3 Systems Biology Approaches to Understanding and Predicting Fungal Virulence

Chapter
First Online:
Part of the The Mycota book series (MYCOTA, volume 12)

Abstract

The identification of fungal virulence factors and novel targets for therapeutic intervention are hindered by the rapid adaptability of pathogenic fungi to their host. One of the major goals of systems biology (SysBio) is to investigate the molecular wiring and dynamics in biological networks, as well as to identify and predict emerging properties of systems. Recent advances in SysBio approaches have paved the way for deciphering host–pathogen interaction complexity and the identification of microbial virulence factors. In this chapter, we discuss SysBio-based methods and milestones in the investigation of fungal virulence, emphasizing computational and modeling-based approaches in the Candida and Saccharomyces genera. We describe the applicability of each method to specific experimental questions using numerous case examples, and critically discuss current gaps and pitfalls in the analysis of SysBio data sets.

Keywords

High Performance Liquid Chromatography Monte Carlo Massive Parallel Signature Sequencing Boolean Model System Biology Markup Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

Work on systems biology in the KK group has been supported by a grant from the Christian Doppler Research Society, and by grants of the Austrian Science Foundation (FWF-DACH Proj.: I-746-B11, FWF-P25333-B09), by the SysMo-MOSES project through the FFG, the WWTF, and by the IP-UNICELLSYS from the FP7 programme. Work on systems biology of fungal infection in the EK group has been supported by grants from the German Research Council (DFG: CRC618), the EU Marie-Curie Program (FinSysB, PITN-GA-2008-214004) and the EU FP7 programme (IP-UNICELLSYS and IP-SysteMtb). We would like to thank Sara Tierney for contributing to the artwork.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Christian Doppler Laboratory Infection Biology, Max F. Perutz LaboratoriesMedical University of ViennaViennaAustria
  2. 2.Institute of Biology, Theoretical BiophysicsHumboldt-Universität zu BerlinBerlinGermany

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