The Effect of Competitive and Mutualist Bacteria on the Infection Rate of Generalist Phage N

Abstract

To better understand the host range of viruses, it is important to understand how interspecies interactions such as mutualism and competition impact how and why viruses are able to infect multiple hosts or just one. In this experiment, lawns of E. coli and S. enterica were plated in either a cooperative environment or a competitive environment and subsequently infected with both a generalist bacteriophage and a specialist bacteriophage. The generalist phage, N, was able to infect both E. coli and S. enterica. T7 was one specialist phage and could only infect E. coli. P22 was the other specialist phage and could only infect S. enterica. In the competitive environment, mathematical modeling predicted that the generalist would perform better than the specialist phage, resulting in a higher yield of the generalist after 48 hours. In the cooperative environment, modeling predicted that the specialist would outperform the generalist phage, resulting in a higher yield of specialist after 48 hours. In the cooperative experiment, the generalist was expected to have a lower infection rate compared to the initial phage dilutions. While our experimental results in both competitive conditions, T7/N and P22/N, were consistent with our hypothesis, the cooperative resulted deviated: in the P22/N data, the specialist phage indeed outperformed the generalist, but the opposite was seen in the T7/N data. However, our data were not statistically significant, and there were many possible sources of error that could have led to these unexpected results, such as measurement or mathematical errors resulting in unbalanced starting phage ratios, N being better at infecting E. coli than S. enterica, or due to contamination of the cultures with bacteria resistant to T7. If after further experimentation and resolution of these errors, these data hold true, this would be extremely interesting for further investigate as they do not match expectations based on modeling or batch culture experimentation.