Project: Living with uninvited guests – comparing plant and animal responses to endocytic invasions

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.

Acronym	SHIPREC
Project Results (after finalisation)	SHIPREC addresses the basic biological question how the extremely divergent host organisms, human and plant, respond to invasion by the same pathogen, Salmonella bacteria, in an effort to better understand the interactions between this pathogen and its hosts. By integrating results using a systems biology approach, we hoped to expose weaknesses and strengths in the responses and asked the question: Are there host ‘weak points’ that Salmonella exploits in animals and plant host cells alike? Because Salmonellosis is a significant health problem for both humans and animals, amplified by its remarkable ability to “hide” inside plant cells, the findings may be exploited for drug development, diagnosis, disease forecasting, prevention and control. Our team consists of computational modelers (Vincent Jansen and Alex Gammerman at Royal Holloway University of London (RHUL), UK, Baldo Oliva (Pompeu Fabra, Spain) and Infociencia Inc., Spain.) and experimentalists with different relevant domain knowledge: Rob La Ragione (RL, Veterinary Laboratory Agency, UK), is responsible for animal cell derived materials and Heribert Hirt (HH) at the Unité de Recherche en Génomique Végétale, France, is overseeing all plant studies. Transcriptomic and proteomic data sets have been generated by HH, RL, Gary Coulton, St George’s University of London, Harald Mischak, Mosaiques Inc., Germany. Mikhail Soloviev (RHUL) is applying protein arrays to the problem. The project is coordinated by Judith Klein-Seetharaman (Univ. of Warwick, UK and Research Center Jülich, Germany) who integrates the experimental and computational approaches. The deliverables of the project include generation of new data, algorithms, and biological insight. Gene expression datasets were obtained for Arabidopsis plants and human 2D and 3D gut cell lines in the presence and absence of Salmonella infections. Novel algorithms were developed to compare these gene expression results as there is no way to compare genes between Arabidopsis and Humans directly due to the extreme divergence. The new method, therefore, compares different species on a functional level rather than between genes as is classically done. Different profiles are fitted to the gene expression data capturing qualitative features of the gene's expression over time. Genes are then grouped according to their function based on gene ontology data, and groups are tested for significance. This has resulted in the identification of functional groups that are expressed in both human and plants cells following Salmonella invasion. To compare host response at the protein level, proteomic and phosphoproteomic data is being generated, and were analyzed in a prediction framework using the BIANA platform that was extended to include host-pathogen interactome features. The expansion is available online at http://sbi.imim.es/BIPS.php. To enable statistical evaluation of interactome analysis, the first gold standard for Salmonella-host interactomes were created by manual curation of hundreds of database and thousands of literature entries. This enabled the development of novel machine learning based algorithms based on conformal predictors to extract information on protein-protein interaction networks and kinase-substrate phosphorylation pairs.
Network	ERASysBio+
Call	ERASysBio+-2008-01

Project partner

Number	Name	Role	Country
1	Research Centre Jülich GmbH	Coordinator	Germany
2	Unité de Recherche en Génomique Végétale	Partner	France
3	Royal Holloway University of London	Partner	United Kingdom
4	University of London	Partner	United Kingdom
5	mosaiques diagnostics GmbH	Partner	Germany
6	Universitat Pompeu Fabra	Partner	Spain
7	INFOCIENCIA, S. L.	Partner	Spain