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Optimal foraging predicts the ecology but not the evolution of host specialization in bacteriophages.

Guyader S, Burch CL - PLoS ONE (2008)

Bottom Line: Although generalist phiX174 populations evolved even broader diets at low host density, they did not show a tendency to evolve the predicted specialist foraging strategy at high host density.Similarly, specialist G4 populations were unable to evolve the predicted generalist foraging strategy at low host density.These results demonstrate that optimal foraging models developed to explain the behaviorally determined diets of predators may have only limited success predicting the genetically determined diets of bacteriophage, and that optimal foraging probably plays a smaller role than genetic constraints in the evolution of host specialization in bacteriophages.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, University of North Carolina, Chapel Hill, North Carolina, United States of America.

ABSTRACT
We explore the ability of optimal foraging theory to explain the observation among marine bacteriophages that host range appears to be negatively correlated with host abundance in the local marine environment. We modified Charnov's classic diet composition model to describe the ecological dynamics of the related generalist and specialist bacteriophages phiX174 and G4, and confirmed that specialist phages are ecologically favored only at high host densities. Our modified model accurately predicted the ecological dynamics of phage populations in laboratory microcosms, but had only limited success predicting evolutionary dynamics. We monitored evolution of attachment rate, the phenotype that governs diet breadth, in phage populations adapting to both low and high host density microcosms. Although generalist phiX174 populations evolved even broader diets at low host density, they did not show a tendency to evolve the predicted specialist foraging strategy at high host density. Similarly, specialist G4 populations were unable to evolve the predicted generalist foraging strategy at low host density. These results demonstrate that optimal foraging models developed to explain the behaviorally determined diets of predators may have only limited success predicting the genetically determined diets of bacteriophage, and that optimal foraging probably plays a smaller role than genetic constraints in the evolution of host specialization in bacteriophages.

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Predictions of the optimal foraging model using parameters measured in φX174.Given that φX174 consumes the more profitable host E. coli, we determined the E. coli densities over which φX174 benefits by also consuming the less profitable host S. typhimurium. φX174 should consume S. typhimurium only at host densities where the profitability of S. typhimurium (dashed line) exceeds the growth rate achieved on a diet of only E. coli (solid line). Both quantities are shown on the same scale as the experimental measures, in which growth rate is calculated as the phage concentration after 45 minutes divided by the initial phage concentration. Growth rate on E. coli was calculated as lnBEc/(1/(kEcN)+LEc)×45 minutes, and profitability of S. typhimurium was calcualated as lnBSt/LSt×45 minutes. Both quantities are described in equation 5.
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pone-0001946-g002: Predictions of the optimal foraging model using parameters measured in φX174.Given that φX174 consumes the more profitable host E. coli, we determined the E. coli densities over which φX174 benefits by also consuming the less profitable host S. typhimurium. φX174 should consume S. typhimurium only at host densities where the profitability of S. typhimurium (dashed line) exceeds the growth rate achieved on a diet of only E. coli (solid line). Both quantities are shown on the same scale as the experimental measures, in which growth rate is calculated as the phage concentration after 45 minutes divided by the initial phage concentration. Growth rate on E. coli was calculated as lnBEc/(1/(kEcN)+LEc)×45 minutes, and profitability of S. typhimurium was calcualated as lnBSt/LSt×45 minutes. Both quantities are described in equation 5.

Mentions: Incorporating the measured parameter values into the left and right sides of equation 5, we determined the density of E. coli below which it should be advantageous for φX174 to include S. typhimurium (the less profitable host) in the diet. In Figure 2 we plot the expected rate of energy intake as a function of E. coli density for a diet consisting only of E. coli (right side of equation 5). In addition we plot the profitability of S. typhimurium (left side of equation 5), a quantity that does not depend on host density. The two lines intersect at a host density of 5.03×107 bacteria/mL, indicating that inclusion of S. typhimurium in the diet should be advantageous for E. coli densities below 5×107 bacteria/mL. In other words, the optimal foraging model predicts that the generalist phenotype of φX174 will be advantageous below this cell density, but costly above it.


