Understanding how pathogen diversity is maintained is the central question of this project. It has been suggested that two mechanisms of natural selection may maintain genetic diversity within the bacterium Borrelia burgdorferi: frequency-dependence and host specialization. Computer simulation modeling, field data collection, and molecular techniques will be integrated to evaluate the evidence for these mechanisms of selection. The first aim of this project is to develop a method for identifying different genotypes of B. burgdorferi from a large number of samples. This method will then be used to monitor wildlife populations naturally infected with this pathogen, for evidence of either selection mechanism.

B. burgdorferi is the bacterium that causes Lyme disease, which has a significant public health impact in the United States. Diversity within this species also relates to human illness, as some types tend to cause more severe disease than others. Understanding how this diversity is maintained may provide insight into the evolution of virulence in this bacterium. The molecular identification method to be developed should be an economical and effective tool for further studies on this pathogen and system. Findings will be disseminated to high school students and the general public, via established relationships between the co-PI and various educators and public outreach programs.

Project Report

The diversity of genotypes of Borrelia burgdorferi, the bacterium that causes Lyme disease, provides opportunities to study how and why so many of these types have persisted. One explanation that is thought to apply to many pathogens with this array of diversity, such as malaria and influenza, is frequency-dependent selection. This project has allowed us to test this explanation as a plausible mechanism for maintaining Borrelia burgdorferi diversity. This is particularly important because some genotypes are more likely to cause human disease than others, and a better understanding of what allows these types to persist in nature may allow us to better control disease risk. We tested this hypothesis using a combination of field-collected data and computer simulations. The key comparison in evaluating frequency-dependent selection was measuring how long infected hosts could remain infectious, relative to how long they would remain immune to later infection. Our measurements showed that in this system, this ratio does not support frequency-dependent selection. The generalizations regarding relative duration of host immunity and infectiousness are applicable to other pathogens as well. Depending on how long hosts are infectious and then retain immunity to a pathogen, we can quantify the strength of this form of selection on the pathogen, which provides us with a better understanding of its evolution. In the course of conducting this project, we also developed a relatively inexpensive method to quickly identify genotypes of Borrelia burgdorferi from field-collected samples. This process was formerly time-consuming and cost-prohibitive, limiting the studies that could be performed. This new method should facilitate future research on this important pathogen. To promote this method and ease of use, we created analysis software that is freely available on the co-PI's website. The method protocol will be submitted to a peer-reviewed journal and, once published, will also be widely available. This project created research and teaching opportunities for the co-PI, as well as the early career field assistants who were hired to collect data for this project. Results were shared with participants in the Young Scholars program through Yale University's Center for Analytical Sciences, a program designed to teach biostatistics to local high school students and expose them to a variety of scientific and analytical career paths.

National Science Foundation (NSF)
Division of Environmental Biology (DEB)
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Samuel M. Scheiner
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Yale University
New Haven
United States
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