References of "Ebenhoh, Oliver"
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See detailThe intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling
Pfau, Thomas UL; Christian, Nils UL; Masakapalli, Shyam K. et al

in Scientific Reports (2018), 8

Genome-scale metabolic network models can be used for various analyses including the prediction of metabolic responses to changes in the environment. Legumes are well known for their rhizobial symbiosis ... [more ▼]

Genome-scale metabolic network models can be used for various analyses including the prediction of metabolic responses to changes in the environment. Legumes are well known for their rhizobial symbiosis that introduces nitrogen into the global nutrient cycle. Here, we describe a fully compartmentalised, mass and charge-balanced, genome-scale model of the clover Medicago truncatula, which has been adopted as a model organism for legumes. We employed flux balance analysis to demonstrate that the network is capable of producing biomass components in experimentally observed proportions, during day and night. By connecting the plant model to a model of its rhizobial symbiont, Sinorhizobium meliloti, we were able to investigate the effects of the symbiosis on metabolic fluxes and plant growth and could demonstrate how oxygen availability influences metabolic exchanges between plant and symbiont, thus elucidating potential benefits of inter organism amino acid cycling. We thus provide a modelling framework, in which the interlinked metabolism of plants and nodules can be studied from a theoretical perspective. [less ▲]

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See detailData-driven dynamical model indicates that the heat shock response in Chlamydomonas reinhardtii is tailored to handle natural temperature variation
Magni, Stefano UL; Succurro, Antonella; Skupin, Alexander UL et al

in Journal of the Royal Society, Interface (2018), 15(142), 20170965

Global warming exposes plants to severe heat stress, with consequent crop yield reduction. Organisms exposed to high temperature stresses typically protect themselves with a heat shock response (HSR ... [more ▼]

Global warming exposes plants to severe heat stress, with consequent crop yield reduction. Organisms exposed to high temperature stresses typically protect themselves with a heat shock response (HSR), where accumulation of unfolded proteins initiates the synthesis of heat shock proteins through the heat shock transcription factor HSF1. While the molecular mechanisms are qualitatively well characterized, our quantitative understanding of the under- lying dynamics is still very limited. Here, we study the dynamics of HSR in the photosynthetic model organism Chlamydomonas reinhardtii with a data-driven mathematical model of HSR. We based our dynamical model mostly on mass action kinetics, with a few nonlinear terms. The model was parametrized and validated by several independent datasets obtained from the literature. We demonstrate that HSR quantitatively and significantly differs if an increase in temperature of the same magnitude occurs abruptly, as often applied under laboratory conditions, or gradually, which would rather be expected under natural conditions. In contrast to rapid temperature increases, under gradual changes only negligible amounts of misfolded proteins accumulate, indicating that the HSR of C. reinhardtii efficiently avoids the accumulation of misfolded proteins under conditions most likely to prevail in nature. The mathematical model we developed is a flexible tool to simulate the HSR to different conditions and complements the current experimental approaches. [less ▲]

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See detailA systems-wide understanding of photosynthetic acclimation in algae and higher plants
Wanjiku Moejes, Fiona; Matuszyńska, Anna; Adhikari, Kailash et al

in Journal of Experimental Botany (2017), 68(11), 26672681

The ability of phototrophs to colonise different environments relies on robust protection against oxidative stress, a critical requirement for the successful evolutionary transition from water to land ... [more ▼]

The ability of phototrophs to colonise different environments relies on robust protection against oxidative stress, a critical requirement for the successful evolutionary transition from water to land. Photosynthetic organisms have developed numerous strategies to adapt their photosynthetic apparatus to changing light conditions in order to optimise their photosynthetic yield, which is crucial for life on Earth to exist. Photosynthetic acclimation is an excellent example of the complexity of biological systems, where highly diverse processes, ranging from electron excitation over protein protonation to enzymatic processes coupling ion gradients with biosynthetic activity, interact on drastically different timescales from picoseconds to hours. Efficient functioning of the photosynthetic apparatus and its protection is paramount for efficient downstream processes, including metabolism and growth. Modern experimental techniques can be successfully integrated with theoretical and mathematical models to promote our understanding of underlying mechanisms and principles. This review aims to provide a retrospective analysis of multidisciplinary photosynthetic acclimation research carried out by members of the Marie Curie Initial Training Project, AccliPhot, placing the results in a wider context. The review also highlights the applicability of photosynthetic organisms for industry, particularly with regards to the cultivation of microalgae. It intends to demonstrate how theoretical concepts can successfully complement experimental studies broadening our knowledge of common principles in acclimation processes in photosynthetic organisms, as well as in the field of applied microalgal biotechnology. [less ▲]

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See detailInsight into metabolic pathways of the potential biofuel producer, Paenibacillus polymyxa ICGEB2008
Adlakha, Nidhi; Pfau, Thomas UL; Ebenhöh, Oliver et al

in Biotechnology for Biofuels (2015), 8(159),

Background Paenibacillus polymyxa is a facultative anaerobe known for production of hydrolytic enzymes and various important biofuel molecules. Despite its wide industrial use and the availability of its ... [more ▼]

