Molecular mapping of microbial communities at the host-pathogen interface by multi-modal 3-dimensional imaging mass spectrometry

通过多模态 3 维成像质谱法绘制宿主-病原体界面微生物群落的分子图谱

• 批准号: 10465090
• 负责人: Eric P Skaar
• 金额: $ 59.51万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-19 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10465090
• 关键词: 3-Dimensional; Abscess; Affect; Animal Model; Animals; Anterior nares; Antibiotics; Antibodies; Architecture; Awareness; Bacteria; Bacterial Infections; Bacterial Proteins; Behavior; Biology; Biomedical Research; Cell Differentiation process; Cell physiology; Cells; Cellular Metabolic Process; Chemicals; Communicable Diseases; Communities; Complement; Complex; Computer Analysis; Computer Vision Systems; Custom; Data; Development; Diagnosis; Differentiation Antigens; Dimensions; Disease; Ecosystem; Elements; Environment; Exposure to; Fourier transform ion cyclotron resonance; Functional disorder; Genus staphylococcus; Glean; Growth; Health; Health Promotion; Heterogeneity; Histology; Human; Image; Imaging technology; Immune; Immune response; Immunology; Imprisonment; Individual; Infection; Infectious Diseases Research; Integration Host Factors; Knowledge; Label; Lesion; Lipids; Machine Learning; Magnetic Resonance Imaging; Maps; Mass Spectrum Analysis; Metals; Methodology; Methods; Microbe; Microbial Biofilms; Modality; Modeling; Molecular; Multimodal Imaging; Nutrient; Optics; Organism; Pathogenesis; Physiological; Population; Process; Proteins; Reagent; Research; Resolution; Sampling; Signal Transduction; Site; Source; Spatial Distribution; Specificity; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Speed; Staphylococcus aureus; Stress; Structure; Techniques; Technology; Therapeutic Intervention; Three-Dimensional Imaging; Three-dimensional analysis; Tissues; Toxin; Vertebrates; Visualization; Work; animal imaging; bacterial community; base; body system; commensal bacteria; experimental study; host colonization; imaging capabilities; imaging detection; imaging modality; imaging platform; improved; in vivo; innovation; interest; machine learning pipeline; mass spectrometric imaging; microbial; microbial colonization; microbial community; microbial composition; microscopic imaging; molecular imaging; molecular marker; mouse model; multimodality; neutrophil; new therapeutic target; next generation; novel; pathogen; protein expression; response; supervised learning; targeted treatment; virtual

PROJECT SUMMARY Cellular interactions with the environment form the basis of health and disease for all organisms. Exposure to nutrients, toxins, and neighboring cells trigger coordinated molecular responses that impact cell function and metabolism in a beneficial, adaptive, or detrimental manner. Although the benefits of multicellularity for the formation of complex tissue structures or the function of entire organ systems has been long appreciated, it has only recently been understood that microbial inhabitants of vertebrates also have a tremendous impact on host cell function and dysfunction. Despite this, an understanding of these interactions has not moved beyond simple associations, and there are virtually no molecular technologies available that adequately define how a complex microbial ecosystem impacts host cell function, or how the host response to microbial colonization affects the bacterial community. This gap in knowledge is striking when one considers the broad and significant impact that microbes have on human health. In this application, we propose to expressly fill this knowledge gap through development of a novel multimodal imaging pipeline that will provide 3-dimensional information on the molecular heterogeneity of microbial communities and the immune response at the host-pathogen interface. This proposal combines our expertise in immunology, infection biology, mass spectrometry, small animal imaging, machine learning, and computer vision to develop an integrated multimodal visualization method for studying infectious disease. Our unique approach will computationally combine ultra-high speed (~50px/s) MALDI-TOF images, ultra-high mass resolution (>200,000 resolving power) MALDI FTICR IMS, metal imaging by LA-ICP-IMS, high-spatial resolution optical microscopy, and MR imaging using data-driven image fusion. This strategy will enable 3-D molecular images to be generated for thousands of elements, metabolites, lipids, and proteins with an unprecedented combination of chemical specificity and spatial fidelity more than 50x faster than is currently possible. We will use this next-generation imaging capability to (i) define the heterogeneous microbial subpopulations throughout the 3-D volume of a S. aureus community, (ii) uncover the host molecules that form the abscess and accumulate to restrict microbial growth in murine models, and (iii) elucidate molecular markers that differentiate in vivo biofilms at the host-pathogen interface, between abscesses at various stages of progression, and under distinct degrees of nutrient stress. These studies will uncover new targets for therapeutic intervention and the techniques developed as a result of this proposal will be broadly applicable to all physiologically relevant processes, profoundly impacting biomedical research.

项目摘要 与环境的细胞相互作用构成了所有生物的健康和疾病的基础。接触 营养素，毒素和邻近细胞触发了影响细胞功能和的分子反应 以有益，适应性或有害方式的新陈代谢。虽然多细胞的好处 长期以来，它的形成复杂的组织结构或整个器官系统的功能已被人们所欣赏，它具有 直到最近才理解，脊椎动物的微生物居民也对宿主产生巨大影响 细胞功能和功能障碍。尽管如此，对这些互动的理解并没有超越简单 关联，几乎没有任何分子技术可以充分定义复杂的方式 微生物生态系统会影响宿主细胞功能，或者宿主对微生物定植的反应如何影响 细菌社区。当人们考虑到广泛而重大的影响时，这种知识的差距令人震惊 微生物具有人类健康。在此应用程序中，我们建议通过 开发新型的多模式成像管道，该管道将提供有关分子的3维信息 微生物群落的异质性和宿主病原体界面的免疫反应。 该建议结合了我们在免疫学，感染生物学，质谱，小动物方面的专业知识 成像，机器学习和计算机视觉，以开发一种集成的多模式可视化方法 研究传染病。我们独特的方法将在计算上结合超高速度（〜50px/s） MALDI-TOF图像，超高质量分辨率（> 200,000分辨率）MALDI FTICR IMS，金属成像 通过LA-ICP-IMS，使用数据驱动的图像融合，高空间分辨率光学显微镜和MR成像。这 策略将使成千上万个元素，代谢物，脂质和 化学特异性和空间保真度的前所未有组合的蛋白质超过50倍 目前有可能。我们将使用此下一代成像能力来定义异质微生物 在金黄色葡萄球菌群落的3-D体积中的亚群，（ii）发现形成的宿主分子 脓肿并积聚以限制鼠模型中的微生物生长，（iii）阐明了分子标记 在宿主 - 病原体界面处的体内生物膜区分，在各个阶段的脓肿之间 进展，在不同程度的养分胁迫下。这些研究将发现治疗的新目标 干预和由于本提案而开发的技术将广泛适用于所有人 生理相关的过程，对生物医学研究产生深远的影响。