Publication

Software for lattice light-sheet imaging of FRET biosensors, illustrated with a new Rap1 biosensor

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Last modified
  • 05/15/2025
Type of Material
Authors
    Ellen C. O'Shaughnessy, University of North CarolinaOrrin J. Stone, University of North CarolinaPaul K. LaFosse, University of North CarolinaMihai L. Azoitei, University of North CarolinaDenis Tsygankov, Emory UniversityJohn M. Heddleston, Howard Hughes Medical InstituteWesley R. Legant, University of North CarolinaErika S. Wittchen, University of North CarolinaKeith Burridge, University of North CarolinaTimothy C. Elston, University of North CarolinaEric Betzig, Howard Hughes Medical InstituteTeng-Leong Chew, Howard Hughes Medical InstituteDavid Adalsteinsson, University of North CarolinaKlaus M. Hahn, University of North Carolina
Language
  • English
Date
  • 2019-09-01
Publisher
  • Rockefeller University Press
Publication Version
Copyright Statement
  • © 2019 O’Shaughnessy et al.
License
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 218
Issue
  • 9
Start Page
  • 3153
End Page
  • 3160
Grant/Funding Information
  • We thank the National Institutes of Health (R35GM122596 and R01HL133668) and the U.S. Department of Defense (W911NF-15-1-0631/A16-0438-001) for their support.
Supplemental Material (URL)
Abstract
  • Lattice light-sheet microscopy (LLSM) is valuable for its combination of reduced photobleaching and outstanding spatiotemporal resolution in 3D. Using LLSM to image biosensors in living cells could provide unprecedented visualization of rapid, localized changes in protein conformation or posttranslational modification. However, computational manipulations required for biosensor imaging with LLSM are challenging for many software packages. The calculations require processing large amounts of data even for simple changes such as reorientation of cell renderings or testing the effects of user-selectable settings, and lattice imaging poses unique challenges in thresholding and ratio imaging. We describe here a new software package, named ImageTank, that is specifically designed for practical imaging of biosensors using LLSM. To demonstrate its capabilities, we use a new biosensor to study the rapid 3D dynamics of the small GTPase Rap1 in vesicles and cell protrusions.
Author Notes
  • Correspondence: David Adalsteinsson (david@unc.edu); Klaus M. Hahn (khahn@med.unc.edu); P.K.LaFosse’s present address is National Institutes of Mental Health, Bethesda, MD; W.R. Legant’s present address is Departments of Pharmacology and Biomedical Engineering, the University of North Carolina at Chapel Hill, Chapel Hill, NC; E. Betzig’s present address is the Department of Physics, University of California, Berkeley, Berkeley, CA
Keywords
Research Categories
  • Biology, Cell

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