic and stoichiometric models are grouped according to their applicability preconditions in (1) general constraints, (2) organism-level constraints, and (3) experiment-level constraints. General constraints are universal and are applicable for any system. Organism-level constraints are applicable for biological systems and usually are organism-specific, but these constraints can be applied without information about experimental conditions. To apply experimental-level constraints, peculiarities of the organism and the experimental set-up have to be taken into account to calculate the values of constraints. The limitations of applicability of particular constraints for kinetic and stoichiometric models are addressed.

Total enzyme activity constraint and homeostatic constraint impact on the optimization potential of a kinetic model

The application of biologically and biochemically relevant constraints during the optimization of kinetic models reduces the impact of suggested changes in processes not included in the scope of the model. This increases the probability that the design suggested by model optimization can be carried out by an organism after implementation of design in vivo. A case study was carried out to determine the impact of total enzyme activity and homeostatic constraints on the objective function values and the following ranking of adjustable parameter combinations. The application of constraints on the model of sugar cane metabolism revealed that a homeostatic constraint caused heavier limitations of the objective function than a total enzyme activity constraint. Both constraints changed the ranking of adjustable parameter combinations: no "universal" constraint-independent top-ranked combinations were found. Therefore, when searching for the best subset of adjustable parameters, a full scan of their combinations is suggested for a small number of adjustable parameters, and evolutionary search strategies are suggested for a large number. Simultaneous application of both constraints is suggested.

L-Tryptophan Production in Escherichia coli Improved by Weakening the Pta-AckA Pathway

Acetate accumulation during the fermentation process of Escherichia coli FB-04, an L-tryptophan production strain, is detrimental to L-tryptophan production. In an initial attempt to reduce acetate formation, the phosphate acetyltransferase gene (pta) from E. coli FB-04 was deleted, forming strain FB-04(Δpta). Unfortunately, FB-04(Δpta) exhibited a growth defect. Therefore, pta was replaced with a pta variant (pta1) from E. coli CCTCC M 2016009, forming strain FB-04(pta1). Pta1 exhibits lower catalytic capacity and substrate affinity than Pta because of a single amino acid substitution (Pro69Leu). FB-04(pta1) lacked the growth defect of FB-04(Δpta) and showed improved fermentation performance. Strain FB-04(pta1) showed a 91% increase in L-tryptophan yield in flask fermentation experiments, while acetate production decreased by 35%, compared with its parent FB-04. Throughout the fed-batch fermentation process, acetate accumulation by FB-04(pta1) was slower than that by FB-04. The final L-tryptophan titer of FB-04(pta1) reached 44.0 g/L, representing a 15% increase over that of FB-04. Metabolomics analysis showed that the pta1 genomic substitution slightly decreased carbon flux through glycolysis and significantly increased carbon fluxes through the pentose phosphate and common aromatic pathways. These results indicate that this strategy enhances L-tryptophan production and decreases acetate accumulation during the L-tryptophan fermentation process.

Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli

Background

A kinetic model provides insights into the dynamic response of biological systems and predicts how their complex metabolic and gene regulatory networks generate particular functions. Of many biological systems, Escherichia coli metabolic pathways have been modeled extensively at the enzymatic and genetic levels, but existing models cannot accurately reproduce experimental behaviors in a batch culture, due to the inadequate estimation of a specific cell growth rate and a large number of unmeasured parameters.

Results

In this study, we developed a detailed kinetic model for the central carbon metabolism of E. coli in a batch culture, which includes the glycolytic pathway, tricarboxylic acid cycle, pentose phosphate pathway, Entner-Doudoroff pathway, anaplerotic pathway, glyoxylate shunt, oxidative phosphorylation, phosphotransferase system (Pts), non-Pts and metabolic gene regulations by four protein transcription factors: cAMP receptor, catabolite repressor/activator, pyruvate dehydrogenase complex repressor and isocitrate lyase regulator. The kinetic parameters were estimated by a constrained optimization method on a supercomputer. The model estimated a specific growth rate based on reaction kinetics and accurately reproduced the dynamics of wild-type E. coli and multiple genetic mutants in a batch culture.

