Amsterdam Institute for Molecules

Amsterdam, Netherlands

Amsterdam Institute for Molecules

Amsterdam, Netherlands
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Hanemaaijer M.,Amsterdam Institute for Molecules | Olivier B.G.,Amsterdam Institute for Molecules | Roling W.F.M.,Amsterdam Institute for Molecules | Bruggeman F.J.,Amsterdam Institute for Molecules | Teusink B.,Amsterdam Institute for Molecules
PLoS ONE | Year: 2017

An important challenge in microbial ecology is to infer metabolic-exchange fluxes between growing microbial species from community-level data, concerning species abundances and metabolite concentrations. Here we apply a model-based approach to integrate such experimental data and thereby infer metabolic-exchange fluxes. We designed a synthetic anaerobic co-culture of Clostridium acetobutylicum and Wolinella succinogenes that interact via interspecies hydrogen transfer and applied different environmental conditions for which we expected the metabolic-exchange rates to change. We used stoichiometric models of the metabolism of the two microorganisms that represents our current physiological understanding and found that this understanding - the model - is sufficient to infer the identity and magnitude of the metabolic-exchange fluxes and it suggested unexpected interactions. Where the model could not fit all experimental data, it indicates specific requirement for further physiological studies. We show that the nitrogen source influences the rate of interspecies hydrogen transfer in the co-culture. Additionally, the model can predict the intracellular fluxes and optimal metabolic exchange rates, which can point to engineering strategies. This study therefore offers a realistic illustration of the strengths and weaknesses of modelbased integration of heterogenous data that makes inference of metabolic-exchange fluxes possible from community-level experimental data. © 2017 Hanemaaijer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Haagsma A.C.,VU University Amsterdam | Haagsma A.C.,Amsterdam Institute for Molecules | Podasca I.,VU University Amsterdam | Podasca I.,Amsterdam Institute for Molecules | And 7 more authors.
PLoS ONE | Year: 2011

Infections with Mycobacterium tuberculosis are substantially increasing on a worldwide scale and new antibiotics are urgently needed to combat concomitantly emerging drug-resistant mycobacterial strains. The diarylquinoline TMC207 is a highly promising drug candidate for treatment of tuberculosis. This compound kills M. tuberculosis by binding to a new target, mycobacterial ATP synthase. In this study we used biochemical assays and binding studies to characterize the interaction between TMC207 and ATP synthase. We show that TMC207 acts independent of the proton motive force and does not compete with protons for a common binding site. The drug is active on mycobacterial ATP synthesis at neutral and acidic pH with no significant change in affinity between pH 5.25 and pH 7.5, indicating that the protonated form of TMC207 is the active drug entity. The interaction of TMC207 with ATP synthase can be explained by a one-site binding mechanism, the drug molecule thus binds to a defined binding site on ATP synthase. TMC207 affinity for its target decreases with increasing ionic strength, suggesting that electrostatic forces play a significant role in drug binding. Our results are consistent with previous docking studies and provide experimental support for a predicted function of TMC207 in mimicking key residues in the proton transfer chain and blocking rotary movement of subunit c during catalysis. Furthermore, the high affinity of TMC207 at low proton motive force and low pH values may in part explain the exceptional ability of this compound to efficiently kill mycobacteria in different microenvironments. © 2011 Haagsma et al.


Levering J.,University of Heidelberg | Fiedler T.,University of Rostock | Sieg A.,University of Rostock | van Grinsven K.W.A.,Swammerdam Institute for Life science | And 8 more authors.
Journal of Biotechnology | Year: 2016

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. © 2016 Elsevier B.V.


PubMed | Amsterdam Institute for Molecules, University of Rostock, Swammerdam Institute for Life science and University of Heidelberg
Type: | Journal: Journal of biotechnology | Year: 2016

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets.


El-Kebir M.,Life science | El-Kebir M.,VU University Amsterdam | El-Kebir M.,Amsterdam Institute for Molecules | Brandt B.W.,VU University Amsterdam | And 7 more authors.
BMC Systems Biology | Year: 2014

Background: Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks. We recently developed Natalie, which computes high-quality network alignments via advanced methods from combinatorial optimization.Results: Here, we present NatalieQ, a web server for topology-based alignment of a specified query protein-protein interaction network to a selected target network using the Natalie algorithm. By incorporating similarity at both the sequence and the network level, we compute alignments that allow for the transfer of functional annotation as well as for the prediction of missing interactions. We illustrate the capabilities of NatalieQ with a biological case study involving the Wnt signaling pathway.Conclusions: We show that topology-based network alignment can produce results complementary to those obtained by using sequence similarity alone. We also demonstrate that NatalieQ is able to predict putative interactions. The server is available at: http://www.ibi.vu.nl/programs/natalieq/. © 2014 El-Kebir et al.; licensee BioMed Central Ltd.


Haagsma A.C.,VU University Amsterdam | Haagsma A.C.,Amsterdam Institute for Molecules | Driessen N.N.,VU University Amsterdam | Hahn M.-M.,VU University Amsterdam | And 5 more authors.
FEMS Microbiology Letters | Year: 2010

ATP synthase is a validated drug target for the treatment of tuberculosis, and ATP synthase inhibitors are promising candidate drugs for the treatment of infections caused by other slow-growing mycobacteria, such as Mycobacterium leprae and Mycobacterium ulcerans. ATP synthase is an essential enzyme in the energy metabolism of Mycobacterium tuberculosis; however, no biochemical data are available to characterize the role of ATP synthase in slow-growing mycobacterial strains. Here, we show that inverted membrane vesicles from the slow-growing model strain Mycobacterium bovis BCG are active in ATP synthesis, but ATP synthase displays no detectable ATP hydrolysis activity and does not set up a proton-motive force (PMF) using ATP as a substrate. Treatment with methanol as well as PMF activation unmasked the ATP hydrolysis activity, indicating that the intrinsic subunit ε and inhibitory ADP are responsible for the suppression of hydrolytic activity. These results suggest that the enzyme is needed for the synthesis of ATP, not for the maintenance of the PMF. For the development of new antimycobacterial drugs acting on ATP synthase, screening for ATP synthesis inhibitors, but not for ATP hydrolysis blockers, can be regarded as a promising strategy. © 2010 Federation of European Microbiological Societies.


Lu P.,VU University Amsterdam | Lu P.,Amsterdam Institute for Molecules | Haagsma A.C.,VU University Amsterdam | Haagsma A.C.,Amsterdam Institute for Molecules | And 8 more authors.
Antimicrobial Agents and Chemotherapy | Year: 2011

Pyrazinoic acid, the active form of the first-line antituberculosis drug pyrazinamide, decreased the proton motive force and respiratory ATP synthesis rates in subcellular mycobacterial membrane assays. Pyrazinoic acid also significantly lowered cellular ATP levels in Mycobacterium bovis BCG. These results indicate that the predominant mechanism of killing by this drug may operate by depletion of cellular ATP reserves. Copyright © 2011, American Society for Microbiology. All Rights Reserved.

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