Background Paenibacillus polymyxa is a facultative anaerobe known for production of hydrolytic enzymes and various important biofuel molecules. Despite its wide industrial use and the availability of its genome sequence, very little is known about metabolic pathways operative in the Paenibacillus system. Here, we report metabolic insights of an insect gut symbiont, Paenibacillus polymyxa ICGEB2008, and reveal pathways playing an important role in the production of 2,3-butanediol and ethanol. Result We developed a metabolic network model of P. polymyxa ICGEB2008 with 133 metabolites and 158 reactions. Flux balance analysis was employed to investigate the importance of redox balance in ICGEB2008. This led to the detection of the Bifid shunt, a pathway previously not described in Paenibacillus, which can uncouple the production of ATP from the generation of reducing equivalents. Using a combined experimental and modeling approach, we further studied pathways involved in 2,3-butanediol and ethanol production and also demonstrated the production of hydrogen by the organism. We could further show that the nitrogen source is critical for metabolite production by Paenibacillus, and correctly quantify the influence on the by-product metabolite profile of ICGEB2008. Both simulations and experiments showed that metabolic flux is diverted from ethanol to acetate production when an oxidized nitrogen source is utilized. Conclusion We have created a predictive model of the central carbon metabolism of P. polymyxa ICGEB2008 and could show the presence of the Bifid shunt and explain its role in ICGEB2008. An in-depth study has been performed to understand the metabolic pathways involved in ethanol, 2,3-butanediol and hydrogen production, which can be utilized as a basis for further metabolic engineering efforts to improve the efficiency of biofuel production by this P. polymyxa strain. [less ▲]

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See detailMesoscopic behavior from microscopic Markov dynamics and its application to calcium release channels.
Christian, Nils UL; Skupin, Alexander UL; Morante, Silvia et al

in Journal of Theoretical Biology (2014), 343

A major challenge in biology is to understand how molecular processes determine phenotypic features. We address this fundamental problem in a class of model systems by developing a general mathematical ... [more ▼]

A major challenge in biology is to understand how molecular processes determine phenotypic features. We address this fundamental problem in a class of model systems by developing a general mathematical framework that allows the calculation of mesoscopic properties from the knowledge of microscopic Markovian transition probabilities. We show how exact analytic formulae for the first and second moments of resident time distributions in mesostates can be derived from microscopic resident times and transition probabilities even for systems with a large number of microstates. We apply our formalism to models of the inositol trisphosphate receptor, which plays a key role in generating calcium signals triggering a wide variety of cellular responses. We demonstrate how experimentally accessible quantities such as opening and closing times and the coefficient of variation of inter-spike intervals, and other, more elaborated, quantities can be analytically calculated from the underlying microscopic Markovian dynamics. A virtue of our approach is that we do not need to follow the detailed time evolution of the whole system, as we derive the relevant properties of its steady state without having to take into account the often extremely complicated transient features. We emphasize that our formulae fully agree with results obtained by stochastic simulations and approaches based on a full determination of the microscopic system's time evolution. We also illustrate how experiments can be devised to discriminate between alternative molecular models of the inositol trisphosphate receptor. The developed approach is applicable to any system described by a Markov process and, owing to the analytic nature of the resulting formulae, provides an easy way to characterize also rare events that are of particular importance to understand the intermittency properties of complex dynamic systems. [less ▲]

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See detailSystems approaches to modelling pathways and networks
Pfau, Thomas UL; Christian, Nils UL; Ebenhöh, Oliver

in Briefings in Functional Genomics (2011), 10(5), 266-279

It has become commonly accepted that systems approaches to biology are of outstanding importance to gain understanding from the vast amount of data which is presently being generated by advancing high ... [more ▼]

It has become commonly accepted that systems approaches to biology are of outstanding importance to gain understanding from the vast amount of data which is presently being generated by advancing high-throughput technologies. The diversity of methods to model pathways and networks has significantly expanded over the past two decades. Modern and traditional approaches are equally important and recent activities aim at integrating the advantages of both. While traditional methods, based on differential equations, are useful to study the dynamics of small systems, modern constraint-based models can be applied to genome-scale systems, but are not able to capture dynamic features. Integrating different approaches is important to develop consistent theoretical descriptions encompassing various scales of biological information. The rapid progress of the field of theoretical systems biology, however, demonstrates how our fundamental theoretical understanding of biology is gaining momentum. The scientific community has apparently accepted the challenge to truly understand the principles of life. [less ▲]

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See detailIntegration of proteomic and metabolomic profiling as well as metabolic modeling for the functional analysis of metabolic networks.
May, Patrick UL; Christian, Nils UL; Ebenhoh, Oliver et al

in Methods in Molecular Biology (Clifton, N.J.) (2011), 694

The integrated analysis of different omics-level data sets is most naturally performed in the context of common process or pathway association. In this chapter, the two basic approaches for a metabolic ... [more ▼]

