Data from: Associations among antibiotic and phage resistance phenotypes in natural and clinical Escherichia coli isolates

The spread of antibiotic resistance is driving interest in new approaches
to control bacterial pathogens. This includes applying multiple
antibiotics strategically, using bacteriophages against
antibiotic-resistant bacteria, and combining both types of antibacterial
agents. All these approaches rely on or are impacted by associations among
resistance phenotypes (where bacteria resistant to one antibacterial agent
are also relatively susceptible or resistant to others). Experiments with
laboratory strains have shown strong associations between some resistance
phenotypes, but we lack a quantitative understanding of associations among
antibiotic and phage resistance phenotypes in natural and clinical
populations. To address this, we measured resistance to various
antibiotics and bacteriophages for 94 natural and clinical Escherichia
coli isolates. We found several positive associations between resistance
phenotypes across isolates. Associations were on average stronger for
antibacterial agents of the same type (antibiotic-antibiotic or
phage-phage) than different types (antibiotic-phage). Plasmid profiles and
genetic knockouts suggested that such associations can result from both
colocalization of resistance genes and pleiotropic effects of individual
resistance mechanisms, including one case of antibiotic-phage
cross-resistance. Antibiotic resistance was predicted by core genome
phylogeny and plasmid profile, but phage resistance was predicted only by
core genome phylogeny. Finally, we used observed associations to predict
genes involved in a previously uncharacterized phage resistance mechanism,
which we verified using experimental evolution. Our data suggest that
susceptibility to phages and antibiotics are evolving largely
independently, and unlike in experiments with lab strains, negative
associations between antibiotic resistance phenotypes in nature are rare.
This is relevant for treatment scenarios where bacteria encounter multiple
antibacterial agents.