Lysis timing and bacteriophage fitness

Abstract

The effect of lysis timing on bacteriophage (phage) fitness has received little theoretical or experimental attention. Previously, the impact of lysis timing on phage fitness was studied using a theoretical model based on the marginal value theorem from the optimal foraging theory. An implicit conclusion of the model is that, for any combination of host quantity and quality, an optimal time to lyse the host would exist so that the phage fitness would be the highest. To test the prediction, an array of isogenic lambda-phages that differ only in their lysis times was constructed. For each phage strain, the lysis time, burst size, and fitness (growth rate) were determined. The result showed that there is a positive linear relationship between lysis time and burst size. Moreover, the strain with an intermediate lysis time has the highest fitness, indicating the existence of an optimal lysis time. A mathematical model is also constructed to describe the population dynamics of phage infection. Computer simulations using parameter values derived from phage lambda-infection also showed an optimal lysis time. However, both the optimum and the fitness are different from the experimental result. The evolution of phage lysis timing is discussed from the perspectives of multiple infection and life-history trait evolution.

Figure 1.

Construction of isogenic λ-strains. Various plasmids carrying different λ S alleles (Sx) were each transformed into the E. coli lysogen carrying a prophage λ with mutations in cI (cI857) and S (Sam7) genes. After thermal induction of the lysogen, a mixture of phage progeny is produced, but only ones carrying the Sx allele (as a result of homologous recombination between prophage genome and the plasmid) can form plaques when plated on the bacterial host.

Figure 2.

Topology of the λ-S105 holin protein. The S105 protein has three α-helical transmembrane domains (rounded rectangles) with an N-out, C-in configuration. For various S alleles used in this study, mutations are also mapped onto the secondary structure. See Table 2 for the S allele genotypes.

Figure 3.

The lysis curves of three λ S alleles. The culture turbidity (in A₅₅₀) was sampled every 2 min using a sipper-equipped spectrophotometer. In this particular example, the lysis times for λ(S105_L14C/C51S) (▪), λ(Swt) (•), and λ(S_S68C) (▴) are 41, 51, and 63 min, respectively.

Figure 4.

An example of the population dynamics during fitness assay. The concentrations of E. coli (○) infected with λ(S105) (•) were plotted against time. Another phage strain, λ(S105_C51S/S76C) (▪), was also plotted (the corresponding host concentration is not shown).

Figure 5.

The effect of lysis time on burst size and fitness. For each of the 11 S alleles, burst size (□), individual fitness measurements (•), and average fitness (○) are plotted against their corresponding lysis times. Error bars indicate one standard error. The dashed curve shows the quadratic fit of the individual fitness measurements, and the solid linear line represents the regression of burst size on lysis time.

Figure 6.

Simulated infection dynamics in a tube culture. The uninfected host (thick solid line), infected host (short dotted line), and phage (dashed line) concentrations were plotted against time after infection. The parameter values used in the simulation are derived from phage λ(S105) with lysis time of 42.7 min and from its bacterial host E. coli K12 (see text for more details). The experimental data of uninfected host (thin solid line with ○) and phage (thin dashed line with •) (from Figure 4) were superimposed on the simulation result.

Figure 7.

Phage fitness calculated from simulated infection dynamics. The calculated phage fitness [•, using w = (P₅/P₀)/5], the experimental results with error bars (○, from Figure 5), and the quadratic fit (dashed curve, from Figure 5) are shown.