The integrated analysis of different omics-level data sets is most naturally performed in the context of common process or pathway association. In this chapter, the two basic approaches for a metabolic pathway-centric integration of proteomics and metabolomics data are described: the knowledge-based approach relying on existing metabolic pathway information, and a data-driven approach that aims to deduce functional (pathway) associations directly from the data. Relevant algorithmic approaches for the generation of metabolic networks of model organisms, their functional analysis, database resources, visualization and analysis tools will be described. The use of proteomics data in the process of metabolic network reconstruction will be discussed. [less ▲]

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See detailModeling the complex dynamics of enzyme-pathway coevolution.
Schutte, Moritz; Skupin, Alexander UL; Segre, Daniel et al

in Chaos (2010), 20(4), 045115

Metabolic pathways must have coevolved with the corresponding enzyme gene sequences. However, the evolutionary dynamics ensuing from the interplay between metabolic networks and genomes is still poorly ... [more ▼]

Metabolic pathways must have coevolved with the corresponding enzyme gene sequences. However, the evolutionary dynamics ensuing from the interplay between metabolic networks and genomes is still poorly understood. Here, we present a computational model that generates putative evolutionary walks on the metabolic network using a parallel evolution of metabolic reactions and their catalyzing enzymes. Starting from an initial set of compounds and enzymes, we expand the metabolic network iteratively by adding new enzymes with a probability that depends on their sequence-based similarity to already present enzymes. Thus, we obtain simulated time courses of chemical evolution in which we can monitor the appearance of new metabolites, enzyme sequences, or even entire organisms. We observe that new enzymes do not appear gradually but rather in clusters which correspond to enzyme classes. A comparison with Brownian motion dynamics indicates that our system displays biased random walks similar to diffusion on the metabolic network with long-range correlations. This suggests that a quantitative molecular principle may underlie the appearance of punctuated equilibrium dynamics, whereby enzymes occur in bursts rather than by phyletic gradualism. Moreover, the simulated time courses lead to a putative time-order of enzyme and organism appearance. Among the patterns we detect in these evolutionary trends is a significant correlation between the time of appearance and their enzyme repertoire size. Hence, our approach to metabolic evolution may help understand the rise in complexity at the biochemical and genomic levels. [less ▲]

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See detailAn integrative approach towards completing genome-scale metabolic networks.
Christian, Nils UL; May, Patrick UL; Kempa, Stefan et al

in Molecular Biosystems (2009), 5(12), 1889-903

Genome-scale metabolic networks which have been automatically derived through sequence comparison techniques are necessarily incomplete. We propose a strategy that incorporates genomic sequence data and ... [more ▼]

Genome-scale metabolic networks which have been automatically derived through sequence comparison techniques are necessarily incomplete. We propose a strategy that incorporates genomic sequence data and metabolite profiles into modeling approaches to arrive at improved gene annotations and more complete genome-scale metabolic networks. The core of our strategy is an algorithm that computes minimal sets of reactions by which a draft network has to be extended in order to be consistent with experimental observations. A particular strength of our approach is that alternative possibilities are suggested and thus experimentally testable hypotheses are produced. We carefully evaluate our strategy on the well-studied metabolic network of Escherichia coli, demonstrating how the predictions can be improved by incorporating sequence data. Subsequently, we apply our method to the recently sequenced green alga Chlamydomonas reinhardtii. We suggest specific genes in the genome of Chlamydomonas which are the strongest candidates for coding the responsible enzymes. [less ▲]

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See detailMetabolomics- and proteomics-assisted genome annotation and analysis of the draft metabolic network of Chlamydomonas reinhardtii.
May, Patrick UL; Wienkoop, Stefanie; Kempa, Stefan et al

in Genetics (2008), 179(1), 157-66

We present an integrated analysis of the molecular repertoire of Chlamydomonas reinhardtii under reference conditions. Bioinformatics annotation methods combined with GCxGC/MS-based metabolomics and LC/MS ... [more ▼]

We present an integrated analysis of the molecular repertoire of Chlamydomonas reinhardtii under reference conditions. Bioinformatics annotation methods combined with GCxGC/MS-based metabolomics and LC/MS-based shotgun proteomics profiling technologies have been applied to characterize abundant proteins and metabolites, resulting in the detection of 1069 proteins and 159 metabolites. Of the measured proteins, 204 currently do not have EST sequence support; thus a significant portion of the proteomics-detected proteins provide evidence for the validity of in silico gene models. Furthermore, the generated peptide data lend support to the validity of a number of proteins currently in the proposed model stage. By integrating genomic annotation information with experimentally identified metabolites and proteins, we constructed a draft metabolic network for Chlamydomonas. Computational metabolic modeling allowed an identification of missing enzymatic links. Some experimentally detected metabolites are not producible by the currently known and annotated enzyme set, thus suggesting entry points for further targeted gene discovery or biochemical pathway research. All data sets are made available as supplementary material as well as web-accessible databases and within the functional context via the Chlamydomonas-adapted MapMan annotation platform. Information of identified peptides is also available directly via the JGI-Chlamydomonas genomic resource database (http://genome.jgi-psf.org/Chlre3/Chlre3.home.html). [less ▲]

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