Connecting theory with data in host-parasite evolution

将宿主-寄生虫进化中的理论与数据联系起来

• 批准号: RGPIN-2016-05488
• 负责人: Bolker, Benjamin
• 金额: $ 3.19万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=645762
• 关键词: Connecting; theory; data; host; parasite

My research programme aims to understand ecological***communities and disease outbreaks by building mathematical and***statistical models to analyze data and connect it with theory. I***propose to explore the short-term evolution of parasites (i.e.,***disease-causing organisms such as viruses, bacteria, or intestinal***worms) and their hosts. Over the long term, parasites often evolve to***intermediate levels of aggressiveness (host exploitation),***compromising between underexploiting their hosts (or being outcompeted***by more aggressive parasites) and killing them too quickly; hosts***evolve to reduce the damaging effects of parasites either by attacking***them (resistance) or learning to live with them (tolerance). Over the***short term, however, e.g. during an epidemic, the direction of***evolution is often surprising; I will make new models, and use***existing data, to predict how parasite exploitation and host defences***co-evolve.******We must consider resistance, tolerance, and exploitation as***interlocking parts of the host-parasite relationship, rather than as***separately evolving traits. While biologists have increasingly adopted***such a holistic view when measuring host resistance and tolerance, we***do not yet have an integrated theoretical framework for the***coevolution of these three traits. I will construct mathematical and***computational models to predict joint changes in resistance,***tolerance, and exploitation during epidemics. Due to data limitations,***at present only simple versions of these models can be used in the***real world, but developing the general models will help us understand***what kinds of data we need to collect in the future in order to***understand and predict the evolution of diseases and their hosts.******Another recent insight of my research programme is that hosts and***diseases can evolve quickly, even as an epidemic spreads in the***population: these “eco-evolutionary” models combine ecological and***evolutionary processes. I have previously developed simple***eco-evolutionary models, but will move forward to build more complex,***realistic models that can be applied and tested against data. In***particular, I will develop eco-evolutionary models for the evolution***of resistance, tolerance and exploitation in HIV (in humans) and in***myxomatosis (in rabbits). While modellers have already begun to tackle***the eco-evolutionary dynamics of these diseases, their models are***missing important components. I will answer the questions: how do***social characteristics like partnership duration or use of sex workers***affect the rate of evolution of HIV and other sexually transmitted***diseases? How do we expect myxomatosis to change over short geographic***scales or over the course of a season?***The answers to these questions will build our understanding of the ecology and evolution of infectious disease, helping us to predict and manage infectious diseases of wildlife, domestic plants and animals, and humans.**

我的研究项目旨在通过建立数学和统计模型来分析数据并将其与理论联系起来，以了解生态***群落和疾病爆发。我***建议探索寄生虫（即***致病生物体，如病毒、细菌或肠道***蠕虫）及其宿主的短期进化。从长远来看，寄生虫通常会进化到***中等程度的攻击性（宿主剥削），***在充分利用宿主（或被更具攻击性的寄生虫竞争***）和过快杀死宿主之间妥协；宿主***通过攻击***寄生虫（抵抗）或学习与寄生虫共存（耐受）来进化以减少寄生虫的破坏性影响。然而，在***短期内，例如疫情期间，***演变的方向往往令人惊讶；我将制作新模型，并使用***现有数据来预测寄生虫利用和宿主防御***如何共同进化。******我们必须将抗性、耐受性和利用视为***宿主-寄生虫关系的连锁部分，而不是***单独进化的特征。虽然生物学家在测量宿主抵抗力和耐受性时越来越多地采用***这样的整体观点，但我们***还没有针对这三个性状的***协同进化的综合理论框架。我将构建数学和计算模型来预测流行病期间抵抗力、耐受力和剥削的联合变化。由于数据限制，***目前只有这些模型的简单版本可以在***现实世界中使用，但开发通用模型将帮助我们了解***未来需要收集哪些类型的数据，以便***理解和预测疾病及其宿主的演变。******我的研究项目的另一个最新见解是，即使流行病在***人群中传播，宿主和***疾病也可以快速进化：这些 “生态进化”模型结合了生态和***进化过程。我之前开发过简单的***生态进化模型，但我将继续构建更复杂的***现实模型，可以根据数据进行应用和测试。 特别是，我将开发生态进化模型，用于艾滋病毒（人类）和粘液瘤病（兔子）的耐药性、耐受性和利用的进化***。虽然建模者已经开始解决***这些疾病的生态进化动力学，但他们的模型***缺少重要组成部分。我将回答以下问题：***诸如伴侣关系持续时间或使用性工作者等社会特征***如何影响艾滋病毒和其他性传播***疾病的进化速度？我们预计粘液瘤病在短期地理***尺度或一个季节的过程中会如何变化？***这些问题的答案将加深我们对传染病的生态和进化的理解，帮助我们预测和管理野生动物、家养动植物以及人类的传染病。**