Evolution of antibiotic tolerance in the 'wild': A quantitative approach

Informations projet

Tolerome

N° de convention de subvention: 681819

DOI

10.3030/681819

Projet clôturé

Date de signature de la CE 20 Avril 2016

Date de début 1 Mai 2016

Date de fin 31 Octobre 2021

Financé au titre de

• EXCELLENT SCIENCE - European Research Council (ERC)

Coût total

€ 1 978 750,00

Contribution de l’UE

€ 1 978 750,00

Coordonné par

THE HEBREW UNIVERSITY OF JERUSALEM
Israel

Periodic Reporting for period 4 - Tolerome (Evolution of antibiotic tolerance in the 'wild': A quantitative approach)

Période du rapport: 2020-11-01 au 2021-10-31

Résumé du contexte et des objectifs généraux du projet

The failure of antibiotic treatments is a major concern worldwide. Resistance is a major determinant in the survival for bacteria under antibiotics. However, it is often observed that bacteria become recalcitrant to antibiotics treatments, without developing resistance, a phenomenon termed “tolerance”. The extent and importance of tolerance for infections is the subject of intense debate. In this project, we followed closely bacterial cultures as they evolved towards antibiotic resistance. Aided by a mathematical model, and by performing quantitative biophysical measurements on the evolving populations, we were able to reveal that bacteria become first tolerant to antibiotic treatment, and only subsequently acquire resistance mutations. In experimental evolution in the lab, we could compute that the initial evolution of tolerance promotes by a factor of 20 the speed of the evolution of resistance. These results prompted us to examine the evolution of resistance in patients with life-threatening bloodstream infections using a similar approach. We found that a similar evolution was taking place in patients under antibiotic treatment: the pathogens first acquired mutations for tolerance and only afterwards acquired antibiotic resistance mutations. Our work provides a new framework for understanding the role of tolerance in the evolution of résistance and points to antibiotic combinations that are potent at delaying its appearance.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

We have shown, by performing experimental evolution experiments under the high concentrations of antibiotics typically achieved in patients, that resistance evolves always first through a tolerance step. In other words, in all our experiments in which resistance to antibiotics evolved, the first mutations that fixed in the population were in fact tolerance mutations, and resistance mutations appeared only as a second step on top of the tolerant background. We were able to reconstruct the evolutionary trajectories in several strains and analyze quantitatively the separate contributions of tolerance and resistance mutations to fitness. Our mathematical analysis identifies tolerance as a key factor to promote the subsequent emergence of resistance. Therefore, preventing tolerance may impede the evolution of resistance.
These results prompted us to develop techniques to monitor the evolution of tolerance in patients. The Tolerance Detection test (TDtest) was then applied to monitor the evolution of tolerance in life-threatening blood infections. Strikingly, we found that tolerance evolves fast and the, similar to our results in vitro, promotes the evolution of resistance. These results point to new antibiotic combinations that could help prevent the evolution of tolerance and resistance.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

The results of our combined approach of experimental evolution in the lab, and the close follow up of the evolution in patients has enabled us to uncover a new evolutionary path by which antibiotic resistance evolves in the lab and in blood infections. Importantly, we have gained new understanding for the drug combinations that could prevent the evolution of resistance.

Automated detection of antibiotic tolerance

The evolutionary path to antibiotic resistance goes first through tolerance