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，统称为微生物群落。这些微生物为宿主发挥着许多重要的功能，包括防御寄生虫和病原体的感染。为了完成这些功能，微生物必须与宿主细胞和寄生虫细胞密切互动。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来实现的，这些信使微生物群中的细菌、宿主和寄生虫之间可以进行交流。这项研究项目通过设计一个模型蜜蜂肠道系统来促进对微生物组的理解。这样的系统具有明显更少的细菌分类群，并发挥与其他肠道微生物相同的功能，包括在宿主防御寄生虫方面发挥作用。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被用来进一步了解微生物组及其在宿主防御中的作用。从该项目获得的知识将对操纵微生物群以促进宿主健康至关重要，最终也包括对人类健康的影响。正在为小学生开发一个以计算机科学和生物学为基础的推广模块。指导学生和教师构建树莓PI集群，然后根据研究数据集将其用于学生主导的项目。越来越多的证据表明，微生物群通过物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-寄生虫相互作用中的种间细胞信号的理解。模式系统是蜜蜂肠道微生物群，由不到10个细菌分类群组成。三个目标共同解决了微生物群在宿主防御寄生虫中的作用，评估了微生物群中与寄生虫抗性有关的功能冗余，并在实验上测试了网络预测。带有共同肠道寄生虫的蜜蜂提供数据，为感染寄生虫的蜜蜂和抵抗感染的蜜蜂生成相互作用网络。在这些网络中，特定的基因模块和细菌分类群在肠道微生物群中被识别出来，这对寄生虫的抗性很重要。通过这种方式，宿主、寄生虫和细菌之间的关键相互作用被阐明。下一步，开发了一种替代的、免费的方法来为这个系统建立微生物组网络。在这种方法中，优势蜜蜂肠道细菌的全基因组序列是从寄生虫感染流行率不同的蜂房收集的。在这些优势细菌分类群中菌株水平变异的重要性在一大组计算衍生的网络中被探索。评估了网络拓扑的变化，包括根据经验得出的电阻模块的变化。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了预测。这些预测是通过创造具有合成肠道微生物的蜜蜂来检验的，这些微生物被预测为抗寄生虫或敏感的。该项目将极大地促进对微生物群影响宿主健康的机制的了解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.