Decoding interspecies signaling networks and the biogeography of polymicrobial infections

项目总结 多种微生物群落在人体中普遍存在，它们的行为是两者的关键驱动因素 健康和疾病。细菌是社会有机体；因此，群体的行为不仅由 群落的组成，也取决于组成要素与其周围环境之间的相互作用 环境。所有社区都认同的一个关键原则是，空间很重要。团体组织起来以最大化 采购商品，最大限度地减少接触有毒化合物，并优化沟通。我们最近的数据 揭示细菌可以与遥远物种的成员交流，并通过改变它们的空间方式来做出反应 构建他们的社区。我的实验室试图了解细菌是如何通过 在他们的原生环境中观察他们，跟踪他们的行动，并倾听和解码他们的 语言。 我们利用铜绿假单胞菌，这是最臭名昭著的条件致病菌，有多种类型 多菌感染，包括囊性纤维化患者的慢性伤口和肺部感染。我们 最近报道，铜绿假单胞菌可引起患者肺部其他重要病原体的感染。 几十年来，对激烈的抗生素治疗仍然没有反应，并导致肺功能衰退和早期 死亡。 在这项建议中，我们首先在现场可视化多微生物群落的空间景观。 CF患者的移植肺和多菌感染的动物模型。通过结合下一代 组织清除和荧光原位杂交，我们能够可视化物种在 相对于彼此和主体结构的一系列空间尺度。这将产生一种前所未有的观点 感染过程中的微生物，并为可视化富含多种微生物的其他器官中的群落提供了一个平台 社区，如胃肠道。 接下来，我们将系统地解码物种间的信号语言。我们设计了高通量的屏幕 以确定信号传递所必需的基因和信号分子的谱系。使用实时成像技术 由我的实验室率先开发的，我们可视化并跟踪细菌细胞的运动，基因表达和动力学 运动附属物，在所识别的路径调制时。初步研究显示铜绿假单胞菌对 通过激活多个信号系统，这些信号系统调整移动方向并激活毒力系统。 总而言之，这些研究将构建物种间交流的全面图景，并对 相互作用如何加剧疾病。

PROJECT SUMMARY Polymicrobial communities are ubiquitous in the human body and their behaviors are critical drivers of both health and disease. Bacteria are social organisms; thus, the behavior of the group is driven not only by the composition of the community, but also by interactions between the constituents and their surrounding environment. A key principle shared among all communities, is that space matters. Groups organize to maximize acquisition of goods, minimize exposure to toxic compounds, and optimize communication. Our recent data reveal bacteria can communicate with members of distant species and respond by changing how they spatially structure their communities. My laboratory seeks to understand how bacteria communicate between species by observing them in their native environment, tracking their movements, and listening to and decoding their languages. We utilize Pseudomonas aeruginosa, the most notoriously problematic opportunistic pathogen in multiple types of polymicrobial infections, including chronic wounds and lung infections in cystic fibrosis (CF) patients. We recently reported that P. aeruginosa establishes infections with other important pathogens in the lungs of patients with CF for decades, remaining unresponsive to intense antibiotic therapies and causing lung decline and early death. In this proposal, we begin by visualizing the spatial landscape of polymicrobial communities in situ, in transplanted lungs from CF patients and animal models of polymicrobial infection. By combining next-generation tissue clearing and fluorescent in situ hybridization, we are able to visualize the spatial positioning of species on a range of spatial scales, in relation to each other and host structures. This will yield an unprecedented view of microbes during infection and provide a platform for visualizing communities in other organs rich in polymicrobial communities, such as the gastrointestinal tract. Next, we will systematically decode the interspecies signaling language. We designed high-throughput screens to identify genes necessary for signaling and the repertoire of signaling molecules. Using live-imaging techniques pioneered by my lab, we visualize and track the movement of bacterial cells, gene expression, and dynamics of motility appendages, upon modulation of the identified pathways. Initial studies reveal P. aeruginosa responds by activating multiple signaling systems, which tune the direction of movement and activate virulence systems. Collectively, these studies will construct a comprehensive picture of interspecies communication and enlighten how interactions exacerbate disease.