Monday, August 2, 2010

PS 15-122: Biophysical basis underlying parasite resistance: Shedding light on the black box of ecological trade-offs

Devin T. Dobias, Michigan State University, Justin R. Meyer, Michigan State University, Ryan T. Quick, Michigan State University, and Richard E. Lenski, Michigan State University.

Background/Question/Methods

Trade-offs between a host’s resistance to parasites and its competitive fitness in the absence of parasites are thought to be widespread.  Although many studies have documented such trade-offs, the biophysical basis for the trade-offs are rarely known. Understanding the basis is essential to predict what form and magnitude the trade-off takes, as well as predicting how the relationship might vary across environments.  With this deeper understanding, ecologists will be better equipped to understand population dynamics and conditions for coexistence.  For this study, I used a model microbial host and parasite system, Escherichia coli and bacteriophage λ, to investigate the biophysical basis of host trade-offs in this interaction.  I generated a library of resistant E. coli and measured their costs of resistance. I then employed three-dimensional protein models of the mutant proteins to probe the functional basis for the cost to resistance.

Results/Conclusions

Host resistance usually involved mutations in the gene encoding a surface receptor protein, maltoporin, and those mutations were the focus of my analysis.  These mutations typically produce structural changes within the loops of this receptor. These changes appear to cause one of two negative effects on the function of the porin.  The mutated loops inhibit the uptake of resources, or they may promote the entrance of toxins into the cell.  I found that the magnitude of these negative effects correlated with how severely the mutations distorted the porin’s predicted three-dimensional confirmation. Altogether, this poster will address this first step in opening the black box of ecological trade-offs by presenting an integrative analysis based on first principles of protein structure and function in E. coli.