Multi-level dynamics of viral co-infection
病毒共感染的多层次动态
基本信息
- 批准号:9034607
- 负责人:
- 金额:$ 32.05万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:
- 资助国家:美国
- 起止时间:至
- 项目状态:未结题
- 来源:
- 关键词:AddressAdultAffectAntiviral ResponseBindingBiological ModelsCollaborationsCommunicable DiseasesCommunitiesComplementComplexDataData SetDemographyDevelopmentDrosophila C virusDrosophila genusEnvironmentEpidemiologic StudiesEpidemiologyFertilityFutureGene ExpressionGeneticGoalsGrowthHumanIdahoImmune responseImmunologyIndividualInfectionInsectaInvertebratesLaboratoriesLeadMetabolic Clearance RateModelingMolecularOrganismOutcomeParentsPathogenesisPathologyPopulationPopulation DynamicsProcessPropertyPublic HealthResearchSatellite VirusesStatistical ModelsSystemTechnologyTestingTimeUniversitiesViralViral VectorVirusVirus DiseasesWorkbaseco-infectionexpectationflyinterestmathematical modelmortalityoffspringoral infectionpathogenresponsetooltranscriptometransmission processvectorviral transmissionvirology
项目摘要
Epidemiological data suggest that viruses that co-circulate within human populations interact in unique ways
that can result in altered replication, pathogenesis, and transmission dynamics compared to how they would
operate in isolation. In order to understand the effects of viral co-infection at population levels, it is critical to
dissect the mechanisms of interaction between viruses at multiple levels within their shared host. A system in
which multiple viruses and hosts can be manipulated is critical for modeling how unrelated viruses interact
within their shared hosts and how these interactions alter the effects of infection. The long-term goal of this
research is to uncover properties of viral co-infection that can be tested for generality in other systems. The
objectives of the proposed study are to establish a tractable invertebrate model system of viral infection and
co-infection, and to develop mathematical models to understand how viruses interact with each other and their
host to ultimately affect the host pathology and population dynamics. Drosophila and associated viruses will be
used to test the central hypothesis that co-infection results in non-additive effects relative to single infections,
and that these effects are correlated at different levels of organization. Oral infection of adult flies with
Drosophila C virus (DCV) and Drosophila X virus (DXV) will be used to test the effects of co-infection on viral
growth dynamics, host gene expression, viral transmission rates, and host demography, including fecundity,
developmental rate, and mortality. Aim 1 will focus on molecular interactions, by quantifying viral growth
dynamics and characterizing the host transcriptome in response to single and dual virus infections in adult
flies. In Aim 2, the effects of co-infection on both direct and environmental transmission of the viruses will be
determined. Fecundity, offspring developmental rate, and mortality are major contributors to population
dynamics and will thus be the focus of Aim 3. Understanding how co-infection alters fly demography will lead to
modeling of long-term impacts of co-circulating viruses in infected populations. Statistical and mathematical
modeling within and between the three aims will be used to describe the interactions between DCV and DXV
within their shared host. This study will advance the field by generating rich datasets to test models of viral co-
infection and by establishing a tractable model system for the study of viral co-infection at multiple
organizational levels.
流行病学数据表明,在人群中共同传播的病毒以独特的方式相互作用
这可能会导致复制,发病机制和传播动力学的改变,
孤立地运作。为了了解病毒合并感染在人群水平上的影响,
剖析病毒在其共享宿主内多层次相互作用的机制。的系统
哪一种病毒和宿主可以被操纵对于模拟不相关的病毒如何相互作用至关重要
以及这些相互作用如何改变感染的效果。长期目标是
研究的目的是揭示病毒共感染的特性,这些特性可以在其他系统中进行通用性测试。的
本研究的目的是建立一个易于处理的无脊椎动物病毒感染模型系统,
共同感染,并开发数学模型,以了解病毒如何相互作用,
最终影响宿主病理学和种群动态。果蝇和相关的病毒
用于检验合并感染相对于单一感染导致非累加效应的中心假设,
这些影响在不同的组织层次上是相互关联的。成蝇经口感染
将使用果蝇C病毒(DCV)和果蝇X病毒(DXV)来测试共感染对病毒的影响。
生长动力学、宿主基因表达、病毒传播率和宿主人口统计学,包括繁殖力,
发育率和死亡率。目标1将通过量化病毒生长来关注分子相互作用
动态和表征宿主转录组对成人中单一和双重病毒感染的响应
苍蝇在目标2中,将研究合并感染对病毒直接传播和环境传播的影响。
测定繁殖力、后代发育率和死亡率是影响种群数量的主要因素
因此,这将是目标3的重点。了解合并感染如何改变苍蝇人口结构将导致
在受感染人群中共同传播病毒的长期影响建模。统计和数学
在这三个目标内部和之间建立模型,将用来描述分布式控制飞行器和分布式控制飞行器之间的相互作用
在他们共享的主机。这项研究将通过生成丰富的数据集来测试病毒协同模型,从而推动该领域的发展。
感染,并建立了一个易于处理的模型系统,用于研究病毒在多个
组织层面。
项目成果
期刊论文数量(0)
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科研奖励数量(0)
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专利数量(0)
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