Tuberculosis (TB) is a re-emerging global health threat caused by Mycobacterium tuberculosis (Mtb). One third of the world's population is infected with Mtb and new infections occur at a rate of one per second. Despite global research efforts, mechanisms underlying pathogenesis, virulence and persistence of Mtb infection remain poorly understood. Simple reductionist approaches are insufficient to understand its complex biology. The grand goal of the SysteMTb project is to establish a Systems Biology framework to understand key features of Mtb and its interactions with the host which, in turn, will provide new insights and a solid (model based) knowledge for the development of novel and cost-effective strategies to combat tuberculosis. To achieve this, SysteMTb will: i) generate and integrate quantitative data sets of Mtb (e.g. transcriptomics, proteomics, metabolomics, structural genomics, lipidomics, glycomics) alone, or in the presence of host macrophages, ii) develop computer models at different appropriate levels of system complexity with emphasis on metabolism, regulatory networks and transcription regulation, and iii) identify new possible targets for therapeutic intervention based on computer modelling. The combination of these approaches will provide a rational framework to understand mycobacterial physiology during infection and to identify essential nodes that are optimal for effective therapeutic interventions.