High-throughput analysis of growth differences among phage strains

Although methods such as spectrophotometry are useful for identifying growth differences among bacterial strains, it is currently difficult to similarly determine whether bacteriophage strains differ in growth using high throughput methods. Here we use automated spectrophotometry to develop an in vitro method for indirectly distinguishing fitness (growth) differences among virus strains, based on direct measures of their infected bacterial hosts. We used computer simulations of a mathematical model for phage growth to predict which features of bacterial growth curves were best associated with differences in growth among phage strains. We then tested these predictions using the in vitro method to confirm which of the inferred viral growth traits best reflected known fitness differences among genotypes of the RNA phage phi-6, when infecting a Pseudomonas syringae host. Results showed that the inferred phage trait of time-to-extinction (time required to drive bacterial density below detectable optical density) reliably correlated with genotype rankings based on absolute fitness (phage titer per ml). These data suggested that the high-throughput analysis was valuable for identifying growth differences among virus strains, and that the method may be especially useful for high throughput analyses of fitness differences among phage strains cultured and/or evolved in liquid (unstructured) environments.

► Automated spectrophotometry of host bacteria as indicator of phage fitness.
► Math model and computer simulation predict phage fitness from host growth.
► Theory predictions confirmed by phage and bacteria experiments.
► Automated results correlate with known phage fitness rankings using classic methods.