Immunophenotyping using flow cytometry is in a position similar to that of genomics a decade ago. Highly polychromatic assays with 6 to 18 colors have been demonstrated in academic labs, but have generally not been regularly deployed for clinical studies in a robust, industrialized manner. Immune system monitoring in humans, including the application of sophisticated multi-parameter flow cytometry, would make possible indepth phenotyping that more directly reflects disease pathogenesis and progression. Polychromatic flow cytometry provides a powerful assessment of immune function based on differences in cell numbers, cell types and the expression of cell-associated surface and intracellular molecules related to immune perturbation. Development of a comprehensive platform that introduces: automation to cell processing;highspeed cell interrogation running a 96-well plate in under six minutes;and multidimensional data analysis tools implementing the newly developed "FLAME" program will allow the precise and robust measurement of human immune responses to viral vaccines and infections.
The aim of this core is to bring new technologies to the U19 to achieve high throughput but also robust and precise examinafion of the immune cell status before, during and after immunization or infecfion. The bulk of all samples collected from Projects 1 and 2 will be processed and analyzed by Flow Cytometry using a state-of-the-art robotics platform. The multidimensional robotic flow core has the capability to use validated robotic methods to process blood samples, resulfing in minimal variafion in cell preparafion. The processed samples will be prepared using the robofic platform to detect the level of immune status markers of different cell populations using polychromafic flow cytometry. The application of robotics, careful quality control of reagents, and automated downstream analysis of flow-data in mulfi-dimensional space is crifical in the U19's challenge to establish this network of human immunology profiling research groups.

Agency
National Institute of Health (NIH)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI089992-05
Application #
8699134
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
Budget End
Support Year
5
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Yale University
Department
Type
DUNS #
City
New Haven
State
CT
Country
United States
Zip Code
06510
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