Living with uninvited guests -comparing plant and animal responses to endocytic invasions – ERASYSBIO (ANR-09-SYSB-0007)
Salmonella are Gram-negative bacterial facultative endopathogens capable of infecting an unusually wide range of organisms and the causative agent of various human diseases, from enteritis to typhoid fever. Salmonellosis is the most frequent food-borne disease with ~ 1,5 billion infections world-wide yearly and has been linked to contamination of vegetables and fruits. Salmonella communicate with their hosts at every stage of their life cycles. However, unlike for other pathogens, such as HIV-1, for which more than 2500 interactions with its human host have been reported, taking a system-wide view for Salmonella is in its infancy but is critical to fully grasp the mechanisms of host-pathogen responses. In this project, we address the basic biological question how divergent hosts, such as plants and animals, respond to invasion by Salmonella. This can help us elucidate the way the interaction between the hosts and the pathogen works. Analyzing the responses of different hosts to invasion, and integrating these results using a systems biology approach will expose the weaknesses and strengths in the responses: Are there host ‘weak points’ that Salmonella exploits in animals and plant host cells alike? By comparison of the reactions of evolutionarily diverse hosts, fundamentally conserved communication mechanisms may be discovered, and can potentially be exploited for drug discovery and biomarker development. An interdisciplinary consortium of experimental and computational scientists will develop dynamic models of Salmonella infecting diverse host cells. Project partners are located at 8 institutions (universities, companies and government laboratories) in four countries. Project coordinator is Judith Klein-Seetharaman, Univ. of Pittsburgh, USA and Research Center Jülich, Germany. Experimental partners are the Veterinary Laboratory Agency, England, Heribert Hirt, URGV, France, Gary Coulton, St George’s, England, Harald Mischak, mosaiques diagnostics Inc., Germany, and Mikhail Soloviev, RHUL, England. High-throughput transcriptomic and proteomic data will be generated. Machine learning, mathematical modelling, statistics and network analysis will be carried out by Vincent Jansen and Alex Gammerman at RHUL, England, Baldo Oliva, Pompeu Fabra, Spain and Infociencia Inc., Spain
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
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