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Image Correlation Spectroscopy to Define Membrane Dynamics

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Live Cell Imaging

Part of the book series: Methods in Molecular Biology ((MIMB,volume 591))

Abstract

Fluorescent imaging techniques are powerful tools that aid in studying protein dynamics and membrane domains and allow for the visualization and data collection of such structures as caveolae and clathrin-coated pits, key players in the regulation of cell communication and signaling. The family of image correlation spectroscopy (FICS) provides a unique way to determine details about aggregation, clustering, and dynamics of proteins on the plasma membrane. FICS consists of many imaging techniques which we will focus on including image correlation spectroscopy, image cross-correlation spectroscopy and dynamic image correlation spectroscopy. Image correlation spectroscopy is a tool used to calculate the cluster density, which is the average number of clusters per unit area along with data to determine the degree of aggregation of plasma membrane proteins. Image cross-correlation spectroscopy measures the colocalization of proteins of interest. Dynamic image correlation spectroscopy can be used to analyze protein aggregate dynamics on the cell surface during live-cell imaging in the millisecond to second range.

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References

  1. Abrami L, Fivaz M, van der Goot FG. (2000) Surface dynamics of aerolysin on the plasma membrane of living cells. Int J Med Microbiol. 290(4–5):363–7.

    CAS  PubMed  Google Scholar 

  2. Abumrad NA, Sfeir Z, Connelly MA, Coburn C. (2000) Lipid transporters: membrane transport systems for cholesterol and fatty acids. Curr Opin Clin Nutr Metab Care. 3(4):255–62.

    Article  CAS  PubMed  Google Scholar 

  3. Barr FA, Shorter J. (2000) Membrane traffic: do cones mark sites of fission? Curr Biol. 10(4):R141–4.

    Article  CAS  PubMed  Google Scholar 

  4. Basanez G. (2002) Membrane fusion: the process and its energy suppliers. Cell Mol Life Sci. 59(9):1478–90.

    Article  CAS  PubMed  Google Scholar 

  5. Bechinger B. (2000) Understanding peptide interactions with the lipid bilayer: a guide to membrane protein engineering. Curr Opin Chem Biol. 4(6):639–44.

    Article  CAS  PubMed  Google Scholar 

  6. Anderson RG, Jacobson K. (2002) A role for lipid shells in targeting proteins to caveolae, rafts, and other lipid domains. Science. 296(5574):1821–5.

    Article  CAS  PubMed  Google Scholar 

  7. Barnett-Norris J, Lynch D, Reggio PH. (2005) Lipids, lipid rafts and caveolae: their importance for GPCR signaling and their centrality to the endocannabinoid system. Life Sci. 77(14):1625–39.

    Article  CAS  PubMed  Google Scholar 

  8. Bathori G, Cervenak L, Karadi I. (2004) Caveolae -an alternative endocytotic pathway for targeted drug delivery. Crit Rev Ther Drug Carrier Syst. 21(2):67–95.

    Article  PubMed  Google Scholar 

  9. Brown DA, London E. (1998) Functions of lipid rafts in biological membranes. Annu Rev Cell Dev Biol. 14:111–36.

    Article  CAS  PubMed  Google Scholar 

  10. Cohen AW, Hnasko R, Schubert W, Lisanti MP. (2004) Role of caveolae and caveolins in health and disease. Physiol Rev. 84(4): 1341–79.

    Article  CAS  PubMed  Google Scholar 

  11. Dobrowsky RT. (2000) Sphingolipid signalling domains floating on rafts or buried in caves? Cell Signal. 12(2):81–90.

    Article  CAS  PubMed  Google Scholar 

  12. Fielding CJ, Fielding PE. (2004) Membrane cholesterol and the regulation of signal transduction. Biochem Soc Trans. 32(1):65–9.

    Article  CAS  PubMed  Google Scholar 

  13. Galbiati F, Razani B, Lisanti MP. (2001) Emerging themes in lipid rafts and caveolae. Cell. 106(4):403–11.

    Article  CAS  PubMed  Google Scholar 

  14. Brown CM, Roth MG, Henis YI, Petersen NO. (1999) An internalization-competent influenza hemagglutinin mutant causes the redistribution of AP-2 to existing coated pits and is colocalized with AP-2 in clathrin free clusters. Biochemistry.38(46):15166–73.

    Article  CAS  PubMed  Google Scholar 

  15. Fire E, Brown CM, Roth MG, Henis YI, Petersen NO. (1997) Partitioning of proteins into plasma membrane microdomains. Clustering of mutant influenza virus hemagglutinins into coated pits depends on the strength of the internalization signal. J Biol Chem. 272(47):29538–45.

    Article  CAS  PubMed  Google Scholar 

  16. Nohe A, Petersen NO. (2004) Analyzing protein–protein interactions in cell membranes. Bioessays. 26(2):196–203.

    Article  CAS  PubMed  Google Scholar 

  17. Nohe A, Petersen NO. (2007) Image correlation spectroscopy. Sci STKE. 2007. DOI:10.1126/stke.4172007P17 417:l7.

    Google Scholar 

  18. Wiseman PW, Hoddelius P, Petersen NO, Magnusson KE. (1997) Aggregation of PDGF-beta receptors in human skin fibroblasts: characterization by image correlation spectroscopy (ICS). FEBS Lett. 401(1):43–8.

    Article  CAS  PubMed  Google Scholar 

  19. Wiseman PW, Petersen NO. (1999) Image correlation spectroscopy. II. Optimization for ultrasensitive detection of preexisting platelet-derived growth factor-beta receptor oligomers on intact cells. Biophys J. 76(2):963–77.

    Article  CAS  PubMed  Google Scholar 

  20. Nohe A, Hassel S, Ehrlich M, Neubauer F, Sebald W. and Knaus P. (2002). The mode of BMP receptor oligomerization determines different BMP-2 signaling pathways. J. Biol. Chem. 15:5330–8.

    Article  CAS  PubMed  Google Scholar 

  21. Nohe A, Keating E, Underhill TM, Knaus P, Petersen NO. (2003) Effect of the distribution and clustering of the type I A BMP receptor (ALK3) with the type II BMP receptor on the activation of signalling pathways. J Cell Sci. 116(16):3277–84.

    Article  CAS  PubMed  Google Scholar 

  22. Nohe A, Keating E, Underhill TM, Knaus P, Petersen NO. (2005) Dynamics and interaction of caveolin-1 isoforms with BMP-receptors. J Cell Sci. 118(3):643–50.

    Article  CAS  PubMed  Google Scholar 

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© 2010 Humana Press, a part of Springer Science+Business Media, LLC

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Bonor, J., Nohe, A. (2010). Image Correlation Spectroscopy to Define Membrane Dynamics. In: Papkovsky, D. (eds) Live Cell Imaging. Methods in Molecular Biology, vol 591. Humana Press. https://doi.org/10.1007/978-1-60761-404-3_21

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  • DOI: https://doi.org/10.1007/978-1-60761-404-3_21

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60761-403-6

  • Online ISBN: 978-1-60761-404-3

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