Understanding mosquito movement and its relevance to control through genetic analysis
Understanding mosquito movement and its relevance to control through genetic analysis
批准号:
10267751
负责人:
John Macky Marshall
金额:
$56.19万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-21 至 2024-08-31
关键词:
AddressAedesAntimalarialsBreedingCaliforniaChikungunya virusChromosomal translocationChromosome MappingCollectionCulicidaeDataDengueDengue VirusDevelopmentEcologyEffectivenessEngineeringEntomologyEnvironmental WindFishesGenesGeneticHabitatsHomingHousingIndividualInsecticidesInterventionKnowledgeLarvaLeadLocationMale SterilityMethodsModelingMosquito ControlMosquito-borne infectious diseaseMovementParentsPartner in relationshipPatternPopulationPopulation DynamicsPopulation ReplacementsPopulation SizesProtocols documentationResearchSafetySample SizeSamplingSchemeSiblingsSingaporeSiteSpeedStructureSystemTransfectionTunaVariantWolbachiaZIKAZika Virusanalytical methodbasechikungunyacoralcostdensitydisorder controlgene drive systemgenetic analysisgenome sequencinggenomic dataglobal healthin silicoinnovationinterestland covermalemating behaviormortalitynovelnovel strategiesoffspringsimulationsurveillance strategythree dimensional structurethree-dimensional modelingtooltrial designvector controlvector mosquito
中文摘要
项目摘要/摘要:
登革热、基孔肯雅热、寨卡病毒和其他蚊媒疾病继续构成重大的全球卫生负担
在世界大部分地区,尽管广泛分发以杀虫剂为基础的工具和抗疟疾药物
毒品。因此,人们对控制这些疾病的新战略感兴趣,包括释放
基因不育的雄性蚊子,转沃尔巴克氏菌的蚊子,以及基因改造的蚊子
基因驱动系统。关于试验设计的这些策略和考虑因素的安全性和有效性
和实施在很大程度上取决于对蚊子运动的详细了解
和广阔的空间尺度,然而,我们对这些运动模式的理解存在重大差距。这个
基因组测序成本的下降和分析地理编码基因组数据的新方法提供了
消除这些知识差距的机会。在这个项目中,我们建议设计一种强大的方法来
推论细尺度蚊子传播模式及其对创新媒介控制策略的影响。我们
建议使用电子计算机模拟蚊子生态和初步地理编码的蚊子基因组数据
从加利福尼亚州弗雷斯诺收集,以确定能够量化扩散模式的采样例程,
使用遗传亲缘关系分析的种群数量和交配模式(目标1)。这些分析的结果将
迭代地通知两轮后续埃及伊蚊采集的采样方案
登革热、基孔肯雅和寨卡病毒的传播媒介,新加坡宜顺(目标2)。基因组测序和
亲属关系分析将被用来量化Ae。埃及伊蚊的迁徙模式、种群数量和交配
该位置的行为,并对Ae的空间结构的3D模型进行参数化。埃及伊蚊种群
动力学。由此产生的模型将用于探索生物安全、试验设计和实施
对新的病媒控制战略的考虑包括:i)人口抑制系统,例如
沃尔巴克氏菌感染的男性和遗传不育的男性,以及二)种群替换系统,如
沃尔巴克氏菌、染色体易位等局部化系统和非易位基因
本地化系统,如基于归巢的基因驱动(目标3)。我们预计拟议的研究将导致
制定大大加强的监测战略,以推断细微规模的蚊子活动模式和
其他人口统计参数,并帮助告知安全应用几个新颖和非常有希望的
控制登革热、基孔肯雅和寨卡病毒以及其他由蚊子传播的破坏性病毒的战略
疾病。
英文摘要
PROJECT SUMMARY/ABSTRACT:
Dengue, Chikungunya, Zika and other mosquito-borne diseases continue to pose a major global health burden
through much of the world, despite the widespread distribution of insecticide-based tools and antimalarial
drugs. Consequently, there is interest in novel strategies to control these diseases, including the release of
genetically sterile male mosquitoes, mosquitoes transfected with Wolbachia, and mosquitoes engineered with
gene drive systems. The safety and effectiveness of these strategies and considerations regarding trial design
and implementation are critically dependent upon a detailed understanding of mosquito movement at both fine
and broad spatial scales, yet there are major gaps in our understanding of these movement patterns. The
declining cost of genome sequencing and novel methods for analyzing geocoded genomic data provide
opportunities to address these knowledge gaps. In this project, we propose to devise a robust approach for
inferring fine-scale mosquito dispersal patterns and their impact on innovative vector control strategies. We
propose to use in silico simulations of mosquito ecology and preliminary geocoded mosquito genomic data
collected from Fresno, California to determine sampling routines capable of quantifying dispersal patterns,
population sizes and mating patterns using genetic kinship analyses (Aim 1). Results from these analyses will
iteratively inform sampling schemes for two rounds of subsequent collections of Aedes aegypti, the mosquito
vector of dengue, Chikungunya and Zika viruses, in Yishun, Singapore (Aim 2). Genome sequencing and
kinship analyses will be used to quantify Ae. aegypti movement patterns, population sizes and mating
behaviors at this location, and to parameterize spatially-structured 3D models of Ae. aegypti population
dynamics. The resulting models will be used to explore biosafety, trial design and implementation
considerations for novel vector control strategies including: i) population suppression systems such as
Wolbachia-infected males and genetically sterile males, and ii) population replacement systems such as
population transfection with Wolbachia, localized systems such as chromosomal translocations, and non-
localized systems such as homing-based gene drive (Aim 3). We expect the proposed research to lead to the
development of greatly enhanced surveillance strategies to infer fine-scale mosquito movement patterns and
other demographic parameters, and to help inform the safe application of several novel and highly promising
strategies for the control of dengue, Chikungunya and Zika viruses and other devastating mosquito-borne
diseases.
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会议论文
Understanding mosquito movement and its relevance to control through genetic analysis
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批准号:10468809
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项目类别:
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资助金额:$52.06万
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财政年份:2020
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负责人:John Macky Marshall
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依托单位:
海外基金