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

项目总结 细胞与环境的相互作用构成了所有生物体健康和疾病的基础。暴露量 对营养物质、毒素和邻近细胞触发协调的分子反应，影响细胞功能和 以有益的、适应的或有害的方式代谢。尽管多细胞技术对 人们早就意识到复杂组织结构的形成或整个器官系统的功能，它 直到最近才了解到脊椎动物的微生物栖息地对宿主也有巨大的影响 细胞功能和功能障碍。尽管如此，对这些相互作用的理解并没有超越简单 几乎没有分子技术可以充分定义一种复合体是如何 微生物生态系统影响宿主细胞功能，或宿主对微生物定植的反应如何影响 细菌群落。当人们考虑到这种知识的广泛和重大影响时，这种差距是惊人的 微生物对人类健康有影响。在本申请中，我们建议通过以下方式明确地填补这一知识空白 开发一种新的多模式成像管道，提供分子的三维信息 微生物群落的异质性和宿主-病原体界面的免疫反应。 这项建议结合了我们在免疫学、感染生物学、质谱学、小动物等方面的专业知识 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(~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 由LA-ICP-IMS、高空间分辨率光学显微镜和磁共振成像采用数据驱动的图像融合。这 这一战略将使人们能够为数千种元素、代谢物、脂质和 具有前所未有的化学专一性和空间保真度组合的蛋白质比 目前是可能的。我们将使用这种下一代成像能力来(I)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)揭示形成 在小鼠模型中脓肿和积聚限制微生物生长，以及(Iii)阐明分子标记 区分宿主-病原体界面上的活体生物膜，区分不同阶段的脓肿 进展，并在不同程度的营养胁迫下。这些研究将发现治疗的新靶点 作为这一提议的结果而开发的干预和技术将广泛适用于所有 生理上相关的过程，深刻地影响着生物医学研究。

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.