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.

项目总结