Details
- Autor(en) / Beteiligte
- Titel
- Fast bacterial growth reduces antibiotic accumulation and efficacy
- Ist Teil von
- eLife, 2022-06, Vol.11
- Ort / Verlag
- England: eLife Sciences Publications Ltd
- Erscheinungsjahr
- 2022
- Link zum Volltext
- Quelle
- EZB Free E-Journals
- Beschreibungen/Notizen
- Phenotypic variations between individual microbial cells play a key role in the resistance of microbial pathogens to pharmacotherapies. Nevertheless, little is known about cell individuality in antibiotic accumulation. Here, we hypothesise that phenotypic diversification can be driven by fundamental cell-to-cell differences in drug transport rates. To test this hypothesis, we employed microfluidics-based single-cell microscopy, libraries of fluorescent antibiotic probes and mathematical modelling. This approach allowed us to rapidly identify phenotypic variants that avoid antibiotic accumulation within populations of , , and . Crucially, we found that fast growing phenotypic variants avoid macrolide accumulation and survive treatment without genetic mutations. These findings are in contrast with the current consensus that cellular dormancy and slow metabolism underlie bacterial survival to antibiotics. Our results also show that fast growing variants display significantly higher expression of ribosomal promoters before drug treatment compared to slow growing variants. Drug-free active ribosomes facilitate essential cellular processes in these fast-growing variants, including efflux that can reduce macrolide accumulation. We used this new knowledge to eradicate variants that displayed low antibiotic accumulation through the chemical manipulation of their outer membrane inspiring new avenues to overcome current antibiotic treatment failures.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 2050-084XeISSN: 2050-084XDOI: 10.7554/elife.74062Titel-ID: cdi_doaj_primary_oai_doaj_org_article_f9443964bba24775899537b4edeb0b4a
- Format
- –
- Schlagworte
- Anti-Bacterial Agents - metabolism, Anti-Bacterial Agents - pharmacology, antibiotic resistance, antibiotic uptake, Antibiotics, Antimicrobial agents, Bacteria, Bacterial infections, Datasets, Dormancy, Drug resistance, Drug Resistance, Bacterial - genetics, E coli, Escherichia coli - genetics, Escherichia coli - metabolism, Escherichia coli Proteins - metabolism, Fluorescent indicators, Gram-negative bacteria, Macrolides, Mathematical models, membrane transport, Microbial Sensitivity Tests, Microbiology and Infectious Disease, Microfluidics, Microscopy, phenotypic heterogeneity, Phenotypic variations, Physics of Living Systems, Population, Pseudomonas aeruginosa - metabolism, Ribosomes, single-cell analysis