title: Automated line scan analysis to quantify biosensor activity at the cell edge.
abstract: Biosensors are valuable tools used to image the subcellular localization and kinetics of protein activity in living cells. Signaling at the edge of motile cells that regulates cell protrusion and retraction is important in many aspects of cell physiology, and frequently studied using biosensors. However, quantitation and interpretation is limited by the heterogeneity of this signaling behavior; automated analytical approaches are required to systematically extract large data sets from biosensor studies for statistical analysis. Here we describe an automated analysis to relate the velocity at specific points along the cell edge with biosensor activity in adjoining regions. Time series of biosensor images are processed to interpolate a smooth edge of the cell at each time point. Profiles of biosensor activity ('line scans') are then calculated along lines perpendicular to the cell edge. An energy minimization method is used to calculate a velocity associated with each line scan. Sorting line scans by the proximal velocity has generated novel biological insights, as exemplified by analysis of the Src merobody biosensor. With the large data sets that can be generated automatically by this program, conclusions can be drawn that are not apparent from qualitative or 'manual' quantitative techniques. Our 'LineScan' software includes a graphical user interface (GUI) to facilitate application in other studies. It is available at hahnlab.com and is exemplified here in a study using the RhoC FLARE biosensor.
authors.affiliation: Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
authors.forename: R J
authors.initials: RJ
authors.lastname: Allen
authors.affiliation: Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
authors.forename: D
authors.initials: D
authors.lastname: Tsygankov
authors.affiliation: Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
authors.forename: J S
authors.initials: JS
authors.lastname: Zawistowski
authors.affiliation: Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
authors.forename: T C
authors.initials: TC
authors.lastname: Elston
authors.affiliation: Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States. Electronic address: khahn@med.unc.edu.
authors.forename: K M
authors.initials: KM
authors.lastname: Hahn
mesh_terms: D000818:Animals; D015374:Biosensing Techniques; D002478:Cells, Cultured; D007091:Image Processing, Computer-Assisted; D051379:Mice; D012984:Software; D018631:ras Proteins / Q000378:metabolism; D000075024:rhoC GTP-Binding Protein
chemical_list: C512911:Rhoc protein, mouse; D018631:ras Proteins; D000075024:rhoC GTP-Binding Protein
keywords: Actin; Biosensor; GUI; Linescan; Motility; Software