Biology of gene-deleted M.tuberculosis strains - immunological marker profiling
|Coordinator||Karolinska institutet - Institutionen för mikrobiologi, tumör- och cellbiologi|
|Funding from Vinnova||SEK 3 615 000|
|Project duration||September 2009 - August 2012|
Purpose and goal
Biology of gene-deleted M.tuberculosis strains - immunological marker profilingWe need: 1. An early warning system for resistant TB and novel anti-Mtb drugs. 2. More effective Mtb vaccines. 3. Novel markers to effectively diagnose latent TB and to monitor response to therapy. The biology of Mtb and the host immune response are both important parameters for the clinical outcome, appropriate and predictive models are needed to address points 1-3. Objectives: 1. To establish biologically meaningful and clinically relevant pre-clinical models of gene-deleted M.tuberculosis defect variants (rMtb). 2. To gauge robust markers of Mtb and rMtb infection associated wit rMtb/Mtb biology and clinical endpoints in preclinical models. 3. To selectively test relevant markers in selected patient populations.
Results and expected effects
We propose to establish biologically meaningful and clinically relevant pre-clinical models of gene-deleted M.tuberculosis (Mtb) defect variants (rMtb). Robust markers of Mtb and rMtb infection associated wit rMtb/Mtb biology and clinical endpoints will be tested in preclinical (murine, humanized mouse) models and guided by novel high content immunological markers signatures. Candidate markers will be tested for clinical relevance in selected patient populations. The diagnosis of latent TB may trigger early TB treatment and represents a central point as an inclusion/exclusion criterium for clinical trials.
Approach and implementation
Biomarkers include tetramer-guided analysis of TB-specific T-cells, antibody recognition of Mtb specific epitopes and biologically relevant immune signatures. The implementation of novel anti-Mtb drugs requires robust biomarkers to reliably measure response to therapy and relevant markers for early STOP/GO decisions in product development