Ants as a model system to study processes that influence the transmission dynamics of infectious diseases

蚂蚁作为模型系统来研究影响传染病传播动态的过程

• 批准号: 1414296
• 负责人: David Hughes
• 金额: $ 183.13万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-15 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1414296&HistoricalAwards=false
• 关键词: Ants; model; system; study; processes

Living in societies affects disease transmission, and understanding how infectious diseases transmit in social settings is a crucial area of research for humans directly, for the animals and plants we use as food, and for the environments we seek to protect. Many settings for disease spread are currently being studied, from schools and workplaces to farms and wild areas. But few systems offer the opportunity to experimentally examine the diverse factors driving disease transmission. Social ant colonies provide a novel experimental approach to manipulate infection and measure disease transmission. In this project, the investigators will seek to understand the role of group size, group complexity, and individual contact networks in driving infectious disease transmission. Historically, linking individual contact patterns with the emergent properties of disease transmission has been limited by logistical constraints. In this research, scientists will use video cameras and ant colonies as a model system to track social interaction networks and follow movement of beneficial, null and pathogenic agents. The project will leverage a general excitement for ants, including public interest in some of their parasites, such as zombie ant fungi, to provide products for diverse stakeholders. These will include comprehensive lesson plans, work modules and experiments on mathematical biology of disease. Videos, computer code, games and statistical packages will also be developed, enabling K-12 teachers and students, university classes, and the broader public, to collect and analyze data on social interactions and pathogen transmission. The Epidemics MOOC (Massive, Open, Online Course) at Pennsylvania State University will disseminate the project to a broad audience. Because the research focuses on understanding the mathematical rules of disease transmission, the results will have direct relevance for humans and provide novel insights into how to manipulate the process of transmission to reduce disease. Ants have a highly evolved social system. Their colonies have agriculture, waste management, air conditioning, aggressive interactions and food limitation. They also are able to effectively control many diseases. Because ant societies are known to optimize the transmission of resources like sugar and protein while reducing pathogen spread, they will serve as a model system for understanding disease transmission. Using epidemiological, spatial and network models, the research will investigate how a range of agents from positive (food) to negative (pathogens) to null (inert beads) are shuttled around the nest. The study of transmission elements that range from beneficial to virulent will allow the establishment of baseline patterns for scaling transmission as a function of colony size and extrinsic conditions (i.e. physical structure) and will shed new light on the role of infectious processes in structuring societies. Although the study of contact networks is often limited to examining a subset of a population (ignoring contacts with unmeasured individuals), some proxy for the relevant contacts that is easier to measure or to the realized transmission network of some pathogen rather than the full network of potential paths, is needed. The use of video recording within ant nests will allow high-resolution quantification of contacts; thus enabling a comprehensive study of pathogen transmission as an emergent property of societies. The project will include continuous data recorded on thousands of individuals to study the scaling of transmission as a generic process (i.e. independent of pathogens) and link that transmission to the spread of both beneficial and deleterious elements. Using novel dynamic network models and spatial movement models, the important components of social living that promote disease transmission, and those that reduce its spread will be identified. The role of these components will be verified with targeted knockout experiments that will provide specific insights into controlling destructive ant colonies and general insights into the mechanisms behind social immunity and disease control in humans and other social species.

生活在社会中会影响疾病的传播，了解传染病如何在社会环境中传播，对于人类、我们用作食物的动物和植物以及我们寻求保护的环境来说，都是一个至关重要的研究领域。目前正在研究疾病传播的许多环境，从学校和工作场所到农场和野生地区。但是很少有系统能提供实验检验驱动疾病传播的各种因素的机会。社会蚁群为控制感染和测量疾病传播提供了一种新的实验方法。在这个项目中，研究人员将试图了解群体规模、群体复杂性和个体接触网络在推动传染病传播中的作用。从历史上看，将个人接触模式与疾病传播的突发特性联系起来受到后勤限制的限制。在这项研究中，科学家将使用摄像机和蚁群作为模型系统来跟踪社会互动网络，并跟踪有益，无效和致病因子的运动。该项目将利用人们对蚂蚁的普遍兴趣，包括公众对蚂蚁寄生虫（如僵尸蚂蚁真菌）的兴趣，为不同的利益相关者提供产品。这些将包括全面的课程计划、工作模块和疾病数学生物学实验。还将开发视频、计算机代码、游戏和统计软件包，使K-12教师和学生、大学班级和广大公众能够收集和分析有关社会互动和病原体传播的数据。宾夕法尼亚州立大学的流行病MOOC（大规模、开放、在线课程）将把这个项目传播给广泛的受众。由于研究的重点是了解疾病传播的数学规则，因此研究结果将与人类直接相关，并为如何操纵传播过程以减少疾病提供新的见解。蚂蚁有高度进化的社会系统。它们的栖息地有农业、废物管理、空调、攻击性互动和食物限制。他们也能够有效地控制许多疾病。因为已知蚂蚁社会在减少病原体传播的同时优化糖和蛋白质等资源的传播，它们将作为理解疾病传播的模型系统。利用流行病学、空间和网络模型，该研究将调查从阳性（食物）到阴性（病原体）再到无效（惰性珠子）的一系列病原体是如何在巢穴周围穿梭的。对从有益到有害的传播要素的研究，将允许建立按群体规模和外部条件（即物理结构）的函数缩放传播的基线模式，并将揭示感染过程在构建社会中的作用。虽然对接触网络的研究通常仅限于检查人群的一个子集（忽略与未测量个体的接触），但需要一些更容易测量的相关接触的代理或某些病原体的已实现传播网络，而不是潜在路径的完整网络。在蚁巢内使用视频记录可以对接触进行高分辨率量化；因此，能够全面研究病原体传播作为一个新兴的社会属性。该项目将包括记录数千人的连续数据，以研究作为一般过程的传播规模（即独立于病原体），并将该传播与有益和有害元素的传播联系起来。利用新的动态网络模型和空间运动模型，将确定社会生活中促进疾病传播和减少疾病传播的重要组成部分。这些成分的作用将通过靶向敲除实验得到验证，这将为控制破坏性蚁群提供具体的见解，并为人类和其他社会物种的社会免疫和疾病控制背后的机制提供一般见解。