Conclusions

This model overcame the intrinsic limitations of existing kinetic models in a batch culture, predicted the effects of multilayer regulations (allosteric effectors and gene expression) on central carbon metabolism and proposed rationally designed fast-growing cells based on understandings of molecular processes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-016-0511-x) contains supplementary material, which is available to authorized users.

Modulating the direction of carbon flow in Escherichia coli to improve l-tryptophan production by inactivating the global regulator FruR

The fructose repressor (FruR) affects carbon flux through the central metabolic pathways of Escherichia coli. In this study, l-tryptophan production in Escherichia coli FB-04 was improved by knocking out the fruR gene, thereby inactivating FruR. This fruR knockout strain, E. coli FB-04(ΔfruR), not only exhibited higher growth efficiency, it also showed substantially improved l-tryptophan production. l-tryptophan production by E. coli FB-04(ΔfruR) and l-tryptophan yield per glucose were increased by 62.5% and 52.4%, respectively, compared with the parent E. coli FB-04. Metabolomics analysis showed that the fruR knockout significantly enhances metabolic flow through glycolysis, the pentose phosphate pathway and the TCA cycle, increasing levels of critical precursors and substrates for l-tryptophan biosynthesis. These results indicate that fruR deletion should enhance l-tryptophan production and improve the efficiency of carbon source utilization independent of genetic background.

Kinetic modeling of cell metabolism for microbial production

Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations.

An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems

Computational modelling of biochemical systems based on top-down and bottom-up approaches has been well studied over the last decade. In this research, after illustrating how to generate atomic components by a set of given reactants and two user pre-defined component patterns, we propose an integrative top-down and bottom-up modelling approach for stepwise qualitative exploration of interactions among reactants in biochemical systems. Evolution strategy is applied to the top-down modelling approach to compose models, and simulated annealing is employed in the bottom-up modelling approach to explore potential interactions based on models constructed from the top-down modelling process. Both the top-down and bottom-up approaches support stepwise modular addition or subtraction for the model evolution. Experimental results indicate that our modelling approach is feasible to learn the relationships among biochemical reactants qualitatively. In addition, hidden reactants of the target biochemical system can be obtained by generating complex reactants in corresponding composed models. Moreover, qualitatively learned models with inferred reactants and alternative topologies can be used for further web-lab experimental investigations by biologists of interest, which may result in a better understanding of the system.

Phosphate limited fed-batch processes: impact on carbon usage and energy metabolism in Escherichia coli

Phosphate starvation is often applied as a tool to limit cell growth in microbial production processes without hampering carbon and/or nitrogen supply alternatively. This contribution focuses on the interplay of process induced phosphate starvation and microbial performance studying an l-tryptophan overproducing Escherichia coli strain as a model for highly ATP demanding processes in comparison with an E. coli wildtype strain. To enable a time-resolved analysis, constant phosphate feeding strategies were applied to elongate the transition from phosphate saturated to phosphate limited cell growth. With increasing phosphate limitation, a reduced cellular efficiency of ATP formation via respiratory chain activity and the ATP synthase complex was found for both strains. Process balancing, transcriptome analysis and flux balance analysis are pointing toward a multi-stage decoupling scenario, which in essence deteriorates the stoichiometric ratio of ATP formation to proton translocation, thereby affecting ATP availability from respiration and carbon usage. Starting off with a potential influence on ATP-synthase efficiency (stage 1), decoupling is further increased by modified respiratory activity (stage 2) and byproduct overflow (stage 3) finally resulting in a metabolic breakdown entering complete phosphate depletion (stage 4). The decoupling is initiated by phosphate limitation; further effects are mainly mediated on metabolic level through ATP availability and energy charge, additionally affected by ATP demanding product synthesis.

Kinetic models in industrial biotechnology - Improving cell factory performance

An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed.

