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.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Postdoctoral Individual National Research Service Award (F32)
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Special Emphasis Panel (ZRG1-F05-R (20))
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Sakalian, Michael
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Harvard University
Anatomy/Cell Biology
Schools of Medicine
United States
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Mendoza, Michelle C; Vilela, Marco; Juarez, Jesus E et al. (2015) ERK reinforces actin polymerization to power persistent edge protrusion during motility. Sci Signal 8:ra47
Martin, Katrin; Vilela, Marco; Jeon, Noo Li et al. (2014) A growth factor-induced, spatially organizing cytoskeletal module enables rapid and persistent fibroblast migration. Dev Cell 30:701-16
Vilela, Marco; Halidi, Nadia; Besson, Sebastien et al. (2013) Fluctuation analysis of activity biosensor images for the study of information flow in signaling pathways. Methods Enzymol 519:253-76