Optimal foraging predicts the ecology but not the evolution of host specialization in bacteriophages.

Guyader S, Burch CL - PLoS ONE (2008)

Predictions of the optimal foraging model using parameters measured in φX174.Given that φX174 consumes the more profitable host E. coli, we determined the E. coli densities over which φX174 benefits by also consuming the less profitable host S. typhimurium. φX174 should consume S. typhimurium only at host densities where the profitability of S. typhimurium (dashed line) exceeds the growth rate achieved on a diet of only E. coli (solid line). Both quantities are shown on the same scale as the experimental measures, in which growth rate is calculated as the phage concentration after 45 minutes divided by the initial phage concentration. Growth rate on E. coli was calculated as lnBEc/(1/(kEcN)+LEc)×45 minutes, and profitability of S. typhimurium was calcualated as lnBSt/LSt×45 minutes. Both quantities are described in equation 5.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2279161&req=5

pone-0001946-g002: Predictions of the optimal foraging model using parameters measured in φX174.Given that φX174 consumes the more profitable host E. coli, we determined the E. coli densities over which φX174 benefits by also consuming the less profitable host S. typhimurium. φX174 should consume S. typhimurium only at host densities where the profitability of S. typhimurium (dashed line) exceeds the growth rate achieved on a diet of only E. coli (solid line). Both quantities are shown on the same scale as the experimental measures, in which growth rate is calculated as the phage concentration after 45 minutes divided by the initial phage concentration. Growth rate on E. coli was calculated as lnBEc/(1/(kEcN)+LEc)×45 minutes, and profitability of S. typhimurium was calcualated as lnBSt/LSt×45 minutes. Both quantities are described in equation 5.
Mentions: Incorporating the measured parameter values into the left and right sides of equation 5, we determined the density of E. coli below which it should be advantageous for φX174 to include S. typhimurium (the less profitable host) in the diet. In Figure 2 we plot the expected rate of energy intake as a function of E. coli density for a diet consisting only of E. coli (right side of equation 5). In addition we plot the profitability of S. typhimurium (left side of equation 5), a quantity that does not depend on host density. The two lines intersect at a host density of 5.03×107 bacteria/mL, indicating that inclusion of S. typhimurium in the diet should be advantageous for E. coli densities below 5×107 bacteria/mL. In other words, the optimal foraging model predicts that the generalist phenotype of φX174 will be advantageous below this cell density, but costly above it.

Bottom Line: Although generalist phiX174 populations evolved even broader diets at low host density, they did not show a tendency to evolve the predicted specialist foraging strategy at high host density.Similarly, specialist G4 populations were unable to evolve the predicted generalist foraging strategy at low host density.These results demonstrate that optimal foraging models developed to explain the behaviorally determined diets of predators may have only limited success predicting the genetically determined diets of bacteriophage, and that optimal foraging probably plays a smaller role than genetic constraints in the evolution of host specialization in bacteriophages.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, University of North Carolina, Chapel Hill, North Carolina, United States of America.

ABSTRACT
We explore the ability of optimal foraging theory to explain the observation among marine bacteriophages that host range appears to be negatively correlated with host abundance in the local marine environment. We modified Charnov's classic diet composition model to describe the ecological dynamics of the related generalist and specialist bacteriophages phiX174 and G4, and confirmed that specialist phages are ecologically favored only at high host densities. Our modified model accurately predicted the ecological dynamics of phage populations in laboratory microcosms, but had only limited success predicting evolutionary dynamics. We monitored evolution of attachment rate, the phenotype that governs diet breadth, in phage populations adapting to both low and high host density microcosms. Although generalist phiX174 populations evolved even broader diets at low host density, they did not show a tendency to evolve the predicted specialist foraging strategy at high host density. Similarly, specialist G4 populations were unable to evolve the predicted generalist foraging strategy at low host density. These results demonstrate that optimal foraging models developed to explain the behaviorally determined diets of predators may have only limited success predicting the genetically determined diets of bacteriophage, and that optimal foraging probably plays a smaller role than genetic constraints in the evolution of host specialization in bacteriophages.

Show MeSH