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Rhodopsin pp 205-219 | Cite as

Detection of Rhodopsin Dimerization In Situ by PIE-FCCS, a Time-Resolved Fluorescence Spectroscopy

Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1271)

Abstract

Rhodopsin self-associates in the plasma membrane. At low concentrations, the interactions are consistent with a monomer-dimer equilibrium (Comar et al., J Am Chem Soc 136(23):8342–8349, 2014). At high concentrations in native tissue, higher-order clusters have been observed (Fotiadis et al., Nature 421:127–128, 2003). The physiological role of rhodopsin dimerization is still being investigated, but it is clear that a quantitative assessment is essential to determining the function of rhodopsin clusters in vision. To quantify rhodopsin interactions, I will outline the theory and methodology of a specialized time-resolved fluorescence spectroscopy for measuring membrane protein-protein interactions called pulsed-interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS). The strength of this technique is its ability to quantify rhodopsin interactions in situ (i.e., a live cell plasma membrane). There are two reasons for restricting the scope to live cell membranes. First, the compositional heterogeneity of the plasma membrane creates a complex milieu with thousands of lipid, protein, and carbohydrate species. This makes it difficult to infer quaternary interactions from detergent solubilized samples or construct a model phospholipid bilayer that recapitulates all of the interactions present in native membranes. Second, organizational structure and dynamics is a key feature of the plasma membrane, and fixation techniques like formaldehyde cross-linking and vitrification will modulate the interactions.

PIE-FCCS is based on two-color fluorescence imaging with time-correlated single-photon counting (TCSPC) (Becker et al., Rev Sci Instrum 70:1835–1841, 1999). By time-tagging every detected photon, the data can be analyzed as a fluorescence intensity distribution, fluorescence lifetime histogram, or fluorescence (cross-)correlation spectra (FCS/FCCS) (Becker, Advanced time-correlated single-photon counting techniques, Springer, Berlin, 2005). These analysis tools can then be used to quantify protein concentration, mobility, clustering, and Förster resonance energy transfer (FRET). In this paper I will focus on PIE-FCCS, which interleaves two wavelength excitation events in time so that the effects of spectral cross-talk and FRET can be isolated. In this way it is possible to characterize monomer-dimer-oligomer equilibria with high accuracy (Müller et al., Biophys J 89:3508–3522, 2005). Currently, PIE-FCCS requires a customized equipment configuration that will be described below. There is an excellent protocol that outlines traditional FCCS on a commercially available instrument (Bacia and Schwille, Nat Protoc 2:2842–2856, 2007). The PIE-FCCS approach is a relatively recent advance in FCCS that has been used in live cell assays to quantify lipid-anchored protein clustering (Triffo et al., J Am Chem Soc 134:10833–10842, 2012), epidermal growth factor receptor dimerization (Endres et al., Cell 152:543–556, 2013), and recently the dimerization of opsin (Comar et al., J Am Chem Soc 136(23):8342–8349, 2014). This paper will outline the theory and instrumentation requirements for PIE-FCCS, as well as the data collection and analysis process.

Key words

Rhodopsin dimerization Membrane protein dynamics Fluorescence correlation spectroscopy Time-correlated single-photon counting Pulsed-interleaved excitation 

References

  1. 1.
    Comar WD, Schubert SM, Jastrzebska B et al (2014) Time-resolved fluorescence spectroscopy measures clustering and mobility of a G protein-coupled receptor opsin in live cell membranes. J Am Chem Soc 136(23):8342–8349CrossRefPubMedGoogle Scholar
  2. 2.
    Fotiadis D, Liang Y, Filipek S et al (2003) Atomic-force microscopy: rhodopsin dimers in native disc membranes. Nature 421:127–128CrossRefPubMedGoogle Scholar
  3. 3.
    Becker W, Hickl H, Zander C et al (1999) Time-resolved detection and identification of single analyte molecules in microcapillaries by time-correlated single-photon counting (TCSPC). Rev Sci Instrum 70:1835–1841CrossRefGoogle Scholar
  4. 4.
    Becker W (ed) (2005) Advanced time-correlated single photon counting techniques, vol 81. Springer, BerlinGoogle Scholar
  5. 5.
    Müller BK, Zaychikov E, Bräuchle C et al (2005) Pulsed interleaved excitation. Biophys J 89:3508–3522CrossRefPubMedCentralPubMedGoogle Scholar
  6. 6.
    Bacia K, Schwille P (2007) Practical guidelines for dual-color fluorescence cross-correlation spectroscopy. Nat Protoc 2:2842–2856CrossRefPubMedGoogle Scholar
  7. 7.
    Triffo SB, Huang HH, Smith AW et al (2012) Monitoring lipid anchor organization in cell membranes by PIE-FCCS. J Am Chem Soc 134:10833–10842CrossRefPubMedCentralPubMedGoogle Scholar
  8. 8.
    Endres NF, Das R, Smith AW et al (2013) Conformational coupling across the plasma membrane in activation of the EGF receptor. Cell 152:543–556CrossRefPubMedCentralPubMedGoogle Scholar
  9. 9.
    Giepmans BNG, Adams SR, Ellisman MH et al (2006) The fluorescent toolbox for assessing protein location and function. Science 312:217–224CrossRefPubMedGoogle Scholar
  10. 10.
    Digman MA, Gratton E (2011) Lessons in fluctuation correlation spectroscopy. Annu Rev Phys Chem 62:645–668CrossRefPubMedCentralPubMedGoogle Scholar
  11. 11.
    Olofsson L, Margeat E (2013) Pulsed interleaved excitation fluorescence spectroscopy with a supercontinuum source. Opt Express 21:3370–3378CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of ChemistryUniversity of AkronAkronUSA

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