Abstract

Antibiotic tolerance, or the ability of bacteria to survive antibiotic treatment in the absence of genetic resistance, has been linked to chronic and recurrent infections. Tolerant cells are often characterized by a low metabolic state, against which most clinically used antibiotics are ineffective. Here, we show that tolerance readily evolves against antibiotics that are strongly dependent on bacterial metabolism, but does not arise against antibiotics whose efficacy is only minimally affected by metabolic state. We identify a mechanism of tolerance evolution in E. coli involving deletion of the sodium-proton antiporter gene nhaA, which results in downregulated metabolism and upregulated stress responses. Additionally, we find that cycling of antibiotics with different metabolic dependencies interrupts evolution of tolerance in vitro, increasing the lifetime of treatment efficacy. Our work highlights the potential for limiting the occurrence and extent of tolerance by accounting for antibiotic dependencies on bacterial metabolism.

Antibiotic tolerance, or the ability of bacteria to survive antibiotic treatment in the absence of genetic resistance, often involves a low metabolic state. Here, Zheng et al. show that tolerance does not readily evolve against antibiotics whose efficacy is only minimally affected by bacterial metabolism, and find that cycling of antibiotics with different metabolic dependencies interrupts evolution of tolerance.

Details

Title
Modulating the evolutionary trajectory of tolerance using antibiotics with different metabolic dependencies
Author
Zheng, Erica J 1 ; Andrews, Ian W 2 ; Grote, Alexandra T 3 ; Manson, Abigail L 3   VIAFID ORCID Logo  ; Alcantar, Miguel A 4   VIAFID ORCID Logo  ; Earl, Ashlee M 3   VIAFID ORCID Logo  ; Collins, James J 5   VIAFID ORCID Logo 

 Harvard University, Program in Chemical Biology, Cambridge, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Broad Institute of MIT and Harvard, Infectious Disease and Microbiome Program, Cambridge, USA (GRID:grid.66859.34) (ISNI:0000 0004 0546 1623) 
 Broad Institute of MIT and Harvard, Infectious Disease and Microbiome Program, Cambridge, USA (GRID:grid.66859.34) (ISNI:0000 0004 0546 1623); Massachusetts Institute of Technology, Institute for Medical Engineering & Science, Department of Biological Engineering, and Synthetic Biology Center, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Broad Institute of MIT and Harvard, Infectious Disease and Microbiome Program, Cambridge, USA (GRID:grid.66859.34) (ISNI:0000 0004 0546 1623) 
 Massachusetts Institute of Technology, Institute for Medical Engineering & Science, Department of Biological Engineering, and Synthetic Biology Center, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Broad Institute of MIT and Harvard, Infectious Disease and Microbiome Program, Cambridge, USA (GRID:grid.66859.34) (ISNI:0000 0004 0546 1623); Massachusetts Institute of Technology, Institute for Medical Engineering & Science, Department of Biological Engineering, and Synthetic Biology Center, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Harvard University, Wyss Institute for Biologically Inspired Engineering, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Harvard-MIT Program in Health Sciences and Technology, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2661264523
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.