Strain Dependent Genetic Networks for Antibiotic-Sensitivity in a Bacterial Pathogen with a Large Pan-Genome.
The interaction between an antibiotic and bacterium is not merely restricted to the drug and its direct target, rather antibiotic induced stress seems to resonate through the bacterium, creating selective pressures that drive the emergence of adaptive mutations not only in the direct target, but in genes involved in many different fundamental processes as well. Surprisingly, it has been shown that adaptive mutations do not necessarily have the same effect in all species, indicating that the genetic background influences how phenotypes are manifested. However, to what extent the genetic background affects the manner in which a bacterium experiences antibiotic stress, and how this stress is processed is unclear. Here we employ the genome-wide tool Tn-Seq to construct daptomycin-sensitivity profiles for two strains of the bacterial pathogen Streptococcus pneumoniae. Remarkably, over half of the genes that are important for dealing with antibiotic-induced stress in one strain are dispensable in another. By confirming over 100 genotype-phenotype relationships, probing potassium-loss, employing genetic interaction mapping as well as temporal gene-expression experiments we reveal genome-wide conditionally important/essential genes, we discover roles for genes with unknown function, and uncover parts of the antibiotic's mode-of-action. Moreover, by mapping the underlying genomic network for two query genes we encounter little conservation in network connectivity between strains as well as profound differences in regulatory relationships. Our approach uniquely enables genome-wide fitness comparisons across strains, facilitating the discovery that antibiotic responses are complex events that can vary widely between strains, which suggests that in some cases the emergence of resistance could be strain specific and at least for species with a large pan-genome less predictable.
Boston College, Biology Department, Chestnut Hill, Massachusetts, United States of America.
Tim
T
van Opijnen
Boston College, Biology Department, Chestnut Hill, Massachusetts, United States of America.
Sandra
0000-0001-6793-3807
S
Dedrick
Boston College, Computer Science Department, Massachusetts, United States of America.
José
J
Bento
D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D017576:Daptomycin / Q000494:pharmacology*; D024881:Drug Resistance, Bacterial / Q000187:drug effects / Q000235:genetics*; D015964:Gene Expression Regulation, Bacterial / Q000187:drug effects*; D053263:Gene Regulatory Networks / Q000502:physiology*; D016680:Genome, Bacterial; D013296:Streptococcus pneumoniae / Q000235:genetics* / Q000254:growth & development
D000900:Anti-Bacterial Agents; D017576:Daptomycin