Currently, cellular alterations associated with pathological conditions are studied using low complexity immunohistochemical (IHC) assays, typically utilizing 2-5 antibodies, that only reveal a tiny subset of the alterations that are occurring, lack comprehensive cellular context, and do not provide quantitative readouts of cellular changes throughout the tissue. For example, a injury or disease can initiate a complex web of pathological alterations across cell types, and at multiple scales ranging from individual cells to multi-cellular units and the layered brain cytoarchitecture. However, technological limitations are hindering a more comprehensive global understanding of these pathological changes. This lack of understanding is hampering our ability to intelligently design effective treatment regimens, and may have contributed to the failures of clinical trials that targeted a single cell type or specific protein. To bridge this gap in our understanding, we propose to develop a Comprehensive Brain Cellular Alteration Profiling Toolkit (CBAT), a carefully validated and broadly applicable image analysis toolkit with unprecedented potential to accelerate investigation & development of next-generation treatments for brain diseases. CBAT, in association with a flexible and modular protocol for highly multiplexed IHC, will enable simultaneous profiling of all major brain cell types and their functional/pathological status (e.g., resting, reactive, apoptotic) across whole brain sections. It will provide quantitative readouts of cellular alterations at multiple scales ranging from individual cells of all types to multi- cellular units (e.g. niches), brain cell layers, and brain regions. Comprehensive cellular profiling and measurements generated using CBAT will enable a deeper understanding of pathological cellular changes that will enable accelerated design, testing, and optimization of therapeutic interventions. Further, it will reduce overall experimental costs by replacing a large number of less-informative assays with a single comprehensive assay. In the longer term, it will enhance our ability to conduct the systems-level investigations that will be required for fully understanding, and successfully treating, multiple brain pathologies. To achieve these goals, we propose the following aims:
Aim 1 : Develop and validate a flexible, scalable, extensible, and reproducible method for comprehensive whole slide imaging of all the major brain cell types in stereotactically aligned rat whole brain sections;
Aim 2 : Develop and validate a turnkey software system profiling cell identify and status at multiple scales ranging from individual cells to multi-cellular units, brain cell layers, and brain anatomic regions;
and Aim 3 : Test the utility of the CBAT system to comprehensively profile concussion biology, and assess the effectiveness of a drug combination to reduce newly identified pathologies. After its development and validation, CBAT will be disseminated to the research community at no cost for use in their specific research projects.

Public Health Relevance

There is a compelling need to accelerate the development of effective treatments for diseases of the brain. Incomplete understanding of the changes that occur in the brain may have led to the failure of clinical trials to block or retard disease processes. We propose to develop a Comprehensive Brain Cellular Alteration Profiling Toolkit (CBAT) to quantitate changes in all cell types found in the brain that will have broad applicability to accelerate the design, testing, and optimization of novel drug and combination drug treatments for treating brain injuries, diseases and dementias.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
1R01NS109118-01A1
Application #
9819169
Study Section
Emerging Imaging Technologies and Applications Study Section (EITA)
Program Officer
Bellgowan, Patrick S F
Project Start
2019-07-01
Project End
2024-03-31
Budget Start
2019-07-01
Budget End
2020-03-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Houston
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
036837920
City
Houston
State
TX
Country
United States
Zip Code
77204