Observing Protein Interactions and Their Stoichiometry in Living Cells by Brightness Analysis of Fluorescence Fluctuation Experiments
School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota, USA. Methods in enzymology
(Impact Factor: 2.09).
01/2010; 472:345-63. DOI: 10.1016/S0076-6879(10)72026-7
A single fluorescently labeled protein generates a short burst of light whenever it passes through a tiny observation volume created within a biological cell. The average amplitude of the burst is related to the stoichiometry of the fluorescently labeled protein complex. Fluorescence fluctuation spectroscopy quantifies the burst amplitude by introducing the brightness parameter. Brightness provides a spectroscopic marker for observing protein interactions and their stoichiometry directly inside cells. Not all fluorescent proteins are suitable for brightness experiments. Here we discuss how brightness properties of the fluorophore influence brightness measurements and how to identify a well-behaved fluorescent protein. Protein interactions and stoichiometry are determined from a brightness titration. Experimental details of brightness titration measurements are described together with the necessary calibration and control experiments.
Available from: PubMed Central
- "If each subunit is tagged with only a single fluorophore, the normalized brightness will reflect the number of subunits in a complex. This is called Brightness Analysis
. In addition, FCS can also determine the average amount of time a protein complex remains in the observation volume ; a value related to the lateral diffusion coefficient of the complex, itself a function of viscosity, mass and hydrodynamic volume (and hence the conformation of the complex). "
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ABSTRACT: Förster resonance energy transfer (FRET) microscopy is frequently used to study protein interactions and conformational changes in living cells. The utility of FRET is limited by false positive and negative signals. To overcome these limitations we have developed Fluorescence Polarization and Fluctuation Analysis (FPFA), a hybrid single-molecule based method combining time-resolved fluorescence anisotropy (homo-FRET) and fluorescence correlation spectroscopy. Using FPFA, homo-FRET (a 1-10 nm proximity gauge), brightness (a measure of the number of fluorescent subunits in a complex), and correlation time (an attribute sensitive to the mass and shape of a protein complex) can be simultaneously measured. These measurements together rigorously constrain the interpretation of FRET signals. Venus based control-constructs were used to validate FPFA. The utility of FPFA was demonstrated by measuring in living cells the number of subunits in the α-isoform of Venus-tagged calcium-calmodulin dependent protein kinase-II (CaMKIIα) holoenzyme. Brightness analysis revealed that the holoenzyme has, on average, 11.9 ± 1.2 subunit, but values ranged from 10-14 in individual cells. Homo-FRET analysis simultaneously detected that catalytic domains were arranged as dimers in the dodecameric holoenzyme, and this paired organization was confirmed by quantitative hetero-FRET analysis. In freshly prepared cell homogenates FPFA detected only 10.2 ± 1.3 subunits in the holoenzyme with values ranging from 9-12. Despite the reduction in subunit number, catalytic domains were still arranged as pairs in homogenates. Thus, FPFA suggests that while the absolute number of subunits in an auto-inhibited holoenzyme might vary from cell to cell, the organization of catalytic domains into pairs is preserved.
PLoS ONE 05/2012; 7(5):e38209. DOI:10.1371/journal.pone.0038209 · 3.23 Impact Factor
Available from: Louis M Mansky
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ABSTRACT: Human T-cell leukemia virus type 1 (HTLV-1) has a reputation for being extremely difficult to study in cell culture. The challenges in propagating HTLV-1 has prevented a rigorous analysis of how these viruses replicate in cells, including the detailed steps involved in virus assembly. The details for how retrovirus particle assembly occurs are poorly understood, even for other more tractable retroviral systems. Recent studies on HTLV-1 using state-of-the-art cryo-electron microscopy and fluorescence-based biophysical approaches explored questions related to HTLV-1 particle size, Gag stoichiometry in virions, and Gag-Gag interactions in living cells. These results provided new and exciting insights into fundamental aspects of HTLV-1 particle assembly-which are distinct from those of other retroviruses, including HIV-1. The application of these and other novel biophysical approaches promise to provide exciting new insights into HTLV-1 replication.
Viruses 06/2011; 3(6):770-93. DOI:10.3390/v3060770 · 3.35 Impact Factor
Available from: ncbi.nlm.nih.gov
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ABSTRACT: Cell-free synthesis, a method for the rapid expression of proteins, is increasingly used to study interactions of complex biological systems. GFP and its variants have become indispensable for fluorescence studies in live cells and are equally attractive as reporters for cell-free systems. This work investigates the use of fluorescence fluctuation spectroscopy (FFS) as a tool for quantitative analysis of protein interactions in cell-free expression systems. We also explore chromophore maturation of fluorescent proteins, which is of crucial importance for fluorescence studies. A droplet sample protocol was developed that ensured sufficient oxygenation for chromophore maturation and ease of manipulation for titration studies. The kinetics of chromophore maturation of EGFP, EYFP, and mCherry were analyzed as a function of temperature. A strong increase in the rate from room temperature to 37°C was observed. We further demonstrate that all EGFP proteins fully mature in the cell-free solution and that brightness is a robust parameter specifying stoichiometry. Finally, FFS is applied to study the stoichiometry of the nuclear transport factor 2 in a cell-free system over a broad concentration range. We conclude that combining cell-free expression and FFS provides a powerful technique for quick, quantitative study of chromophore maturation and protein-protein interaction.
Analytical Biochemistry 10/2011; 421(1):291-8. DOI:10.1016/j.ab.2011.10.040 · 2.22 Impact Factor
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