The Notch signaling pathway enables neighboring cells to coordinate developmental fates in diverse processes such as angiogenesis, neuronal differentiation, and immune system development. Although key components and interactions in the Notch pathway are known, it remains unclear how they work together to determine the cell's signaling state, defined as its quantitative ability to send and receive signals using particular Notch receptors and ligands. Recent work suggests that several aspects of the system can lead to complex signaling behaviors: First, receptors and ligands interact in two distinct ways, inhibiting each other in the same cell (in cis) while productively interacting between cells (in trans) to signal. The ability of a cell to send or receive signals depends strongly on both types o interactions. Second, mammals have multiple types of receptors and ligands, which interact with different strengths, and are frequently co-expressed in natural systems. Third, the three mammalian Fringe proteins can modify receptor-ligand interaction strengths in distinct and ligand-specific ways. Consequently, cells can exhibit non-intuitive signaling states even with relatively few components. In order to understand what signaling states occur in natural processes, and what types of signaling behaviors they enable, this proposal seeks to develop a quantitative and predictive understanding of how the Notch signaling state is determined by the expression levels of receptors, ligands, and Fringe proteins. To do so, we will construct a set of cell lines that allow control of ligand and Fringe expression level, and readout of the resulting Notch activity. We will subject these cell lines to an assay that will quantitatively assess the levels of Notch ligands and receptors simultaneously available on the surface of individual cells. We will use time-lapse microscopy and quantitative image analysis to systematically measure both cis and trans interaction strengths between different ligand-receptor combinations at the level of individual cells. We will further analyze the dependence of these interactions on the level and type of Fringe expression, as well as the effects of interactions between multiple Fringe proteins. We will develop a mathematical modeling framework that uses these data to predict the signaling states of individual cells from component expression levels. We will test these predictions using a microwell patterning system that allows us to analyze both send and receive states of a single cell by co-culturing it with a single neighbor. These methods will allow us to reconstitute and analyze a diverse set of Notch signaling configurations from the bottom up, and provide a comprehensive view of the signaling repertoire of this critical signaling pathway. The results will provide insight into numerous mammalian developmental systems, and could facilitate rational intervention into Notch-dependent disease processes.

Public Health Relevance

Intercellular signaling through the Notch pathway mediates critical and diverse developmental patterning processes including neurogenesis, somitogenesis, angiogenesis, and hematopoietic development. The disruption of Notch signaling is implicated in a number of diseases. This proposal will provide an understanding of how components of the Notch pathway together determine the signaling states of individual cells, and how perturbations of pathway components, such as those that occur in disease, alter these signaling states. The approach involves quantitative single-cell analysis of reconstituted signaling pathways together with mathematical modeling. The results will elucidate mechanisms of Notch function and support the development of pharmacological interventions.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01HD075335-03
Application #
8683211
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Mukhopadhyay, Mahua
Project Start
Project End
Budget Start
Budget End
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
California Institute of Technology
Department
None
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
City
Pasadena
State
CA
Country
United States
Zip Code
91125