Natural killer (NK) cells are the major effector lymphocytes of innate immunity that play a critical role in the immune surveillance of cancer and infection. NK cells distinguish between healthy and abnormal cells by using an array of activating and inhibitory receptors to recognize their respective ligands expressed on a target cell. NK cell recognition determines the education, development, differentiation, function and memory of an NK cell. Thus, understanding the molecular mechanism of NK cell recognition is of critical importance in immunology. NK cell recognition has following important characteristics: (1) it is dynamic ? NK cell recognition is governed by the transient receptor-ligand interactions at the live cell membrane, (2) it is complex ? multiple receptor- ligand interactions function together to determine the responsiveness of an NK cell, (3) it is specific ? NK cells can discriminate between healthy and abnormal cells, (4) it is safe ? NK cell activation is stringently controlled by inhibitory receptors to avoid inadvertent stimulation, (5) it is a binding-signaling coupled process ? an NK cell is able to translate its binding events to cellular signals, and (6) it is a signaling integration process. This complexity reflects the uniquely demanding nature of NK cell recognition, which requires simultaneous detection of multiple ligands on the surface of the target cell being surveyed, precise propagation of recognition signals across the cell membrane, rational integration of activating and inhibitory signals, and fine- tuning of NK cell immune responses. The importance and complexity of NK cell recognition has motivated intensive research for the understanding of the fundamental molecular mechanism. Many models have been proposed but the molecular mechanism governing NK cell recognition remains elusive. The main problem in most studies is the inability to directly measure in situ receptor-ligand interactions with single-molecule resolution, simultaneously visualize real-time live NK cell signaling at the single-cell level, and comprehensively determine the functional phenotypes of individual NK cells. Here we propose an integration model that an NK cell determines its activation threshold by integrating the strength and amplitude of different activating and inhibitory signals from an encountered target cell (responsiveness) and then adjusts it to determine the future threshold for activation upon a new encounter (memory). To test our hypothesis, we propose to apply our state-of-the-art single-cell micropipette assays, single-molecule and super-resolution imaging, and single-cell sequencing technologies, to directly and precisely measure surface molecular interactions, intracellular signaling, and transcriptome and proteome of single NK cells at the single-molecule level. These data can fully address the molecular mechanism of signal reception, transduction, integration, and regulation of NK cell recognition. The results will allow us to test our hypothesis and settle a long-standing question in immunology. The knowledge gained from this study will greatly advance our understanding of NK cells and will have important implications for the development of immunotherapy against cancer and infection.

Public Health Relevance

Natural killer (NK) cells distinguish between healthy cells and abnormal cells. Understanding the molecular mechanism of NK cell recognition will directly advance the understanding, prevention, and treatment of cancer and infection.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
NIH Director’s New Innovator Awards (DP2)
Project #
1DP2AI144245-01
Application #
9562546
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lapham, Cheryl K
Project Start
2018-09-30
Project End
2023-06-30
Budget Start
2018-09-30
Budget End
2023-06-30
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Chicago
Department
Type
Organized Research Units
DUNS #
005421136
City
Chicago
State
IL
Country
United States
Zip Code
60637