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Assessing the stability of parasite communities through perturbation experiments

通过扰动实验评估寄生虫群落的稳定性

基本信息

批准号：
NE/G007349/1
负责人：
Amy Pedersen
金额：
$ 38.14万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FG007349%2F1
关键词：
Assessing stability parasite communities through

项目摘要

In the past twenty years, there has been a surge of interest in the role of disease on individual health and its effects on host populations. These studies and, indeed, the majority of disease control programmes of humans and domestic animals tend to consider individual infections in isolation. However, hosts are typically infected by many parasite species at any one time. For example, humans, particularly in the developing world, can be simultaneously co-infected with a variety of parasites: around 40.3 million people are currently infected with HIV/AIDS, over one third of the population worldwide has TB, and over one fourth has soil transmitted helminths. Importantly, these co-infecting parasites are unlikely to occur in isolation within each host, indeed there may be a vast network of interactions between them. These interactions may arise through direct competition between parasites within each host. However, they may also be indirect, possibly through competition for shared resources (bottom-up interactions) or via the host's immune system (top-down interactions). In this case, immune responses raised against one parasite may also affect other co-infecting parasite species. Alternatively, if the host is combating one parasite type it may not be able to mount an effective response against another. Therefore there may be a complex network of subtle, and difficult to detect interactions between parasite species that result in a diverse, interactive community within each individual host. Clearly, understanding how these communities are shaped is vital for the design of truly effective and sustainable disease control programs. If control approaches only consider one parasite species there may be unpredictable consequences for disease caused by other, co-infecting parasites. However, current approaches to measure parasite interactions are purely observational and, so far, have produced unclear information about their strength or existence. We propose to adopt a new, direct way of measuring interactions using classical community ecology perturbation experiments, by removing certain parasites from wild wood mice and measuring what happens to the remaining parasite species - if they increase after the target parasites have been removed then this suggests that the target species was previously suppressing their abundance. By repeating this process for all main parasite groups in the wood mice, we can build a more complete picture of how these parasite communities are shaped by the interactions between species. Putting all these interactions into a mathematical model will allow us to predict how such parasite communities will respond to more complex treatments, such as the removal of two species at the same time. If our model predictions prove accurate for more complex co-treatment strategies, then these within host network approaches may provide a vital tool for developing long-term disease control strategies in other host species, such as humans, domestic animals or wildlife threatened to extinction by infectious diseases. It is gradually being realised that parasite co-infections play an important role in the occurrence and management of many diseases of human concern. Given the increasing concerns about emerging infectious diseases around the globe, it has never been more pressing to develop a genuine understanding of the factors affecting parasite invasion, transmission, persistence, and control. This project will be a major step in that direction.

在过去的二十年里，人们对疾病对个人健康的作用及其对宿主群体的影响的兴趣激增。这些研究以及大多数人类和家畜的疾病控制方案都倾向于孤立地考虑个体感染。然而，宿主通常在任何时间被许多寄生虫物种感染。例如，人类，特别是发展中国家的人类，可能同时感染各种寄生虫：目前约有4030万人感染艾滋病毒/艾滋病，全世界三分之一以上的人口患有结核病，四分之一以上的人口患有土壤传播的蠕虫。重要的是，这些共同感染的寄生虫不太可能在每个宿主中孤立地发生，实际上它们之间可能存在巨大的相互作用网络。这些相互作用可能通过每个宿主内寄生虫之间的直接竞争而产生。然而，它们也可能是间接的，可能通过竞争共享资源（自下而上的相互作用）或通过宿主的免疫系统（自上而下的相互作用）。在这种情况下，针对一种寄生虫产生的免疫应答也可能影响其他共感染的寄生虫物种。或者，如果宿主正在对抗一种寄生虫，它可能无法对另一种寄生虫作出有效的反应。因此，可能存在一个复杂的微妙网络，难以检测寄生虫物种之间的相互作用，导致每个宿主内的多样性，相互作用的社区。显然，了解这些社区是如何形成的，对于设计真正有效和可持续的疾病控制计划至关重要。如果控制方法仅考虑一种寄生虫物种，则由其他共感染寄生虫引起的疾病可能会产生不可预测的后果。然而，目前测量寄生虫相互作用的方法纯粹是观察性的，到目前为止，对它们的强度或存在的信息还不清楚。我们建议采用一种新的，直接的方法来测量相互作用，使用经典的社区生态扰动实验，通过从野生木鼠中去除某些寄生虫，并测量剩余的寄生虫物种发生了什么-如果它们在目标寄生虫被去除后增加，那么这表明目标物种以前抑制了它们的丰度。通过对木鼠中所有主要的寄生虫群体重复这一过程，我们可以更完整地了解这些寄生虫群落是如何通过物种之间的相互作用形成的。将所有这些相互作用放入数学模型中，将使我们能够预测这些寄生虫群落将如何对更复杂的处理做出反应，例如同时去除两个物种。如果我们的模型预测证明对于更复杂的共同治疗策略是准确的，那么这些宿主网络方法可能为在其他宿主物种（如人类，家畜或因传染病而濒临灭绝的野生动物）中制定长期疾病控制策略提供重要工具。人们逐渐认识到，寄生虫合并感染在人类关注的许多疾病的发生和管理中起着重要作用。鉴于对地球仪新出现的传染病的日益关注，对影响寄生虫入侵、传播、持久性和控制的因素的真正理解从未像现在这样紧迫。该项目将是朝着这一方向迈出的重要一步。