Communications BiologySystems BiologyPeer-reviewed journal article
Forecasting cell fate during antibiotic exposure using stochastic gene expression
Abstract
Antibiotic killing does not occur at a single, precise time for all cells within a population. Variability in time to death can be caused by stochastic expression of genes, resulting in differences in endogenous stress-resistance levels between individual cells in a population. This variability can be part of a bet-hedging strategy where cells leverage noise to ensure a subset of the population can tolerate the drug, while decreasing the overall cost of expressing resistance genes. We asked whether single-cell differences in gene expression prior to antibiotic addition were related to cell survival times after antibiotic exposure for a range of genes of diverse function. We quantified the time to death of single cells under antibiotic exposure in combination with expression of reporters. For some reporters, the time to cell death had a strong relationship with the initial expression level of the genes. Reporters that could forecast cell fate included stress response genes, but also genes involved in a variety of other cellular processes like metabolism. Our results highlight the single-cell level non-uniformity of antibiotic killing and also provide examples of key genes where cell-to-cell variation in expression prior to antibiotic exposure is strongly linked to extended durations of antibiotic survival.
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 25
- FWCI
- 2.25
- Field percentile
- top 12%
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