Dissertation Research: Evolution of Virulence in Sterilizing Pathogens: Spatial Models and Field Studies

论文研究：灭菌病原体毒力的进化：空间模型和实地研究

• 批准号: 9972650
• 负责人: Janis Antonovics
• 金额: $ 0.49万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-07-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9972650&HistoricalAwards=false
• 关键词: Dissertation; Research; Evolution; Virulence; Sterilizing

Antonovics9976250It is commonly suggested that pathogens will evolve toward being harmless so as not to cause the extinction of the host population and hence of themselves. This idea has been disputed on the grounds that selection for reduced virulence would require differential extinction of whole populations, a process that has been considered to be slow and ineffective. This study will use theoretical models to investigate whether the evolution of reduced virulence can occur in situations where the host and pathogen are distributed over a large spatial area, but where their dispersal is much more local. Model assumptions will be tested using the anther-smut disease of white campion. This is as a well-studied disease that partly sterilizes its host. Given present day concerns about emerging infectious diseases, it is important to understand why some pathogens cause very severe disease symptoms, yet others have only a small effect on their hosts. Disease symptoms can change over time as a result of pathogen evolution, but the predicted direction and mechanism of such change has been very controversial. This study will model the processes involved, and therefore help predict possible future directions of change in the severity of infectious diseases.

Antonovics9976250 人们普遍认为，病原体将进化为无害，以免导致宿主群体及其自身的灭绝。 这一想法受到了争议，因为选择降低毒力需要对整个种群进行差异性灭绝，这一过程被认为是缓慢且无效的。 这项研究将使用理论模型来研究在宿主和病原体分布在较大空间区域但其传播更为局部的情况下是否会发生毒力降低的进化。 模型假设将使用白花花药黑粉病进行测试。 这是一种经过充分研究的疾病，可以部分使其宿主绝育。 鉴于目前人们对新出现的传染病的担忧，了解为什么某些病原体会引起非常严重的疾病症状，而另一些病原体对其宿主的影响却很小，这一点很重要。由于病原体的进化，疾病症状可能会随着时间的推移而发生变化，但这种变化的预测方向和机制一直存在很大争议。 这项研究将对所涉及的过程进行建模，从而有助于预测传染病严重程度未来可能的变化方向。