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Understanding mosquito movement and its relevance to control through genetic analysis

通过基因分析了解蚊子的运动及其与控制的相关性

基本信息

批准号：
10468809
负责人：
John Macky Marshall
金额：
$ 52.06万
依托单位：
UNIVERSITY OF CALIFORNIA BERKELEY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-21 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10468809
关键词：
Address Aedes Antimalarials Breeding California Chikungunya virus Chromosomal translocation Chromosome Mapping Collection Culicidae Data Dengue Dengue Virus Development Ecology Effectiveness Engineering Entomology Environmental Wind Fishes Genes Genetic Habitats Homing Housing Individual Insecticides Intervention Knowledge Larva Lead Location Male Sterility Methods Modeling Mosquito Control Mosquito-borne infectious disease Movement Parents Partner in relationship Pattern Population Population Dynamics Population Replacements Population Sizes Protocols documentation Research Safety Sample Size Sampling Scheme Siblings Singapore Site Speed Structure System Transfection Tuna Variant Wolbachia ZIKA Zika Virus analytical method base chikungunya coral cost density disorder control gene drive system genetic analysis genome sequencing genomic data global health in silico innovation interest land cover male mating behavior mortality novel novel strategies offspring simulation surveillance strategy three dimensional structure three-dimensional modeling tool trial design vector control vector mosquito

项目摘要

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.

项目总结/摘要：登革热、基孔肯雅热、寨卡和其他蚊媒疾病继续构成全球重大健康负担在世界大部分地区，尽管广泛分发了基于疟疾的工具和抗疟疾药物，毒品因此，人们对控制这些疾病的新策略感兴趣，包括释放基因不育的雄性蚊子、转染有沃尔巴克氏体的蚊子和经基因工程改造的蚊子。基因驱动系统这些策略的安全性和有效性以及试验设计方面的考虑和实施都严重依赖于对蚊子运动的详细了解，和广阔的空间尺度，但我们对这些运动模式的理解存在重大差距。的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有机会弥补这些知识差距。在这个项目中，我们建议设计一个强大的方法，推断蚊子的细微扩散模式及其对创新性病媒控制战略的影响。我们建议使用蚊子生态学的计算机模拟和初步的地理编码蚊子基因组数据从加州弗雷斯诺收集，以确定能够量化扩散模式的采样程序，使用遗传亲缘关系分析的种群规模和交配模式（目标1）。这些分析的结果将迭代地为随后的两轮埃及伊蚊采集提供信息的采样方案，登革热、基孔肯雅和寨卡病毒的媒介，在新加坡义顺（Aim 2）。基因组测序和亲属关系分析将用于量化Ae。埃及人的移动模式、种群规模和交配行为在这个位置，并参数化的空间结构的3D模型的Ae。埃及人口动力学由此产生的模型将用于探索生物安全性，试验设计和实施新的病媒控制策略的考虑因素包括：i）种群抑制系统，沃尔巴克氏体感染的男性和遗传不育的男性，和ii）人口替代系统，如群体转染与沃尔巴克氏体，局部系统，如染色体易位，和非定位系统，如基于归巢的基因驱动（Aim 3）。我们希望拟议的研究将导致制定大大加强的监测战略，以推断蚊子的细微移动模式，其他人口统计参数，并帮助告知安全应用的几个新的和非常有前途的控制登革热、基孔肯雅和寨卡病毒以及其他破坏性蚊媒病毒的战略疾病