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Competition-driven eco-evolutionary feedback reshapes bacterio-phage lambda's fitness landscape and enables speciation.

Michael B DoudAnimesh GuptaVictor LiSarah J MedinaCaesar A De La FuenteJustin R Meyer
Published in: bioRxiv : the preprint server for biology (2023)
A major challenge in evolutionary biology is explaining how populations navigate rugged fitness landscapes without getting trapped on local optima. One idea illustrated by adaptive dynamics theory is that as populations adapt, their newly enhanced capacities to exploit resources alter fitness payoffs and restructure the landscape in ways that promote speciation by opening new adaptive pathways. While there have been indirect tests of this theory, none have measured how fitness landscapes deform during adaptation, or test whether these shifts promote diversification. Here, we achieve this by studying bacteriophage ⋋, a virus that readily speciates into co-existing receptor specialists under controlled laboratory conditions. We used a high-throughput gene editing-phenotyping technology to measure ⋋'s fitness landscape in the presence of different evolved-⋋ competitors and found that the fitness effects of individual mutations, and their epistatic interactions, depend on the competitor. Using these empirical data, we simulated ⋋'s evolution on an un-changing landscape and one that recapitulates how the landscape deforms during evolution. ⋋ heterogeneity only evolved in the shifting landscape regime. This study provides a test of adaptive dynamics, and, more broadly, shows how fitness landscapes dynamically change during adaptation, potentiating phenomena like speciation by opening new adaptive pathways.
Keyphrases
  • body composition
  • physical activity
  • single cell
  • high throughput
  • genome wide
  • dna methylation
  • machine learning