Strategy for pH control and pH feedback-controlled substrate feeding for high-level production of L-tryptophan by Escherichia coli

Optimum production of L-tryptophan by Escherichia coli depends on pH. Here, we established conditions for optimizing the production of L-tryptophan. The optimum pH range was 6.5-7.2, and pH was controlled using a three-stage strategy [pH 6.5 (0-12 h), pH 6.8 (12-24 h), and pH 7.2 (24-38 h)]. Specifically, ammonium hydroxide was used to adjust pH during the initial 24 h, and potassium hydroxide and ammonium hydroxide (1:2, v/v) were used to adjust pH during 24-38 h. Under these conditions, NH4 (+) and K(+) concentrations were kept below the threshold for inhibiting L-tryptophan production. Optimization was also accomplished using ratios (v/v) of glucose to alkali solutions equal to 4:1 (5-24 h) and 6:1 (24-38 h). The concentration of glucose and the pH were controlled by adjusting the pH automatically. Applying a pH-feedback feeding method, the steady-state concentration of glucose was maintained at approximately 0.2 ± 0.02 g/l, and acetic acid accumulated to a concentration of 1.15 ± 0.03 g/l, and the plasmid stability was 98 ± 0.5 %. The final, optimized concentration of L-tryptophan was 43.65 ± 0.29 g/l from 52.43 ± 0.38 g/l dry cell weight.

Genome-derived minimal metabolic models for Escherichia coli MG1655 with estimated in vivo respiratory ATP stoichiometry

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.

Quantitative analysis of the dynamic signaling pathway involved in the cAMP mediated induction of l-carnitine biosynthesis in E. coli cultures

L-(-)-carnitine can be synthesized from waste bioprecursors in the form of crotonobetaine. Such biotransformation is carried out in E. coli by the enzymes encoded by operons regulated by the cAMP receptor proteins. Non-phosphorylated sugars, such as glycerol are used as energy and carbon source since glucose inhibits cAMP synthesis. Until now little attention has been paid to the regulatory signaling structure that operates during the transition from a glucose-consuming, non-l-carnitine producing steady state, to a glycerol-consuming l-carnitine producing steady state. In this work we aim to elucidate and quantify the underlying regulatory mechanisms operating in the abolition of the glucose inhibiting effect. For this purpose we make use of the systemic approach by integrating the available information and our own experimentally generated data to construct a mathematical model. The model is built using power-law representation and is used as a platform to make predictive simulations and to assess the consistency of the regulatory structure of the overall process. The model is subsequently checked for quality through stability and a special, dynamic sensitivity analysis. The results show that the model is able to deal with the observed system transient phase. The model is multi-hierarchical, comprising the metabolic, gene expression, signaling and bioreactor levels. It involves variables and parameters of a very different nature that develop in different time scales and orders of magnitude. Some of the most relevant conclusions obtained are: (i) the regulatory interactions among glucose, glycerol and cAMP metabolism are far stronger than those present in the l-carnitine transport, production and degradation processes; (ii) carnitine biosynthesis is very sensitive to the cAMP signaling system since it reacts at very low cAMP receptor concentrations, and (iii) ATP is a critical factor in the transient dynamics. All these model-derived observations have been experimentally confirmed by separate studies. As a whole, the model contributes to our general understanding of the transient regulation through the signal regulatory structure, thus enabling more accurate optimization strategies to be used.

Multi-Level Modeling in Systems Biology by Discrete Event Approaches (Mehrebenen-Modellierung in der Systembiologie innerhalb diskret-ereignisbasierter Ansätze)

The creation of models for heterogeneous and complex cellular networks is a central goal of Systems Biology. When modeling a biological network, one may wish to account for certain aspects in detail, while a bird's eye perspective would seem more appropriate for other parts. Multi-level models combine such overview and detail representations. We illustrate multi-level modeling with gene regulation of the Tryptophan operon in E. coli. We review three discrete event modeling formalisms and discuss model design therein: DEVS, STATECHARTS, and stochastic π-CALCULUS. This introductory presentation already reveals some of their respective virtues and shortcomings.

