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Dryad

Diversity in CRISPR-based immunity protects susceptible genotypes by restricting phage spread and evolution

Cite this dataset

Common, Jack; Walker-Sünderhauf, David; van Houte, Stineke; Westra, Edze (2020). Diversity in CRISPR-based immunity protects susceptible genotypes by restricting phage spread and evolution [Dataset]. Dryad. https://doi.org/10.5061/dryad.66t1g1k00

Abstract

Diversity in host resistance often associates with reduced pathogen spread. This may result from ecological and evolutionary processes, likely with feedback between them. Theory and experiments on bacteria-phage interactions have shown that genetic diversity of the bacterial adaptive immune system can limit phage evolution to overcome resistance. Using the CRISPR-Cas bacterial immune system and lytic phage, we engineered a host-pathogen system where each bacterial host genotype could be infected by only one phage genotype. With this model system, we explored how CRISPR diversity impacts the spread of phage when they can overcome a resistance allele, how immune diversity affects the evolution of the phage to increase its host range, and if there was feedback between these processes. We show that increasing CRISPR diversity benefits susceptible bacteria via a dilution effect, which limits the spread of the phage. We suggest that this ecological effect impacts the evolution of novel phage genotypes, which then feeds back into phage population dynamics.

Usage notes

Anyone wishing to use this dataset is suggested to go to this paper's GitHub - github.com/JackCommon/Common_etal_2020

Funding

Biotechnology and Biological Sciences Research Council, Award: BB/J014400/1

Biotechnology and Biological Sciences Research Council, Award: BB/M009122/1

Medical Research Council, Award: MR/N013794/1

Biotechnology and Biological Sciences Research Council, Award: BB/R010781/1

European Research Council, Award: 660039

Biotechnology and Biological Sciences Research Council, Award: BB/N017412/1

Natural Environment Research Council, Award: NE/M018350/1

European Research Council, Award: ERC-STG-2016-714478 – EVOIMMECH