Cell signaling is the process by which cells communicate with each other and with their environments and its regulation is critically important to maintaining homeostasis at the tissue, organ, and organism level. Because aberrant signal transduction underlies the pathogenesis of most diseases, the study of cell signaling has become a central part of cell and molecular biology research. However, current methodologies to analyze cell signaling suffer from multiple technical limitations. For example, signaling pathways are traditionally analyzed using biochemical methods that average measurements obtained across thousands of cells simultaneously, providing an impression of the global signaling landscape that ignores underlying cell-to-cell variability, as well as dynamic localizations and translocations of the molecular mediators. While fluorescence microscopy has the potential to overcome this limitation by enabling real-time observations of rapid molecular events at sub- micron resolution, these methods do not provide sufficient sensitivity or signal stability to observe discrete single-molecule events. Recently, our ability to image cellular processes has been transformed by single- molecule imaging due to advances in fluorescent quantum dot probes and bioorthogonal labeling chemistries. Simultaneously, advanced cell engineering tools like CRISPR/Cas9 and micropatterning now allow us to precisely control cellular genotype and morphology to facilitate imaging of single proteins in a native cellular context. These technologies have matured individually and we propose that they are now primed to be applied as a cohesive suite of tools for precise mapping and analysis of cell signaling. As such, the goal of this proposal is to develop and validate three technologies that in combination will enable intracellular single- molecule analysis including (1) QD labels for intracellular imaging of molecular processes, (2) native protein tagging through gene editing for efficient conjugation, and (3) automated image analysis algorithms optimized to spatially map processes in micropatterned cells across different time scales and registered intracellular locations. We anticipate that by simultaneously advancing these technologies, we will create a novel platform to study cell signaling in living cells with single-molecule resolution in real-time. We will accomplish our objectives through the collaborative work of a multidisciplinary team integrated by Dr. Andrew Smith, who is an expert in optical probe engineering and imaging, and Dr. Pablo Perez-Pinera, who has extensive expertise in gene editing and genome engineering. Their laboratories have been working together for years to initiate the work described in this application. Conceptually, this platform is a revolutionary method to analyze cell signaling and, therefore, it will not only improve our understanding of essential biological processes, but can also enable the development of therapeutics that target these pathways with unprecedented precision and efficacy.

Public Health Relevance

Signal transduction mechanisms are conserved across eukaryotic organisms and fundamentally regulate human development, health, and disease. However, the biochemical methods that traditionally have been used to study cell signaling lack sensitivity and fail to provide spatiotemporal resolution, which are critical parameters to understand these processes at a systems level. Here we propose to develop a novel single-molecule imaging technology that will enable analysis of cell signaling with unprecedented precision and resolution and will ultimately transform our understanding of biology, human physiology, and pathology.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM131272-01
Application #
9653043
Study Section
Cellular and Molecular Technologies Study Section (CMT)
Program Officer
Sammak, Paul J
Project Start
2019-03-01
Project End
2023-02-28
Budget Start
2019-03-01
Budget End
2020-02-29
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Illinois Urbana-Champaign
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
041544081
City
Champaign
State
IL
Country
United States
Zip Code
61820