Topology of the global regulatory network of carbon limitation in Escherichia coli

One fundamental shortcoming of biotechnological processes operating under carbon-limiting conditions is the high-energy demand (maintenance) of the cells. Although the function of the central carbon metabolism in supplying precursors and energy for biosynthesis has been thoroughly characterized, its regulation and dynamic behaviour during carbon-limited growth has not yet been revealed. The current work demonstrates a time series of metabolic flux distributions during fed-batch cultivation of Escherichia coli K-12 W3110 applying a constant feed rate. The fluxes in glycolysis, pentose phosphate pathway and biosynthesis fell significantly, whereas TCA cycle fluxes remained constant. The flux redistribution resulted in an enhanced energy generation in the TCA cycle and consequently, in a 20% lower biomass yield. The intracellular alarmones ppGpp and cAMP accumulated in large quantities after the onset of nutrient limitation, subsequently declining to basal levels. The network topology of the regulation of the central metabolic pathways was identified so that the observed metabolic and regulatory behaviour can be described. This provides novel aspects of global regulation of the metabolism by the cra, crp and relA/spoT modulons. The work constitutes an important step towards dynamic mathematical modelling of regulation and metabolism, which is needed for the rational optimization of biotechnological processes.

Production of tyrosine from sucrose or glucose achieved by rapid genetic changes to phenylalanine-producing Escherichia coli strains

Escherichia coli K12 strains producing L-phenylalanine were converted to L-tyrosine-producing strains using a novel genetic method for gene replacement. We deleted a region of the E. coli K12 chromosome including the pheA gene encoding chorismate mutase/prephenate dehydratase, its leader peptide (pheL), and its promoter using a new polymerase chain reaction-based method that does not leave a chromosomal scar. For high level expression of tyrA, encoding chorismate mutase/prephenate dehydrogenase, its native promoter was replaced with the strong trc promoter. The linked DeltapheLA and Ptrc-tyrA::Kan(R) genetic modifications were moved into L-phenylalanine producing strains by generalized transduction to convert L-phenylalanine-producing strains to L-tyrosine-producing strains. Moreover, introduction of a plasmid carrying genes responsible for sucrose degradation into these strains enabled L-tyrosine-production from sucrose.

Applications of transcriptional profiling in antibiotics discovery and development

This chapter will review specific applications of microarray technology and related data analysis strategies in antibacterial research and development. We present examples of microarray applications spanning the entire antibiotics research and development pipeline, from target discovery, assay development, pharmacological evaluation, to compound safety studies. This review emphasizes the utility of microarrays for a systematic evaluation of novel chemistry as antibiotic agents. Transcriptional profiling has revolutionized the process of target elucidation and has the potential to offer substantial guidance in the identification of new targets. Microarrays will continue to be a workhorse of anti-infectives discovery programs ranging from efficacy assessments of antibiotics ('forward pharmacology') to drug safety evaluations ('toxicogenomics').

The nature of systems biology

The advent of functional genomics has enabled the molecular biosciences to come a long way towards characterizing the molecular constituents of life. Yet, the challenge for biology overall is to understand how organisms function. By discovering how function arises in dynamic interactions, systems biology addresses the missing links between molecules and physiology. Top-down systems biology identifies molecular interaction networks on the basis of correlated molecular behavior observed in genome-wide "omics" studies. Bottom-up systems biology examines the mechanisms through which functional properties arise in the interactions of known components. Here, we outline the challenges faced by systems biology and discuss limitations of the top-down and bottom-up approaches, which, despite these limitations, have already led to the discovery of mechanisms and principles that underlie cell function.

Towards bacterial strains overproducing L-tryptophan and other aromatics by metabolic engineering

The aromatic amino acids, L-tryptophan, L-phenylalanine, and L-tyrosine, can be manufactured by bacterial fermentation. Until recently, production efficiency of classical aromatic amino-acid-producing mutants had not yet reached a high level enough to make the fermentation method the most economic. With the introduction of recombinant DNA technology, it has become possible to apply more rational approaches to strain improvement. Many recent activities in this metabolic engineering have led to several effective approaches, which include modification of terminal pathways leading to removal of bottleneck or metabolic conversion, engineering of central carbon metabolism leading to increased supply of precursors, and transport engineering leading to reduced intracellular pool of the aromatic amino acids. In this review, advances in metabolic engineering for the production of the aromatic amino acids and useful aromatic intermediates are described with particular emphasis on two representative producer organisms, Corynebacterium glutamicum and Escherichia coli.