Investigating drug tolerance in Mycobacterium tuberculosis

Project Details


Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (Mtb), remains an important global public health problem, with 10 million new cases and 1.6 million TB deaths in 20171. Current TB treatment is suboptimal as patients have to be adherent to ≥6 months treatment with multiple drugs2. This results in long periods of infectiousness, considerable inflammation and lung damage and an increased risk of acquisition of drug resistance. Treatment shortening is therefore an important goal of TB research3-6.

In addition, the standardized TB treatment regimen shows important interpatient variability in treatment response, even among patients with confirmed drug susceptible TB. For example, while most patients are cured and remain free of TB following completion of the six-month regimen, some patients relapse even if they were fully adherent to treatment7. Also time to culture conversion, an important predictor of treatment success, strongly varies with 95% confidence intervals ranging from 41 to 83 days following treatment initiation7-9. This variability has primarily been attributed to difference in host factors such as baseline mycobacterial load, presence of cavitary lesions, HIV status and smoking10-15. However, heterogeneity in growth dynamics of the mycobacterial populations may also contribute to this interpatient variability in treatment responses.

Time-kill curves of Mtb under drug pressure are shown to be biphasic, suggesting that more than one bacterial phenotype is present in “fully drug susceptible” bacterial populations16-21. Recent modeling of changes in time to culture positivity (i.e. the time between incubation and positivity) in serial isolates confirmed that indeed two or even three bacterial populations with different growth dynamics and distinctive kill rates are present in clinical sputum specimens22. Bacterial population heterogeneity has since long confounded our understanding of the complex mechanisms whereby bacteria are able to survive drug pressure. Drug tolerance is one possible manifestation of this heterogeneity, and is defined as the temporal and reversible ability of bacteria to survive exposure to bactericidal antibiotics23.

Drug tolerance differs mechanistically from drug resistance -which is a genetically encoded non-reversible drug adaptationas tolerance is transient and is triggered by environmental conditions. The concept of drug tolerance dates from 1944, when during WWII colonel J. Bigger reported himself incapable of completely eradicating an in vitro bacterial infected broth using only antibiotics. He noted the presence of a small bacterial subpopulation that was able to repeatedly persist bactericidal antibiotic activity. He called these bacteria drug tolerant “persisters”24 and hypothesized that, as bactericidal drugs target core metabolic processes, persistent bacteria adopted a metabolic inactive state, resulting in reduced drug sensitivity. Since Biggers attempt 75 years ago, complete sterilization of bacterial broth using purely antibiotics has -to our knowledge- not been described yet, except by Cogan et al., who three years ago proved it possible to completely sterilize bacterial broth with a technique called “fractionated sterilization”, an idea already raised by colonel Bigger in 194425. Fractionated sterilization consists of multiple rounds of antibiotic treatment, intercalated with periods without antibiotic pressure so that the remaining persisters can regrow and regain metabolic activity. Using mathematical modelling of population killing and growth dynamics, Cogan et al. predicted the frequency of antibiotic addition and ratified this idea in vitro obtaining complete sterilization. However, as precise timing of antibiotic addition is crucial, and little shifts in timing between rounds of antibiotic administration result in outgrowth of bacteria, fractionated sterilization is unlikely to work in vivo, where parametrization quickly becomes very complex.
Effective start/end date3/11/20 → …

IWETO expertise domain

  • B780-tropical-medicine