deCiphering bacterial peRsIsTence of Individual Cells down to Atomic Level

Project Details

Description

Urinary tract infections (UTIs) are a worldwide health concern and are mainly caused by uropathogenic
Escherichia coli (UPEC). Antibiotic therapy failure and the chronic nature of UTIs can be attributed to a small
fraction of transiently non-growing, antibiotic-tolerant cells called persisters. An innovative strategy to cure
chronic UTIs would be to induce growth resumption in UPEC persisters, thereby re-sensitizing them to
conventional antibiotics. However, our current understanding of persister awakening is far from complete,
hampering the development of anti-persister drugs. The aim of this project is to study and understand
awakening of UPEC persisters in individual cells up to the atomic level. To reach this goal, we have assembled
a strong multi-disciplinary consortium with highly complementary expertise. We will identify novel genes and
regulatory RNAs involved in awakening by single-cell RNA-seq and by screening a pooled CRISPRi library.
Furthermore, we will characterize persister effectors at unprecedented detail by combining genetic,
biochemical and structural approaches. Finally, in view of developing therapeutics to stimulate awakening, we
will validate our findings in a collection of clinically relevant strains and a model of intracellular infection.
Combined, results from this project will lead to ground-breaking new insights in persister awakening and will
pave the way for the development of critically needed anti-persister drugs to effectively clear UTIs.
Short title or EU acronymCRITICAL
AcronymFWOEOS16
StatusActive
Effective start/end date1/01/2231/12/25

Keywords

  • (p)ppGp
  • Bacterial persistence
  • awakening
  • resuscitation
  • CRISPRi
  • single cell RNA-seq
  • cellular infection model
  • obg

Flemish discipline codes in use since 2023

  • Cell growth and development
  • Bioinformatics data integration and network biology
  • Bacteriology
  • Structural biology
  • Transcriptomics
  • Single-cell data analysis
  • Medicinal chemistry
  • Interactomics

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