Egils Stalidzans

Paint4Net: COBRA Toolbox extension for visualization of stoichiometric models of metabolism

A visual analysis of reconstructions and large stoichiometric models with elastic change of the visualization scope and representation methods becomes increasingly important due to the rapidly growing size and number of available reconstructions. The Paint4Net is a novel COBRA Toolbox extension for automatic generation of a hypergraph layout of defined scope with the steady state rates of reaction fluxes of stoichiometric models. Directionalities and fluxes of reactions are constantly represented in the visualization while detailed information about reaction (ID, name and synonyms, and formula) and metabolite (ID, name and synonyms, and charged formula) appears placing the cursor on the item of interest. Additionally Paint4Net functionality can be used to: (1) get lists of involved metabolites and dead end metabolites of the visualized part of the network, (2) exclude (filter) particular metabolites from representation, (3) find isolated parts of a network and (4) find running cycles when all the substrates are cut down. Layout pictures can be saved in various formats and easily distributed. The Paint4Net is open source software under the GPL v3 license. Relevant documentation and sample data is available at http://www.biosystems.lv/paint4net. The Paint4Net works on MATLAB starting from version of 2009.

Biotechnological potential of respiring Zymomonas mobilis: A stoichiometric analysis of its central metabolism

The active, yet energetically inefficient electron transport chain of the ethanologenic bacterium Zymomonas mobilis could be used in metabolic engineering for redox-balancing purposes during synthesis of certain products. Although several reconstructions of Z. mobilis metabolism have been published, important aspects of redox balance and aerobic catabolism have not previously been considered. Here, annotated genome sequences and metabolic reconstructions have been combined with existing biochemical evidence to yield a medium-scale model of Z. mobilis central metabolism in the form of COBRA Toolbox model files for flux balance analysis (FBA). The stoichiometric analysis presented here suggests the feasibility of several metabolic engineering strategies for obtaining high-value products, such as glycerate, succinate, and glutamate that would use the electron transport chain to oxidize the excess NAD(P)H, generated during synthesis of these metabolites. Oxidation of the excess NAD(P)H would also be needed for synthesis of ethanol from glycerol. Maximum product yields and the byproduct spectra have been estimated for each product, with glucose, xylose, or glycerol as the carbon substrates. These novel pathways represent targets for future metabolic engineering, as they would exploit both the rapid Entner-Doudoroff glycolysis, and the energetically uncoupled electron transport of Z. mobilis.

Kinetic modelling of the Zymomonas mobilis Entner-Doudoroff pathway: insights into control and functionality

Zymomonas mobilis, an ethanol-producing bacterium, possesses the Entner-Doudoroff (E-D) pathway, pyruvate decarboxylase and two alcohol dehydrogenase isoenzymes for the fermentative production of ethanol and carbon dioxide from glucose. Using available kinetic parameters, we have developed a kinetic model that incorporates the enzymic reactions of the E-D pathway, both alcohol dehydrogenases, transport reactions and reactions related to ATP metabolism. After optimizing the reaction parameters within likely physiological limits, the resulting kinetic model was capable of simulating glycolysis in vivo and in cell-free extracts with good agreement with the fluxes and steady-state intermediate concentrations reported in previous experimental studies. In addition, the model is shown to be consistent with experimental results for the coupled response of ATP concentration and glycolytic flux to ATPase inhibition. Metabolic control analysis of the model revealed that the majority of flux control resides not inside, but outside the E-D pathway itself, predominantly in ATP consumption, demonstrating why past attempts to increase the glycolytic flux through overexpression of glycolytic enzymes have been unsuccessful. Co-response analysis indicates how homeostasis of ATP concentrations starts to deteriorate markedly at the highest glycolytic rates. This kinetic model has potential for application in Z. mobilis metabolic engineering and, since there are currently no E-D pathway models available in public databases, it can serve as a basis for the development of models for other micro-organisms possessing this type of glycolytic pathway.

Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies

Mathematical modeling of metabolism is essential for rational metabolic engineering. The present work focuses on several types of modeling approach to quantitative understanding of central metabolic network and energetics in the bioethanol-producing bacterium Zymomonas mobilis. Combined use of Flux Balance, Elementary Flux Mode, and thermodynamic analysis of its central metabolism, together with dynamic modeling of the core catabolic pathways, can help to design novel substrate and product pathways by systematically analyzing the solution space for metabolic engineering, and yields insights into the function of metabolic network, hardly achievable without applying modeling tools.

ConvAn: A convergence analyzing tool for optimization of biochemical networks

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan.

Convergence dynamics of biochemical pathway steady state stochastic global optimization

The stochastic nature of convergence of steady state stochastic global optimization methods in design optimization tasks with steady state precondition is a hardly predictable step in development of industrially efficient strains of microorganisms.

Strategies for structuring interdisciplinary education in Systems Biology: an European perspective

Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii) a description of possible career paths for students who undergo such an education, (iv) conditions that should improve the recruitment of students to such programmes and (v) mechanisms for collaboration and excellence spreading among education professionals. With the growing interest of industry in applying Systems Biology approaches in their fields, a concerted action between academia and industry is needed to build this expertise. Here we present a reflection of the European situation and expertise, where most of the challenges we discuss are universal, anticipating that our suggestions will be useful internationally. We believe that one of the overriding goals of any Systems Biology education should be a student’s ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively across different experimental and theoretical disciplines in research and development.

Model-based biotechnological potential analysis of Kluyveromyces marxianus central metabolism

The non-conventional yeast Kluyveromyces marxianus is an emerging industrial producer for many biotechnological processes. Here, we show the application of a biomass-linked stoichiometric model of central metabolism that is experimentally validated, and mass and charge balanced for assessing the carbon conversion efficiency of wild type and modified K. marxianus. Pairs of substrates (lactose, glucose, inulin, xylose) and products (ethanol, acetate, lactate, glycerol, ethyl acetate, succinate, glutamate, phenylethanol and phenylalanine) are examined by various modelling and optimisation methods. Our model reveals the organism’s potential for industrial application and metabolic engineering. Modelling results imply that the aeration regime can be used as a tool to optimise product yield and flux distribution in K. marxianus. Also rebalancing NADH and NADPH utilisation can be used to improve the efficiency of substrate conversion. Xylose is identified as a biotechnologically promising substrate for K. marxianus.

Search for a Minimal Set of Parameters by Assessing the Total Optimization Potential for a Dynamic Model of a Biochemical Network

Selecting an efficient small set of adjustable parameters to improve metabolic features of an organism is important for a reduction of implementation costs and risks of unpredicted side effects. In practice, to avoid the analysis of a huge combinatorial space for the possible sets of adjustable parameters, experience-, and intuition-based subsets of parameters are often chosen, possibly leaving some interesting counter-intuitive combinations of parameters unrevealed. The combinatorial scan of possible adjustable parameter combinations at the model optimization level is possible; however, the number of analyzed combinations is still limited. The total optimization potential (TOP) approach is proposed to assess the full potential for increasing the value of the objective function by optimizing all possible adjustable parameters. This seemingly unpractical combination of adjustable parameters allows assessing the maximum attainable value of the objective function and stopping the combinatorial space scanning when the desired fraction of TOP is reached and any further increase in the number of adjustable parameters cannot bring any reasonable improvement. The relation between the number of adjustable parameters and the reachable fraction of TOP is a valuable guideline in choosing a rational solution for industrial implementation. The TOP approach is demonstrated on the basis of two case studies.

Two stage optimization of biochemical pathways using parallel runs of global stochastic optimization methods

A disadvantage of global stochastic optimization methods is the stochastic convergence of the best value of the objective function to the global optimum. In spite those methods are widely used optimizing kinetic models of biochemical pathways. Moreover, the growing number of adjustable parameters in the model leads to combinatorial explosion of combinations of adjustable parameters if the best combination per number of adjustable parameters in the combination has to be found. Two stage optimization using automatic optimization termination criteria of parallel optimization runs in case of consensus is proposed in this paper to reduce the duration of scanning. The application of this method is demonstrated solving biotechnologically relevant task - maximization of bioethanol production rate in the yeast glycolysis model. The experimental results underline the efficiency of two stage approach using parallel runs and consensus criteria.