Linking host energetics and multiple host defenses to transmission and virulence evolution
Linking host energetics and multiple host defenses to transmission and virulence evolution
批准号:
10222441
负责人:
Jessica Leigh Hite
金额:
$0.58万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2020-09-30
关键词:
AddressAffectBiologicalBiological AssayBiologyBudgetsCollaborationsCosts and BenefitsDaphniaDataDefense MechanismsDevelopmentDietDiseaseDisease ManagementEnvironmentEpidemiologyEquilibriumEvolutionFeedbackFutureGenerationsGeneticGenetic DeterminismGenetic MarkersGenotypeGrowthHost DefenseHost Defense MechanismImmune systemIndividualInfectionJointsLife TablesLinkModelingNaturePharmaceutical PreparationsPhysiological ProcessesPhysiologyPopulationProcessProductionReproductionResourcesSamplingSeveritiesShapesSystemTestingVaccinesVariantVirulenceclaycostdensityexperimental studyhuman diseaseimmune functionimprovedinsightmathematical modelnovelpathogenpathogen exposurepathogenic bacteriatheoriestraittransmission process
中文摘要
项目总结
病原菌特性的进化,如毒力和传播性,构成了越来越多的
对基础生物学和应用生物学的巨大挑战。毒力和传播从根本上说
疾病的严重程度和传播以及这些特征的频繁演变
破坏减轻疾病的战略(例如,疫苗、药物、饮食)。预测毒力
进化仍然具有挑战性,这在很大程度上是因为
病原体的进化,即宿主防御,仍然知之甚少。多主机防御
机制强烈地决定了病原体的产生(在宿主内),从而决定了传播。
在种群水平上的宿主之间。因此,无论是主机内进程还是主机间进程
最终控制病原体的进化。然而,宿主防御机制及其对
传播也很难解开。主机防御耗费巨大,干扰
彼此之间以及与寄主生理的其他方面(例如,生长、繁殖)之间的差异
宿主基因类型,对环境条件(例如,资源的可用性)很敏感。更好
了解主机内部进程及其对传输的影响将大大
提高我们将这些不同规模的生物组织与病原体进化联系起来的能力。
最近的理论表明,这种跨尺度的联系可以提供对病原体的关键洞察
进化论。然而,到目前为止,这一理论还没有得到实证检验。
我们建议确定宿主能量学和多个
宿主防御机制塑造了毒力和传播的进化。这个项目
将(I)新的能量和进化理论的发展与(Ii)个体和
使用模型寄主-病原体系统的种群水平实验,大型水蚤和
分枝巴氏杆菌(利用该系统众所周知的遗传和环境变异
主持辩护并严格检验理论预测)。这一整合将决定(1)
不同寄主防御机制对病原菌产生的独特和综合影响;
资源可获得性的环境变化如何影响宿主防御策略、病原体
生产、毒力和传播;(3)是否理解机理
宿主内部和宿主之间的连接提高了我们准确预测病原体的能力
在不同的环境和遗传背景下的进化。我们将发展
明确整合资源(寄主饮食)以及寄主内和寄主之间的数学模型
预测流行病学和进化动态的寄主动态(毒力和传播
进化论)。
英文摘要
PROJECT SUMMARY
The evolution of pathogen traits such as virulence and transmission poses an increasingly
formidable challenge to basic and applied biology. Virulence and transmission fundamentally
shape the severity and spread of disease and the evolution of these traits frequently
undermines strategies to mitigate disease (e.g., vaccines, drugs, diet). Predicting virulence
evolution remains challenging, in large part, because one of the most important drivers of
pathogen evolution, host defense, remains poorly understood. Multiple host defense
mechanisms strongly determine pathogen production (within hosts) and thus transmission
between hosts at the population-level. Hence, both within-host and between-host processes
ultimately govern pathogen evolution. Yet, host defense mechanisms and their effects on
transmission are also difficult to unravel. Host defenses are energetically costly, interfere with
one another and with other aspects of host physiology (e.g., growth, reproduction), vary across
host genotypes, and are sensitive to environmental conditions (e.g., resource availability). Better
understanding of within-host processes and their effects on transmission will substantially
improve our ability to link these different scales of biological organization to pathogen evolution.
Recent theory suggests that such cross-scale links can provide key insight into pathogen
evolution. To date, however, this theory has not been tested empirically.
We propose to identify how fundamental interactions between host energetics and multiple
host defense mechanisms shape the evolution of virulence and transmission. This project
integrates (i) the development of novel energetic and evolutionary theory with (ii) individual and
population-level experiments using a model host-pathogen system, Daphnia magna and
Pasteuria ramosa (to leverage this system’s well-known genetic and environmental variation in
host defense and rigorously test theoretical predictions). This integration will determine (1) the
unique and composite effects of different host defense mechanisms on pathogen production; (2)
how environmental variation in resource availability affects host defense strategies, pathogen
production, virulence, and transmission; and (3) whether understanding mechanistic
connections within and between hosts improves our ability to accurately predict pathogen
evolution across different environmental and genetic backgrounds. We will develop
mathematical models that explicitly integrate resources (host diet) and within-host and between-
host dynamics to predict epidemiological and evolutionary dynamics (virulence and transmission
evolution).
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