Magdeburg Center for Systems Biology

Magdeburg, Germany

Magdeburg Center for Systems Biology

Magdeburg, Germany
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Franz A.,Max Planck Institute for Dynamics of Complex Technical Systems | Franz A.,Magdeburg Center for Systems Biology | Rehner R.,Max Planck Institute for Dynamics of Complex Technical Systems | Rehner R.,Magdeburg Center for Systems Biology | And 5 more authors.
Letters in Applied Microbiology | Year: 2012

Aims: The application of Ralstonia eutropha H16 for producing polyhydroxyalkanoates as bioplastics is limited by the incapability of the bacterium to utilize glucose as a growth substrate. This study aims in characterizing glucose-utilizing strains that arose after incubation with high glucose levels, in comparison with previously published mutants, generated either by mutagenesis or by metabolic engineering. Methods and Results: Cultivations on solid and liquid media showed that the application of high substrate concentrations rapidly induced a glucose-positive phenotype. The time span until the onset of growth and the frequency of glucose-utilizing colonies were correlated to the initial glucose concentration. All mutants exhibited elevated activities of glucose-6-phosphate dehydrogenase. The glucose-positive phenotype was abolished after deleting genes for the N-acetylglucosamine phosphotransferase system. Conclusions: A procedure is provided for selecting glucose-utilizing R. eutropha H16 in an unprecedented short time period and without any mutagenic treatment. An altered N-acetylglucosamine phosphotransferase system appears to be a common motif in all glucose-utilizing mutants examined so far. Significance and Impact of the Study: The correlation of the applied glucose concentration and the appearance of glucose-utilizing mutants poses questions about the randomness or the specificity of adaptive mutations in general. Furthermore, glucose-adapted strains of R. eutropha H16 could be useful for the production of bioplastics. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

Hadicke O.,Max Planck Institute for Dynamics of Complex Technical Systems | Hadicke O.,Magdeburg Center for Systems Biology | Klamt S.,Max Planck Institute for Dynamics of Complex Technical Systems | Klamt S.,Magdeburg Center for Systems Biology
Metabolic Engineering | Year: 2011

The model-driven search for gene deletion strategies that increase the production performance of microorganisms is an essential part of metabolic engineering. One theoretical approach is based on Minimal Cut Sets (MCSs) which are minimal sets of knockouts disabling the operation of a specified set of target elementary modes. A limitation of the current approach is that MCSs can induce side effects disabling also desired functionalities. We, therefore, generalize MCSs to Constrained MCSs (cMCSs) allowing for the additional definition of a set of desired modes of which a minimum number must be preserved. Exemplarily for ethanol production by Escherichia coli, we demonstrate that this approach offers enormous flexibility in defining and solving knockout problems. Moreover, many existing methods can be reformulated as special cMCS problems. The cMCSs approach allows systematic enumeration of all equivalent gene deletion combinations and also helps to determine robust knockout strategies for coupled product and biomass synthesis. © 2010 Elsevier Inc.

Franz A.,Max Planck Institute for Dynamics of Complex Technical Systems | Franz A.,Magdeburg Center for Systems Biology | Song H.-S.,Purdue University | Ramkrishna D.,Purdue University | And 3 more authors.
Biochemical Engineering Journal | Year: 2011

In this paper a mathematical model is presented to describe poly(β-hydroxybutyrate) (PHB) formation and consumption in Ralstonia eutropha. The model is based on the hybrid cybernetic modeling approach, which was introduced by Kim et al. [1] and which allows a systematic derivation of the model equations from elementary mode analysis. An extension of this approach is presented to allow for non quasi-stationary metabolites, i.e. PHB. The model is shown to be in good agreement with experimental data for PHB formation and consumption. The model is used afterwards to discuss the occurrence of multiple steady states in a continuous bio reactor. It is shown that the multiplicity region predicted by the model is rather small and it is argued that multiple steady states are therefore unlikely to occur in practice for this specific system. Due to various desirable features such as accounting for cellular regulation at network level and dynamics of intracellular metabolites with a moderate complexity, it is believed that the constructed model is most suitable for control, optimization and monitoring of industrial PHB production processes. © 2011 Elsevier B.V.

