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Decoding interspecies signaling networks and the biogeography of polymicrobial infections

解码种间信号网络和多种微生物感染的生物地理学

基本信息

批准号：
10809397
负责人：
Dominique Limoli
金额：
$ 21.58万
依托单位：
UNIVERSITY OF IOWA
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-18 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10809397
关键词：
3-Dimensional Address Anabolism Animal Model Antibiotic Therapy Antibiotics Attention Bacteria Bacterial Model Bacterial Physiology Behavior Biological Assay Cells Cessation of life Chemotaxis Chronic Communication Communities Data Disease Distant Ecology Environment Exposure to Flagella Fluorescent in Situ Hybridization Future Gastrointestinal tract structure Gene Expression Genes Genetic Genetic Screening Goals Hair Health Human Human body Image Imaging Techniques Immune Immune system In Situ In Vitro Individual Infection Investigation Laboratories Language Life Lung Lung Transplantation Lung infections Maps Measures Mediating Microbe Microbial Biofilms Molecular Biology Movement Nature Neighborhoods Nutrient Organ Organism Pathway interactions Patients Pattern Physiology Pilum Poison Population Positioning Attribute Proteins Pseudomonas aeruginosa Race Reporting Respiratory Tract Infections Role Sampling Sensory Signal Pathway Signal Transduction Signaling Molecule Site Staphylococcus aureus Structure Surface System Techniques Technology Therapeutic Three-Dimensional Imaging Tissues Viral Virulence Visualization Walking Wound Infection antibiotic tolerance antimicrobial appendage arm bacterial community cell motility chronic wound cystic fibrosis infection cystic fibrosis patients design extracellular genetic approach high throughput screening human disease human tissue implantable device in vivo in vivo Model insight interspecies communication live cell imaging member microbial microbial community next generation opportunistic pathogen pathogen polymicrobial biofilm respiratory social therapy design wound

项目摘要

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.

项目摘要多微生物群落在人体中无处不在，它们的行为是两者的关键驱动因素健康和疾病。细菌是社会性有机体;因此，群体的行为不仅受环境的影响，社区的组成，而且还取决于成分与周围环境之间的互动环境所有社区共有的一个关键原则是空间问题。团体组织起来，采购货物，尽量减少接触有毒化合物，并优化沟通。我们最近的数据揭示了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在物种之间交流的，观察他们在他们的原生环境，跟踪他们的运动，倾听和解码他们的声音。语言我们利用铜绿假单胞菌，最臭名昭著的问题机会致病菌在多种类型多微生物感染，包括囊性纤维化（CF）患者的慢性伤口和肺部感染。我们最近报道，铜绿假单胞菌在患者的肺部建立与其他重要病原体的感染数十年来，CF对强烈的抗生素治疗没有反应，导致肺功能下降，死亡在这个建议中，我们开始通过可视化的空间景观的多微生物群落在原位，来自CF患者的移植肺和多种微生物感染的动物模型。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的空间定位，一系列的空间尺度，相对于彼此和主机结构。这将产生一个前所未有的观点，感染期间的微生物，并提供了一个平台，可视化社区在其他器官丰富的多微生物例如胃肠道。接下来，我们将系统地解码物种间的信号语言。我们设计了高通量筛选以确定信号传导所必需的基因和信号分子的库。使用实时成像技术由我的实验室开创，我们可视化和跟踪细菌细胞的运动，基因表达，以及细菌的动力学。运动附属物，在调制的识别途径。初步研究显示铜绿假单胞菌通过激活多个信号系统，调节运动方向并激活毒力系统。总的来说，这些研究将构建一个物种间交流的全面图景，相互作用如何加剧疾病。