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.

项目摘要多数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与疾病。细菌是社会生物；因此，小组的行为不仅是由社区的组成，也是通过成分之间的互动及其周围的互动环境。在所有社区中共有的一个关键原则是空间很重要。小组组织以最大化获取商品，最大程度地减少对有毒化合物的接触并优化通信。我们最近的数据揭示细菌可以与遥远物种的成员进行交流，并通过更改它们的空间方式做出反应构建他们的社区。我的实验室试图了解细菌如何通过观察它们在其本地环境中，跟踪他们的动作，并倾听和解码语言。我们利用铜绿假单胞菌，这是多种类型的最有问题的机会性病原体囊性纤维化（CF）患者的多数菌感染，包括慢性伤口和肺部感染。我们最近报道，铜绿假单胞菌在患者肺中患有其他重要病原体的感染数十年来，CF对强烈的抗生素疗法无反应，并引起肺部下降和早期死亡。在此提案中，我们首先可视化多数菌群社区的空间景观，来自CF患者的肺和多数菌感染的动物模型。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的空间定位一系列空间尺度，相互关系和宿主结构。这将产生前所未有的观点感染过程中的微生物，并提供了一个可视化富含多数型的器官的社区的平台社区，例如胃肠道。接下来，我们将系统地解码种间信号语言。我们设计了高通量屏幕确定信号传导和信号分子库所必需的基因。使用实影技术在我的实验室的开创性时，我们可视化并跟踪细菌细胞的运动，基因表达和动力学在调制已确定的途径后，运动性附加物。初步研究表明，铜绿假单胞菌反应通过激活多个信号系统，这些信号系统调整运动方向并激活毒力系统。总的来说，这些研究将构建种间交流的全面图片并启发相互作用如何加剧疾病。