Project: Integration of computational modelling with transcription and gene essentiality profiling of both MTB bacillus and infected human dendritic cells and macrophages to understand molecular interaction networks involved in the host-pathogen cross-talk

Mycobacterium tuberculosis is a major pathogen of man. Drug treatment is available for human disease but it takes six months, which is impractical in developing world settings where TB is most common. Consequent non-compliance with treatment regimes leads to the emergence of drug resistance. This is now a major world-wide problem with practically incurable ?extreme drug-resistant? strains appearing in many countries. In this project we will study the molecular mechanisms of the interaction between Mycobacterium tuberculosis and human immune system. The knowledge about these mechanisms is necessary for the development of new therapeutic approaches and vaccines which are needed to shorten TB treatment and combat drug resistant strains. We will focus on the interaction of the pathogen with dendritic cells and macrophages, which are cell types active during the immune system response to the infection. The M. tuberculosis is capable of infecting macrophages, but not dendritic cells. Therefore, comparison of the responses of these two cell types to M. tuberculosis will highlight the mechanisms participating in host pathogen interaction. To understand the complex phenomenon of host-pathogen interaction the Systems Biology approach has to be employed, where molecular biology methods are integrated with computational modelling approaches to study cells at the whole genome scale level. We will use state of the art functional genomics techniques to compare interaction of the pathogen with dendritic cells and macrophages and identify human and bacterial genes, which are involved in host-pathogen interaction. The voluminous experimental data sets will be analyzed in the context of the literature knowledge about the vast networks of interacting molecules in the living cells. The computer simulation approaches developed in the physical sciences and engineering fields will be used. The computer models will generate hypotheses, which will be subjected to experimental verification. At the end of the project we expect to deliver a set of models of the molecular interaction networks involved in the interaction of M. tuberculosis with immune system. These models can be used to design therapeutic, diagnostic and vaccination strategies.

Acronym	TB-HOST-NET
Project Results (after finalisation)	Mycobacterium tuberculosis (MTB) remains a global health problem. Information about how this pathogen interacts with the human host is disjointed and incomplete. Systems Biology integrates experimental methods of functional genomics and computational modelling approaches to investigate how the complex properties of the living cells emerge in the network of interactions between their molecular components. The TB-HOST-NET consortium applied this approach to study host pathogen interactions of human macrophages and dendritic cells (DCs) with the MTB bacillus. We used high throughput experimental approaches to simultaneously study gene expression and essentiality of both host and pathogen. These data informed predictive computer models of the molecular mechanisms underpinning observed gene activity changes. The models of host pathogen interaction are being subjected to the iterative cycle of hypothesis generation and experimental validation. The work on the proposal started with the computational analysis of molecular interaction networks involved in host cell immune responses to identify candidate host genes for inactivation in host cells. Three candidate genes (ATF3, ATF6, HIF1) have been selected and silenced by siRNA in human host cells from 11 donors. For each of the knockouts and each of the donors transcriptome analysis has been performed with and without M. tuberculosis infection. Transcriptome analysis of pathogen samples has been performed as well. In parallel the transposon inactivation of pathogen genes has been performed followed by Next Generation Sequencing of clones that survived interaction with host cells. We have identified genes which are underrepresented in surviving clone pool and thus important for host pathogen interaction. Experimental data are being analysed in the context of mechanistic simulations of molecular interaction networks. We have initiated community effort towards reconstruction of genome scale metabolic reaction network of M. tuberculosis and host cell. This model is currently being used to analyse transcriptome data and mechanistically understand metabolic reprogramming of host and pathogen during infection. The model is also used to interpret information about pathogen gene essentiality during infection provided by sequencing of M. tuberculosis transposon libraries. We have also created large-scale models of signaling networks using logical interaction hypergraph and qualitative Petri Nets. We are now constructing models where qualitative Petri Net representation of regulatory processes is integrated with genome scale metabolic models through quasi-steady state approach in our recently published QSSPN framework. All models are subject to experimental validation and will be used to identify mechanisms key for interaction of M. tuberculosis with host cells.
Network	ERASysBio+
Call	ERASysBio+-2008-01

Project partner

Number	Name	Role	Country
1	University of Surrey	Coordinator	United Kingdom
2	CNRS Toulouse	Partner	France
3	Insitut Pasteur Paris	Partner	France
4	Max-Planck-Institute for Dynamics of Complex Technical Systems	Partner	Germany
5	University of Milan-Bicocca	Partner	Italy