Collarborative Research: A systems approach to understanding signaling networks in host-microbiome-parasite interactions

所有动物都含有复杂的细菌和其他微生物群落，统称为微生物组。这些微生物为宿主执行许多重要功能，包括防御寄生虫和病原体的感染。为了实现这些功能，微生物必须与宿主和寄生虫细胞密切相互作用。 越来越多的科学证据表明，这些相互作用是通过产生化学信使发生的，这些化学信使允许微生物组中的细菌、宿主和寄生虫之间进行交流。 该研究项目通过设计蜜蜂肠道系统模型来促进对微生物组的理解。这样的系统具有显著更少的细菌分类群，并与其他肠道微生物组执行相同的功能，包括在宿主防御寄生虫中发挥作用。在这个蜜蜂系统中，肠道微生物组的网络模型和实验操作都用于进一步了解微生物组及其在宿主防御中的作用。从该项目中获得的知识对于操纵微生物组以促进宿主健康（最终包括人类健康）非常重要。 目前正在为小学生开发一个以计算机科学和生物学为基础的外联模块。学生和教师将被引导构建Raspberry Pi集群，然后将其用于基于研究数据集的学生驱动的项目。越来越多的证据表明，微生物组通过种间细胞信号在宿主健康和抵御寄生虫方面发挥着关键作用。这项研究使用系统生物学框架来促进对宿主-微生物组-寄生虫相互作用中种间细胞信号传导的理解。模型系统是蜜蜂肠道微生物组，其由少于十个细菌分类群组成。三个目标共同解决微生物组在宿主防御寄生虫中的作用，评估微生物组与寄生虫抗性相关的功能冗余，并通过实验测试网络预测。具有常见肠道寄生虫的蜜蜂提供数据，以生成寄生虫感染的蜜蜂和抵抗感染的蜜蜂的相互作用网络。在这些网络中，特定的基因模块和细菌分类群，对寄生虫抗性很重要，在肠道微生物组中被确定。通过这种方式，阐明了宿主、寄生虫和细菌之间的关键相互作用。接下来，开发了一种替代的、互补的方法来为该系统构建微生物组网络。对于这种方法，从寄生虫感染流行率不同的养蜂场收集占优势的蜜蜂肠道细菌的全基因组序列。在这些优势细菌类群的菌株水平的变化的重要性进行了探讨，在一个大型的计算衍生的网络。网络拓扑结构的变化，包括变化的衍生电阻模块，进行评估。最后，基于经验和计算网络，对最有可能导致寄生虫抗性的微生物群落结构进行预测。这些预测是通过创造具有合成肠道微生物组的蜜蜂来测试的，这些肠道微生物组被预测为抗寄生虫或易感。该项目将显著推进微生物组影响宿主健康的机制的知识。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

All animals contain complex communities of bacteria and other microbes, known collectively as the microbiome. These microbes perform many important functions for their host, including defense against infection by parasites and pathogens. To accomplish these functions the microbes must interact closely with both host and parasite cells. Increasingly, scientific evidence suggests that these interactions occur through the production of chemical messengers that allow communication among the bacteria in the microbiome, the host and the parasite. This research project advances understanding of the microbiome by devising a model honey bee gut system. Such a system has significantly fewer bacterial taxa and performs the same functions as other gut microbiomes, including playing a role in host defense against parasites. In this honey bee system, both network models and experimental manipulations of the gut microbiome are used to further understanding of the microbiome and its role in host defense. The knowledge derived from the project would be important for manipulating the microbiome for host health, including, ultimately, that of humans. A computer science and biology-based outreach module for elementary school students is being developed. Students and teachers are guided through the building of Raspberry Pi clusters, which are then used for student-driven projects based on the research datasets. Growing evidence points to the critical role that the microbiome plays in host health and defense against parasites via interspecies cellular signaling. This research uses a systems biology framework to advance understanding of interspecific cellular signaling in host-microbiome-parasite interactions. The model system is the honey bee gut microbiome which consists of less than ten bacterial taxa. Three objectives collectively address the role of the microbiome in host defense against parasites, assess functional redundancy in the microbiome in relation to parasite resistance, and experimentally test network predictions. Bees with a common gut parasite provide data to generate interaction networks for bees that are parasite-infected and for bees that are resistant to infection. Within these networks, specific gene modules and bacterial taxa, important for parasite resistance, are identified within the gut microbiome. In this way key interactions among the host, parasite and bacteria are elucidated. Next, an alternative, complimentary approach to building microbiome networks for this system is developed. For this approach whole genome sequences of dominant bee gut bacteria are collected from apiaries that vary in parasite infection prevalence. The importance of strain-level variation in these dominant bacterial taxa are explored in a large set of computationally-derived networks. Shifts in network topology, including changes in the empirically-derived resistance modules, are assessed. Finally, based on the empirical and computational networks, predictions are made about microbiome community structures that are most likely to result in parasite resistance. These predictions are tested by creating bees with synthetic gut microbiomes that are predicted to be parasite-resistant or susceptible. This project will significantly advance knowledge of the mechanisms by which the microbiome impacts host health.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.