Comparative lipidomics for development of Mycobacterium tuberculosis-based lipid biomarkers
Feven Tigistu-Sahle1, *, Tigist Getachew1, Mahlet Tegegne1, Deborah Tilahun1 and Reijo Käkelä2
1 Health Biotechnology Directorate, Ethiopian Biotechnology Institute, Addis Ababa, Ethiopia
2 Helsinki University Lipidomics Unit, Helsinki Institute for Life Science (HiLIFE), Helsinki, Finland
* To whom correspondence should be addressed. E-mail: firstname.lastname@example.org
Background: The global tuberculosis (TB) burden needs to be better addressed by developing new diagnosis tests with improved sensitivity and specificity. Immunoassay based diagnosis of TB is believed to be an attractive method of testing due to its simplicity and specificity. Therefore, identification of Mycobacterium tuberculosis (Mtb) based biomarkers will be sought in developing these assays. However, current diagnostic tests are highly variable in specificity and sensitivity. The role of lipids in the survival, pathogenicity and drug susceptibility of Mtb has been broadly investigated. Nevertheless, to have better understanding of Mtb virulence and to discover chemical markers of its pathogenicity we need a systems level analysis of Mtb lipidome.
Method: Mtb will be isolated from the sputum of two experimental groups; individuals of latent vs active TB infection. Whole organism lipid content of Mtb will be extracted according to established standard protocols. High performance liquid chromatography coupled mass spectrometer (HPLC-MS/MS) will be used to analyze the lipid extracts. Established Lipidome database for Mtb will be used to compare the lipid contents of experimental groups.
Expected outcome: This project aims to establish the lipid content of Mtb during different phases of infection. In doing so we hope to identify potential Mtb-based lipid biomarkers which correlate with TB disease progression. These types of biomarkers will be crucial to provide correlates of risk of TB and determine response to therapy. Lastly, the findings of this project aim to assist in the development of enhanced diagnostic tools with improved sensitivity and specificity.