Detection of the different phases of Mycobacterium tuberculosis infection and prediction of the development of tuberculosis disease progression by application of novel interferon gamma release assay

ended

Tuberculosis disease (TB) is the second leading infectious killer after COVID-19 (above HIV/AIDS). The main reason is due to high ability of the bacteria Mycobacterium tuberculosis (Mtb) to hide after infection and lack of the precise and sensitive tests able to detect different forms of TB and indicate disease progression. Therefore the aim of this project is to search and investigate new antigens that could be used not only for the detection of different phases of Mycobacterium tuberculosis infection but also could be used for precise prognostic tool. To achieve this goal, the experience of the applicant in a LTBI diagnostics, medical microbiology and molecular biology will be combined with hands on training in a field of bioinformatics, and in silico approaches supported by artificial intelligence computational and experimental methods applied for structural analysis of proteins supporting strategic decisions in detection system development. As part of the World Health Organization's (WHO) End TB Strategy to reduce the mortality and incidence rates of TB by 90% and 80%, respectively, in 2025 and further reduction by 95% and 90% in 2035, reverse efforts to focus on TB infection management as one of the TB preventive care approaches for the long-term situation of TB prevention and treatment are highly needed. The main goal of this proposal is to better understand molecular basic of the TB infection and progression aiming identification of the new antigens which later can provide a new avenue for designing of novel interferon gamma release assays (IGRA) test for detection of different phases of TB infection and predict active TB disease progression. We hypothesise that using latency associated protein candidates and IFN-γ-producing CD8+ T cells specific Mtb antigens we will be able to achieve these goals.