Testing community ecology theory as a framework for predicting co-infection: host resource ratios and viral pathogens

测试群落生态理论作为预测共同感染的框架：宿主资源比率和病毒病原体

• 批准号: 1556649
• 负责人: Eric Seabloom
• 金额: $ 64.82万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-15 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1556649&HistoricalAwards=false
• 关键词: Testing; community; ecology; theory; framework

A vast array of microbes (microscopic organisms), such as fungi, bacteria, and viruses, live inside every animal and plant on Earth. These microbial communities influence the growth, reproduction, and death rates of their hosts. Not all microbes are detrimental; the effects of microbes span the full range from causing deadly disease to being essential for host health. Despite the importance of microbial diversity to host well-being, we have little ability to predict the diversity and composition of microbial communities within hosts. This project will address this knowledge gap by testing whether a mathematical model developed originally for plants and algae ('resource-ratio theory') can be used to understand what determines the diversity and composition of the microbes that inhabit plant hosts. The data from these experiments will be used to understand when the predictions of the resource-ratio model apply to microbial communities and how it can be modified to make better predictions. A deeper understanding of the controls on microbial diversity will lead to more accurate predictions about microbes within hosts, which may speed advances in medicine and agriculture.The researchers will grow plants in conditions that vary in the supply of critical soil nutrients, and they will manipulate and measure the abundance and diversity of a group of plant viruses that cause one of the most widespread and devastating diseases of cereal crops worldwide (barley and cereal yellow dwarf viruses; B/CYDV's). Five B/CYD virus species will be used to test the resource-ratio model in a series of growth-chamber and field experiments. In each experiment, they will create a wide range of conditions experienced by the viruses by growing host plants under different resource (nitrogen and phosphorus) supply rates. The researchers will measure viral abundance (titer) within individuals, using quantitative Polymerase Chain Reaction (qPCR) for each virus grown alone and in mixture. They will use viral abundance measurements through time to estimate virus population growth rates. The resource-ratio model will be tested with lab experiments, in order to predict viral diversity in each host. The resource-ratio model will also be modified to include elements of the virus and host biology that could cause deviations from the classic theory, such as host defences against infection by microbes and microbial effects on host nutrient content. To test the relevance of this model to more complex natural communities, the researchers will collect data on B/CYDV titers in field experiments replicated at a local field site and in 30 grasslands spanning 5 continents.

大量的微生物（微生物），如真菌，细菌和病毒，生活在地球上的每一种动物和植物体内。这些微生物群落影响宿主的生长、繁殖和死亡率。并非所有的微生物都是有害的;微生物的影响范围很广，从导致致命疾病到对宿主健康至关重要。尽管微生物多样性对宿主的健康很重要，但我们几乎没有能力预测宿主内微生物群落的多样性和组成。该项目将通过测试最初为植物和藻类开发的数学模型（“资源比例理论”）是否可以用于了解是什么决定了栖息在植物宿主中的微生物的多样性和组成来解决这一知识差距。来自这些实验的数据将用于了解资源比率模型的预测何时适用于微生物群落，以及如何对其进行修改以做出更好的预测。对微生物多样性控制的更深入理解将导致对宿主体内微生物的更准确预测，这可能会加速医学和农业的进步。研究人员将在关键土壤养分供应不同的条件下种植植物，他们将操纵和测量一组植物病毒的丰度和多样性，这些病毒导致谷类作物最广泛和最具破坏性的疾病之一全世界（大麦和谷类黄矮病毒; B/CYDV）。将使用五种B/CYD病毒在一系列生长室和田间实验中检验资源比率模型。在每个实验中，他们将通过在不同的资源（氮和磷）供应率下种植宿主植物来创造病毒所经历的各种条件。研究人员将使用定量聚合酶链反应（qPCR）测量个体内的病毒丰度（滴度），用于单独和混合生长的每种病毒。他们将使用病毒丰度测量来估计病毒种群的增长率。资源比率模型将通过实验室实验进行测试，以预测每种宿主中的病毒多样性。资源比率模型也将被修改，以包括可能导致偏离经典理论的病毒和宿主生物学因素，例如宿主对微生物感染的防御和微生物对宿主营养成分的影响。为了测试该模型与更复杂的自然群落的相关性，研究人员将在当地实地和跨越5大洲的30个草原进行的实地实验中收集B/CYDV滴度的数据。