Klamt S.,Max Planck Institute for Dynamics of Complex Technical Systems | Klamt S.,Magdeburg Center for Systems Biology | Flassig R.J.,Max Planck Institute for Dynamics of Complex Technical Systems | Sundmacher K.,Max Planck Institute for Dynamics of Complex Technical Systems | Sundmacher K.,Otto Von Guericke University of Magdeburg
Bioinformatics | Year: 2010

Motivation: Distinguishing direct from indirect influences is a central issue in reverse engineering of biological networks because it facilitates detection and removal of false positive edges. Transitive reduction is one approach for eliminating edges reflecting indirect effects but its use in reconstructing cyclic interaction graphs with true redundant structures is problematic. Results: We present TRANSWESD, an elaborated variant of TRANSitive reduction for WEighted Signed Digraphs that overcomes conceptual problems of existing versions. Major changes and improvements concern: (i) new statistical approaches for generating high-quality perturbation graphs from systematic perturbation experiments; (ii) the use of edge weights (association strengths) for recognizing true redundant structures; (iii) causal interpretation of cycles; (iv) relaxed definition of transitive reduction; and (v) approximation algorithms for large networks. Using standardized benchmark tests, we demonstrate that our method outperforms existing variants of transitive reduction and is, despite its conceptual simplicity, highly competitive with other reverse engineering methods. © The Author(s) 2010. Published by Oxford University Press.

Klamt S.,Max Planck Institute for Dynamics of Complex Technical Systems | Klamt S.,Magdeburg Center for Systems Biology | von Kamp A.,Max Planck Institute for Dynamics of Complex Technical Systems | von Kamp A.,Magdeburg Center for Systems Biology
BioSystems | Year: 2011

CellNetAnalyzer (CNA) is a MATLAB toolbox providing computational methods for studying structure and function of metabolic and cellular signaling networks. In order to allow non-experts to use these methods easily, CNA provides GUI-based interactive network maps as a means of parameter input and result visualization. However, with the availability of high-throughput data, there is a need to make CNA's functionality also accessible in batch mode for automatic data processing. Furthermore, as some algorithms of CNA are of general relevance for network analysis it would be desirable if they could be called as sub-routines by other applications. For this purpose, we developed an API (application programming interface) for CNA allowing users (i) to access the content of network models in CNA, (ii) to use CNA's network analysis capabilities independent of the GUI, and (iii) to interact with the GUI to facilitate the development of graphical plugins.Here we describe the organization of network projects in CNA and the application of the new API functions to these projects. This includes the creation of network projects from scratch, loading and saving of projects and scenarios, and the application of the actual analysis methods. Furthermore, API functions for the import/export of metabolic models in SBML format and for accessing the GUI are described. Lastly, two example applications demonstrate the use and versatile applicability of CNA's API. CNA is freely available for academic use and can be downloaded from © 2011 Elsevier Ireland Ltd.

Carius A.B.,Max Planck Institute for Dynamics of Complex Technical Systems | Henkel M.,Magdeburg Center for Systems Biology | Grammel H.,Max Planck Institute for Dynamics of Complex Technical Systems
Journal of Bacteriology | Year: 2011

The formation of intracytoplasmic photosynthetic membranes by facultative anoxygenic photosynthetic bacteria has become a prime example for exploring redox control of gene expression in response to oxygen and light. Although a number of redox-responsive sensor proteins and transcription factors have been characterized in several species during the last several years in some detail, the overall understanding of the metabolic events that determine the cellular redox environment and initiate redox signaling is still poor. In the present study we demonstrate that in Rhodospirillum rubrum, the amount of photosynthetic membranes can be drastically elevated by external supplementation of the growth medium with the low-molecular-weight thiol glutathione. Neither the widely used reductant dithiothreitol nor oxidized glutathione caused the same response, suggesting that the effect was specific for reduced glutathione. By determination of the extracellular and intracellular glutathione levels, we correlate the GSH/GSSG redox potential to the expression level of photosynthetic membranes. Possible regulatory interactions with periplasmic, membrane, and cytosolic proteins are discussed. Furthermore, we found that R. rubrum cultures excrete substantial amounts of glutathione to the environment. © 2011, American Society for Microbiology.

Hadicke O.,Max Planck Institute for Dynamics of Complex Technical Systems | Hadicke O.,Magdeburg Center for Systems Biology | Grammel H.,Max Planck Institute for Dynamics of Complex Technical Systems | Grammel H.,Magdeburg Center for Systems Biology | And 2 more authors.
BMC Systems Biology | Year: 2011

