• Host-induced spermidine production in motile triggers phagocytic uptake.

      Felgner, Sebastian; Preusse, Matthias; Beutling, Ulrike; Stahnke, Stephanie; Pawar, Vinay; Rohde, Manfred; Brönstrup, Mark; Stradal, Theresia; Häussler, Susanne; HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany. (elifeSciences, 2020-09-22)
      Exploring the complexity of host-pathogen communication is vital to understand why microbes persist within a host, while others are cleared. Here, we employed a dual-sequencing approach to unravel conversational turn-taking of dynamic host-pathogen communications. We demonstrate that upon hitting a host cell, motile Pseudomonas aeruginosa induce a specific gene expression program. This results in the expression of spermidine on the surface, which specifically activates the PIP3-pathway to induce phagocytic uptake into primary or immortalized murine cells. Non-motile bacteria are more immunogenic due to a lower expression of arnT upon host-cell contact, but do not produce spermidine and are phagocytosed less. We demonstrate that not only the presence of pathogen inherent molecular patterns induces immune responses, but that bacterial motility is linked to a host-cell-induced expression of additional immune modulators. Our results emphasize on the value of integrating microbiological and immunological findings to unravel complex and dynamic host-pathogen interactions.
    • xCELLanalyzer: A Framework for the Analysis of Cellular Impedance Measurements for Mode of Action Discovery

      Franke, Raimo; Hinkelmann, Bettina; Fetz, Verena; Stradal, Theresia; Sasse, Florenz; Klawonn, Frank; Brönstrup, Mark; HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany. (Sage, 2019-01-25)
      Mode of action (MoA) identification of bioactive compounds is very often a challenging and time-consuming task. We used a label-free kinetic profiling method based on an impedance readout to monitor the time-dependent cellular response profiles for the interaction of bioactive natural products and other small molecules with mammalian cells. Such approaches have been rarely used so far due to the lack of data mining tools to properly capture the characteristics of the impedance curves. We developed a data analysis pipeline for the xCELLigence Real-Time Cell Analysis detection platform to process the data, assess and score their reproducibility, and provide rank-based MoA predictions for a reference set of 60 bioactive compounds. The method can reveal additional, previously unknown targets, as exemplified by the identification of tubulin-destabilizing activities of the RNA synthesis inhibitor actinomycin D and the effects on DNA replication of vioprolide A. The data analysis pipeline is based on the statistical programming language R and is available to the scientific community through a GitHub repository.