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

项目摘要 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 营养素，毒素和邻近细胞引发协调的分子反应，影响细胞功能， 以有益的、适应性的或有害的方式进行代谢。虽然多细胞生物的好处 复杂组织结构的形成或整个器官系统的功能长期以来一直受到重视， 直到最近才了解到，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，对这些相互作用的理解并没有超越简单的 关联，并且几乎没有可用的分子技术可以充分定义复杂的 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宿主细胞功能。 细菌群落当人们考虑到这一广泛而重大的影响时， 微生物对人类健康的影响。在本申请中，我们建议通过以下方式明确填补这一知识空白： 开发一种新型的多模态成像管道，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。 该提案结合了我们在免疫学，感染生物学，质谱，小动物 成像，机器学习和计算机视觉，以开发集成的多模态可视化方法， 研究传染病。我们独特的方法将计算联合收割机超高速（~ 50 px/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、高空间分辨率光学显微镜和使用数据驱动图像融合的MR成像。这 该战略将使成千上万的元素，代谢物，脂质， 蛋白质具有前所未有的化学特异性和空间保真度的组合，比蛋白质快50倍以上。 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 亚群在整个三维体积的S.金黄色葡萄球菌社区，（ii）揭示形成的宿主分子 脓肿和积聚限制小鼠模型中微生物生长，和（iii）阐明分子标记 在宿主-病原体界面区分体内生物膜， 进展，并在不同程度的营养胁迫下。这些研究将揭示新的治疗靶点 干预和技术开发的结果，这一建议将广泛适用于所有 生理相关过程，深刻影响生物医学研究。

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.