• Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.

      Wodke, Judith A H; Puchałka, Jacek; Lluch-Senar, Maria; Marcos, Josep; Yus, Eva; Godinho, Miguel; Gutiérrez-Gallego, Ricardo; dos Santos, Vitor A P Martins; Serrano, Luis; Klipp, Edda; et al. (2013)
      Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.
    • Human lung tissue explants reveal novel interactions during Legionella pneumophila infections.

      Jäger, Jens; Marwitz, Sebastian; Tiefenau, Jana; Rasch, Janine; Shevchuk, Olga; Kugler, Christian; Goldmann, Torsten; Steinert, Michael; Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2014-01)
      Histological and clinical investigations describe late stages of Legionnaires' disease but cannot characterize early events of human infection. Cellular or rodent infection models lack the complexity of tissue or have nonhuman backgrounds. Therefore, we developed and applied a novel model for Legionella pneumophila infection comprising living human lung tissue. We stimulated lung explants with L. pneumophila strains and outer membrane vesicles (OMVs) to analyze tissue damage, bacterial replication, and localization as well as the transcriptional response of infected tissue. Interestingly, we found that extracellular adhesion of L. pneumophila to the entire alveolar lining precedes bacterial invasion and replication in recruited macrophages. In contrast, OMVs predominantly bound to alveolar macrophages. Specific damage to septa and epithelia increased over 48 h and was stronger in wild-type-infected and OMV-treated samples than in samples infected with the replication-deficient, type IVB secretion-deficient DotA(-) strain. Transcriptome analysis of lung tissue explants revealed a differential regulation of 2,499 genes after infection. The transcriptional response included the upregulation of uteroglobin and the downregulation of the macrophage receptor with collagenous structure (MARCO). Immunohistochemistry confirmed the downregulation of MARCO at sites of pathogen-induced tissue destruction. Neither host factor has ever been described in the context of L. pneumophila infections. This work demonstrates that the tissue explant model reproduces realistic features of Legionnaires' disease and reveals new functions for bacterial OMVs during infection. Our model allows us to characterize early steps of human infection which otherwise are not feasible for investigations.