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.

Public Health Relevance

This proposal will enable detailed views of the molecular components of infectious disease with unprecedented resolution through the development of a multimodal, 3-dimensional imaging platform. The proposed technologies will improve throughput and molecular specificity, enable automated high-precision and high-accuracy image alignment, and allow for descriptions of molecular signals in 3-D through the fusion of multi-modal imaging data. These studies will uncover targets for therapeutic intervention and antibiotic development and the techniques developed as a result of this proposal will be broadly applicable to all physiologically relevant processes, profoundly impacting biomedical research.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
1R01AI138581-01A1
Application #
9659850
Study Section
Bacterial Pathogenesis Study Section (BACP)
Program Officer
Huntley, Clayton C
Project Start
2018-09-19
Project End
2023-08-31
Budget Start
2018-09-19
Budget End
2019-08-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Vanderbilt University Medical Center
Department
Type
DUNS #
079917897
City
Nashville
State
TN
Country
United States
Zip Code
37232