Integration of modelling with transcription and gene essentiality profiling to study interaction of MTB bacillus with macrophages and dendritic cells.

Lead Research Organisation: University of Surrey
Department Name: Microbial & Cellular Sciences


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, including the UK. In this project we will study the molecular mechanisms of the interaction between Mcyobacterium 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 modeling 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 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.

Technical Summary

Mycobacterium tuberculosis (MTB) remains a global health problem. The interaction of MTB with macrophages and dendritic cells (DCs) is central to the pathogenesis of tuberculosis and to the generation of a protective immune response. Interestingly, MTB is readily phagocytosed by both macrophages and DCs, yet the bacterium is only able to replicate in the macrophage. We will use Systems Biology approach to study host pathogen interactions of human macrophages and dendritic cells (DCs) with the MTB bacillus. We will use high throughput experimental approaches to simultaneously study gene expression and essentiality of both host and pathogen. These data will inform predictive computer models of the molecular mechanisms underpinning observed gene activity changes. We will use available reconstructions of signaling and metabolic networks in both host and pathogen as the starting point of the network analysis. All models will be subjected to the qualitative computer simulations of the relationship between gene activity and the state of proteins and metabolites in the network models. We will identify substances and reactions in the network models which are most affected by gene expression differences between infected macrophages and DCs, as represented by microarray signal ratios. Flux Balance Analysis based approaches will be used for qualitative analysis of metabolic networks. Qualitative analysis of signalling networks will be performed by rule-based approach implemented in the CellNetAnalyzer. Reactions and substances which are most affected by gene expression changes will highlight network modules involved in host pathogen interactions. Detailed modeling of these modules will generate hypotheses about molecular mechanisms underpinning observed gene essentiality and gene activity changes.The hypotheses will be tested by molecular biology teams and observations will inform the models in the iterative cycle of hypothesis generation and experimental validation.

Planned Impact

Tuberculosis remains one of the most important infectious diseases of mankind, claiming 33,000 deaths per week in an epidemic presently involving 9 million new cases of disease each year (WHO, 2008). One third of the world's population carry an asymptomatic persistent infection, providing a vast reservoir of infection (Kochi, 1991). Up to 10% of individuals with latent tuberculosis will go on to develop active disease thus contributing substantially to transmission and the overall incidence of disease (Bloom and Murray, 1992). In addition there exists increasing levels of multiple drug resistant TB (MDR-TB) and extensively drug resistant TB (XDR-TB). Present control strategies are clearly insufficient to reduce the global burden of TB. This project will identify molecular interaction networks involved in the interaction of MTB with the host cell and construct predictive computer models of these networks. The major users of these models will be research groups working on tuberculosis both in the academia and in the industry. The models will be used to generate research hypotheses that will direct further experimental research. The models will be also used directly to identify targets for development of new antibiotics. Predictive models of the interaction between MTB and immune system will also inform research on new vaccination strategies. Systems Biology approach adopted by this project will be also used to investigate other human and animal bacterial pathogens. Therefore, the application of the models resulting from this project will help to combat a major human pathogen. Eradication of resurging human and animal infectious diseases will have a major positive impact on the well-being and quality of life. To ensure that academic and industry research groups will benefit from the results of this project we will adopt open data sharing standards accepted by scientific community. Experimental data will be submitted to recognized, publicly available databases. Models will be available in the SBML format which is widely accepted by research community. To further enhance availability of the models we will made them available in the interactive form via set of www-based tools. These tools will help researchers to identify usefulness of our models without the need to install any specialized software.
Description The TB-HOST-NET was international consortium dedicated to studying interaction between Mycobacterium tuberculosis, a bacterial pathogen causing Tuberculosis disease and two cell types in human immune system. The major discoveries and developments made by University of Surrey partner are:

1. ESSENTIAL GENES. We have discovered genes of Mycobacterium tuberculosis which are essential for its interaction with dendritic cell (DC), a key player in human immune response, responsible for antigen presentation. This has been achieved by the first experiment where large-scale mutagenesis and next generation DNA sequencing have been combined to study M. tuberculosis and DC interaction. The manuscript and full dataset have been submitted for publication in Open Access journal and will be available to the public soon.

2. GENOME SCALE METABOLIC NETWORK: In collaboration with other groups we have created a computer model representing metabolism of M. tuberculosis within macrophage. This is unified model integrating our previous highly cited GSMN-TB model (Genome Biology 2007) and recent work of other groups. The model will be published very soon and will enable prediction of metabolic vulnerabilities of M. tuberculosis by computer simulation.

