Potassium-dependent switching dynamics between persistence and antibiotic susceptibility in Mycobacterium

Mycobacterium tuberculosis, which causes tuberculosis, leads to over one million deaths annually. This bacterium can develop resistance to multiple antibiotics, making it essential to find more efficient treatment methods to protect human health. One way bacteria evade antibiotics is by entering an altered physiological, non-growing state that allows them to survive antibiotic exposure. Such cells are called persisters. Recent studies suggest that potassium may influence the switch between persistent and susceptible states. Understanding and quantifying the effect of potassium on switching is crucial, for example in the clinical treatment of Mycobacterium infections.

Mycobacterium smegmatis is a bacterium used as a non-pathogenic proxy for studying the virulent M. tuberculosis, with which it shares a large part of genetic homology, physiology, and cellular structure. We grew M. smegmatis cells to stationary phase with nutrient depletion for both short (1 day) and long durations (3 days). Following this, the cells were transferred to fresh medium with varying potassium concentrations, and their growth dynamics were observed. We found that stationary growth conditions and altered potassium concentrations affect population growth dynamics.

We developed a mathematical model that accounts for cells switching out of the persistent state, as well as for growing cells. This model allows us to quantify effects on the total population growth, such as altering cell growth, various initial amounts of persister cells, and different switching rates into active state. Using the experimental data, the model was used to predict the fraction of persister cells in the population over time, as well as to provide switching rates, lag times, and growth rates. Different scenarios were simulated with the model to estimate the time until all persisters switched to susceptible state.

Our experiments quantify effects of various potassium concentrations on the switching from persistent to susceptible states in M. smegmatis and M. tuberculosis. By using mathematical modelling, we provide new insight into the contributions of persister cells and switching rates to the cell pool. These insights will refine our knowledge of Mycobacterium and pave the way for more detailed assays in the future, as well as streamline plausible strategies for effective antibiotic treatment.