Most human diseases and disorders can be seen as a projection of disrupted cellular components. Such anomalies restrain and/or modify the natural flow of information among the cellular processes, impairing appropriate cell decision. For instance, mutation of the small GTPase proteins can lead to abnormal cell migration. This simplistic description of an aberrant process highlights the importance of probing not only how information is transmitted, e.g. through amino acid phosphorylation, but also the direction it takes from a given point. The discovery of this directionality potentially defines the function of given cellular component. For example, an active form of a protein switches on a specific cellular behavior at a particular region of the cell. Biosensor technology has been proposed to overcome the current limitations of classical biochemical methods on the process of establishing signaling pathway functionality. These fluorescent constructs allow the measurement of the localization and the active state of the studied molecule in living cells. Because proteins can interact with different molecules in different cellular locations, biosensor technology stands out as a powerful tool to address questions of how differently regulated a given protein is in time and space. This proposal focuses on the computational analysis of biosensor imaging data. The main goal is to build a set of computational tools that will infer paths among molecules and specific cellular behavior from biosensor images. As a proof of concept, the second part of this project focuses on the elucidation of Rac1 regulation at the lamellipodia region of cells using the proposed computational tools. This challenge sets up the suitability and relevance of the computational tools proposed here.

Public Health Relevance

Human pathologies and abnormalities are usually associated with an anomalous cellular behavior. In turn, the cell decision process is largely modulated by protein activity. The main idea of this proposal is to build computational tools that will use biosensor images to relate protein activity to a specific cellular behavior.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32GM103278-02
Application #
8607468
Study Section
Special Emphasis Panel (ZRG1-F05-R (20))
Program Officer
Sakalian, Michael
Project Start
2013-01-01
Project End
2014-06-30
Budget Start
2014-01-01
Budget End
2014-06-30
Support Year
2
Fiscal Year
2014
Total Cost
$26,971
Indirect Cost
Name
Harvard University
Department
Anatomy/Cell Biology
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115