Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Modulating the evolutionary trajectory of tolerance using antibiotics with different metabolic dependencies

Modulating the evolutionary trajectory of tolerance using antibiotics with different metabolic dependencies

Thumbnail Image
Download
Name

s41467-022-30272-0.pdf

Description
Published version
Size

1.07 MB

Format

Adobe PDF

Checksum (MD5)

41228ca3c42c296a711a9e07ceee179b

sword-2023-01-30T18:30:06.original.xml (130 B)
Original SWORD entry document
Author(s)
Zheng, Erica J
•
Andrews, Ian W
•
Grote, Alexandra T
•
Manson, Abigail L
•
Alcantar, Miguel A
•
Earl, Ashlee M
•
Collins, James J
Date Issued
May 9, 2022
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Zheng, Erica J, Andrews, Ian W, Grote, Alexandra T, Manson, Abigail L, Alcantar, Miguel A et al. 2022. "Modulating the evolutionary trajectory of tolerance using antibiotics with different metabolic dependencies." Nature Communications, 13 (1).
Version
Final published version
Abstract
AbstractAntibiotic 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.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Terms of Use
Creative Commons Attribution 4.0 International license
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/147786
DOI of Published Version
https://doi.org/10.1038/s41467-022-30272-0
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.