3. SurreyFBA SOFTWARE. We have significantly extended a set of methods available in our SurreyFBA software for computer simulation of genome scale metabolic networks (Bioinformatics 2011). Version 2.0 of the software includes a set of state of the art approaches for analysis of transcriptomics data in the context of mechanistic model of whole cell metabolism. These methods provide invaluable insight into metabolic state of the cell under conditions of transcriptomic experiment. New version of our free, open source (GNU GPL) software is already available for download ( and a manuscript is under preparation.

4. QSSPN METHOD. To fully understand host-pathogen interaction we need mechanistic models of molecular interaction networks in the cell encompassing not only metabolism but also other classes of molecular interactions. This project contributed to the development of Quasi Steady State Petri Net (QSSPN) - the first method enabling dynamic simulation of molecular interaction networks describing gene regulation, signalling and whole-cell metabolism in human cells. The method has been published as Open Access article in Bioinformatics, 2013. The free, open source (GNU GPL) software can be downloaded from (
Exploitation Route The list of M. tuberculosis genes essential for interaction of this pathogen with Dendritic Cell uncovers vulnerabilities of the pathogen. These findings will be taken forward by research towards development of antibiotics and vaccines, thus contributing to combating world's most dangerous bacterial pathogen.

Genome Scale Metabolic Reaction Network of M. tuberculosis allows simulation of metabolic vulnerabilities of the pathogen. We can previously demonstrated that we can accurately predict reactions which inactivation results in distraction of the pathogen. Enzymes catalysing this reactions are targets for development of much needed new antibiotics. New version of the model increases both scope and accuracy of the predictions. It will be taken forward in research towards development of new antibiotics.

New version of SurreyFBA software enables deduction of the metabolic state of the cell from transcriptomic data. This is invaluable for analysis of medical samples, where transcriptomics is possible, but evaluation of intracellular metabolism is much more difficult. The knowledge about metabolic state enables identification of metabolic biomarkers that can be taken forward towards development of diagnostics and vulnerabilities that provide candidate targets for new drugs. Currently, SurreyFBA is used not only for analysis of M. tuberculosis data but also for interpretation of cancer transcriptomes. The software can thus be used for predictions relevant to development of diagnostics and therapy.
Sectors Healthcare,Pharmaceuticals and Medical Biotechnology

Description This grant has finished in 2013 and the full potential of its findings has not yet been realised. We expect that the insight into interaction between dendritic cell and M. tuberculosis will inform research on new vaccines. Vulnerabilities of the pathogen uncovered by our metabolic model and experimental data will direct research towards new antibiotics. The new simulation algorithms and software will play a role in predictive modelling of genotype-phenotype-environment relationship in medical research.
First Year Of Impact 2014
Sector Healthcare,Pharmaceuticals and Medical Biotechnology
Impact Types Economic

Title SurreyFBA: a command line tool and graphics user interface for constraint-based modeling of genome-scale metabolic reaction networks 
Description Constraint-based modeling of genome-scale metabolic networks has been successfully used in numerous applications such as prediction of gene essentiality and metabolic engineering. We present SurreyFBA, which provides constraint-based simulations and network map visualization in a free, stand-alone software. In addition to basic simulation protocols, the tool also implements the analysis of minimal substrate and product sets, which is useful for metabolic engineering and prediction of nutritional requirements in complex in vivo environments, but not available in other commonly used programs. The SurreyFBA is based on a command line interface to the GLPK solver distributed as binary and source code for the three major operating systems. The command line tool, implemented in C++, is easily executed within scripting languages used in the bioinformatics community and provides efficient implementation of tasks requiring iterative calls to the linear programming solver. SurreyFBA includes JyMet, a graphics user interface allowing spreadsheet-based model presentation, visualization of numerical results on metabolic networks represented in the Petri net convention, as well as in charts and plots. 
Type Of Technology Software 
Year Produced 2011 
Open Source License? Yes  
Impact The SurreyFBA has been used to provide biological insight in bacterial pathogen and biotechnology research at Surrey. Outside of University of Surrey, it has been used as a computational engine for Metexplore software ( and for research on the biosynthesis of metabolites involved in Parkinson's disease and schizophrenia. It is used for teaching both at University of Surrey and University of Manchester.