Background: Purple nonsulfur bacteria (PNSB) are facultative photosynthetic bacteria and exhibit an extremely versatile metabolism. A central focus of research on PNSB dealt with the elucidation of mechanisms by which they manage to balance cellular redox under diverse conditions, in particular under photoheterotrophic growth.Results: Given the complexity of the central metabolism of PNSB, metabolic modeling becomes crucial for an integrated analysis of the accumulated biological knowledge. We reconstructed a stoichiometric model capturing the central metabolism of three important representatives of PNSB (Rhodospirillum rubrum, Rhodobacter sphaeroides and Rhodopseudomonas palustris). Using flux variability analysis, the model reveals key metabolic constraints related to redox homeostasis in these bacteria. With the help of the model we can (i) give quantitative explanations for non-intuitive, partially species-specific phenomena of photoheterotrophic growth of PNSB, (ii) reproduce various quantitative experimental data, and (iii) formulate several new hypotheses. For example, model analysis of photoheterotrophic growth reveals that - despite a large number of utilizable catabolic pathways - substrate-specific biomass and CO 2yields are fixed constraints, irrespective of the assumption of optimal growth. Furthermore, our model explains quantitatively why a CO 2fixing pathway such as the Calvin cycle is required by PNSB for many substrates (even if CO 2is released). We also analyze the role of other pathways potentially involved in redox metabolism and how they affect quantitatively the required capacity of the Calvin cycle. Our model also enables us to discriminate between different acetate assimilation pathways that were proposed recently for R. sphaeroides and R. rubrum, both lacking the isocitrate lyase. Finally, we demonstrate the value of the metabolic model also for potential biotechnological applications: we examine the theoretical capabilities of PNSB for photoheterotrophic hydrogen production and identify suitable genetic interventions to increase the hydrogen yield.Conclusions: Taken together, the metabolic model (i) explains various redox-related phenomena of the versatile metabolism of PNSB, (ii) delivers new hypotheses on the operation and relevance of several metabolic pathways, and (iii) holds significant potential as a tool for rational metabolic engineering of PNSB in biotechnological applications. © 2011 Hädicke et al; licensee BioMed Central Ltd.

Hadicke O.,Max Planck Institute for Dynamics of Complex Technical Systems | Hadicke O.,Magdeburg Center for Systems Biology | Klamt S.,Max Planck Institute for Dynamics of Complex Technical Systems | Klamt S.,Magdeburg Center for Systems Biology
Journal of Biotechnology | Year: 2010

The identification of suitable intervention strategies increasing the productivity of microorganisms is a central issue in metabolic engineering. Here, we introduce a computational framework for strain optimization based on reaction importance measures derived from weighted elementary modes. The objective is to shift the natural flux distribution to synthesis of the desired product with high production rates thereby retaining the ability of the host organism to produce biomass precursors. The stoichiometric approach allows consideration of regulatory/operational constraints and takes product yield and network capacity - the two major determinants of (specific) productivity - explicitly into account. The relative contribution of each reaction to yield and network capacity and thus productivity is estimated by analyzing the spectrum of available conversion routes (elementary modes). A result of our procedure is a reaction ranking suggesting knockout and overexpression candidates. Moreover, we show that the methodology allows for the evaluation of cofactor and co-metabolite requirements in conjunction with product synthesis. We illustrate the proposed method by studying the overproduction of succinate and lactate by Escherichia coli. The metabolic engineering strategies identified in silico resemble existing mutant strains designed for the synthesis of the respective products. Additionally, some non-intuitive intervention strategies are revealed. © 2010 Elsevier B.V.

Heiner M.,TU Brandenburg | Rohr C.,Magdeburg Center for Systems Biology | Schwarick M.,TU Brandenburg | Streif S.,Magdeburg Center for Systems Biology
CMSB 2010 - Proceedings of the 8th International Conference on Computational Methods in Systems Biology | Year: 2010

Stochastic models are becoming increasingly popular in Systems Biology. They are compulsory, if the stochastic noise is crucial for the behavioural properties to be investigated. Thus, substantial effort has been made to develop appropriate and efficient stochastic analysis techniques. The impressive progress of hardware power and specifically the advent of multicore computers have ameliorated the computational tractability of stochastic models. We report on a comparative study focusing on the three base case techniques of stochastic analysis: exact numerical analysis, approximative numerical analysis, and simulation. For modelling we use extended stochastic Petri nets, which allows us to take advantage of structural information and to complement the stochastic analyses by qualitative analyses, belonging to the standard body of Petri net theory. Copyright 2010 ACM.

Schwarick M.,TU Brandenburg | Heiner M.,TU Brandenburg | Rohr C.,Magdeburg Center for Systems Biology
Proceedings of the 2011 8th International Conference on Quantitative Evaluation of Systems, QEST 2011 | Year: 2011

MARCIE is a multi-threaded tool for the analysis of Generalized Stochastic Petri Nets. Its capabilities range from standard properties of qualitative Petri nets to CTL and CSL model checking, recently extended by rewards. The core of MARCIE builds upon Interval Decision Diagrams for the symbolic representation of marking sets of bounded Petri nets (finite state space) and on-the-fly matrix computation for numerical analysis. Approximative engines supporting fast adaptive uniformization and Gillespie simulation open the door to quantitative reasoning on unbounded Petri nets (infinite state space). This paper presents MARCIE's architecture and its most important distinguishing features. Extensive computational experiments demonstrate MARCIE''s strength in comparison with related tools. © 2011 IEEE.

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