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December 13, 2018Open Access

Forecasting when cells die during antibiotic exposure using stochastic gene expression

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Authors

NRNicholas A. RossiIMImane El MeoucheMDMary J. Dunlop

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Overview

Randomized trial investigates how gene expression variability affects cell survival times post-antibiotic exposure, suggesting important implications for treatment strategies.

Key Points

  • This research aims to determine the relationship between single-cell gene expression differences and survival times following antibiotic exposure.
  • Quantified time to death for single cells under antibiotic exposure
  • Analyzed the relationship between initial gene expression levels and cell survival times
  • Utilized reporters to assess diverse gene functions related to stress response and metabolism.
  • Cells with higher initial expression of specific stress response genes showed longer survival times after antibiotic exposure.
  • Certain genes' expression levels can effectively forecast cell fate, linking gene function diversity to survival durations.
  • Demonstrated non-uniformity in cell killing among the population based on individual gene expression variations.

Cite This Study

Rossi et al. (2018) studied this question.

synapsesocial.com/papers/6a1dc102871ff5209bef511fhttps://doi.org/10.1101/494161
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Gene Expression Tradeoffs Determine Bacterial Survival and Adaptation to Antibiotic Stress2024 · 14 citations
  2. 2Hysteresis and noise floor in gene expression optimised for persistence against lethal events2024
  3. 3Slow trajectories generate divergent cell fates following antibiotic stress2025
  4. 4Pre-treatment bacterial cell states shape antibiotic-induced transcriptional reprogramming and survival2026
  5. 5Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures2024 · 14 citations