Microfluidics for single-cell study of antibiotic tolerance and persistence induced by nutrient limitation

Stefany Moreno-Gámez*, Alma Dal Co, Simon van Vliet, Martin Ackermann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

3 Citations (Scopus)
150 Downloads (Pure)

Abstract

Nutrient limitation is one of the most common triggers of antibiotic tolerance and persistence. Here, we present two microfluidic setups to study how spatial and temporal variation in nutrient availability lead to increased survival of bacteria to antibiotics. The first setup is designed to mimic the growth dynamics of bacteria in spatially structured populations (e.g., biofilms) and can be used to study how spatial gradients in nutrient availability, created by the collective metabolic activity of a population, increase antibiotic tolerance. The second setup captures the dynamics of feast-and-famine cycles that bacteria recurrently encounter in nature, and can be used to study how phenotypic heterogeneity in growth resumption after starvation increases survival of clonal bacterial populations. In both setups, the growth rates and metabolic activity of bacteria can be measured at the single-cell level. This is useful to build a mechanistic understanding of how spatiotemporal variation in nutrient availability triggers bacteria to enter phenotypic states that increase their tolerance to antibiotics.

Original languageEnglish
Title of host publicationBacterial Persistence
EditorsNatalie Verstraeten, Jan Michiels
PublisherHumana Press
Chapter8
Pages107-124
Number of pages18
Edition2
ISBN (Electronic)978-1-0716-1621-5
ISBN (Print)978-1-0716-1620-8, 978-1-0716-1623-9
DOIs
Publication statusPublished - 2021

Publication series

NameMethods in Molecular Biology
Volume2357
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Antibiotic persistence
  • Antibiotic tolerance
  • Biofilms
  • Feast-and-famine dynamics
  • Microfluidics
  • Nutrient limitation
  • Phenotypic heterogeneity
  • Single-cell measurements

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