Priyanka Chauhan anticipates to develop new molecular strategies to quantify and control dormant and active states of Mtb by identifying and characterizing various environmental, molecular and genetic determinants (switching factors). These switching factors can then be exploited to control the equilibrium between dormant and growing cells. In addition, drug cocktails can be proposed that combine switch-inducing factors with classical anti-tubercular drugs, henceforth facilitating their bactericidal action against active/replicating or dormant/persistent mycobacteria. This can help in reducing the overall duration of chemotherapy which is one of the main hurdles in achieving the goal of ending the global TB epidemic by 2035. Outcomes of this project will also improve the quantitative understanding of mycobacterial persisters, which is still an underappreciated aspect. Precise quantification is very important and required for identification of new drug candidates, as minor changes of the dormant fraction may considerably influence the results of drug dose and treatment.
Dormant bacteria cannot be isolated from the host due to their very low number and viable but non culturable state. Hence, various in vitro models of dormancy have been developed by stimulating the condition which is believed to be encountered by bacteria inside the host. Taking the lead from previous works of other scientists, Chauhan and her colleagues established a hypoxic in vitro model of dormancy and characterized the dormant phenotype of bacteria by various parameters such as antibiotic tolerance, low ATP measurement, lipid staining, and microscopy. Also, they quantitated temporal declination of oxygen by gas chromatography. Presently, they are moving ahead towards the quantitative aspect of the project and applying single cell analysis techniques such as flow cytometry to develop a new, precise and time saving method to quantitate and isolate the persiters population under variable oxygen conditions.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 713669.