bioRxivEvolutionary Biology
Adaptations accumulated under prolonged resource exhaustion are highly transient
Abstract
Many non-sproulating bacterial species can survive for years within exhausted growth media in a state termed long-term stationary phase (LTSP). We have been carrying out evolutionary experiments aimed at elucidating the dynamics of genetic adaptation under LTSP. We showed that Escherichia coli adapts to prolonged resource exhaustion through the highly convergent acquisition of mutations. In the most striking example of such convergent adaptation, we observed that across all independently evolving LTSP populations, over 90% of E. coli cells carry mutations to one of three specific sites of the RNA polymerase core enzyme (RNAPC). These LTSP adaptations reduce the ability of the cells carrying them to grow once fresh resources are again provided. Here, we examine how LTSP populations recover from costs associated with their adaptation, once resources are again provided to them. We demonstrate that due to the ability of LTSP populations to maintain high levels of standing genetic variation during adaptation, costly adaptations are very rapidly purged from the population once they are provided with fresh resources. We further demonstrate that recovery from costs acquired during adaptation under LTSP occurs much more rapidly than would be possible if LTSP adaptations had fixed during the time populations spent under resource exhaustion. Finally, we previously reported that under LTSP, some clones develop a mutator phenotype, greatly increasing their mutation accumulation rates. Here, we show that the mechanisms, by which populations recover from costs associated with fixed adaptations, may depend on mutator status.
- organism: E. coli
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: variant calling
- approach: experimental assay
- approach: genetic perturbation / CRISPR
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