Novel calibration method for flow cytometric fluorescence resonance energy transfer measurements between visible fluorescent proteins

BACKGROUND

The combination of fluorescence resonance energy transfer (FRET) and flow cytometry offers a statistically firm approach to study protein associations. Fusing green fluorescent protein (GFP) to a studied protein usually does not disturb the normal function of a protein, but quantitation of FRET efficiency calculated between GFP derivatives poses a problem in flow cytometry.

METHODS

We generated chimeras in which cyan fluorescent protein (CFP) was separated by amino acid linkers of different sizes from yellow fluorescent protein (YFP) and used them to calibrate the cell-by-cell flow cytometric FRET measurements carried out on two different dual-laser flow cytometers. Then, CFP-Kip1 was coexpressed in yeast cells with YFP and cyclin-dependent kinase-2 (Cdk2) and served as a positive control for FRET measurements, and CFP-Kip1 coexpressed with a random peptide fused to YFP was the negative control.

RESULTS

We measured donor, direct, and sensitized acceptor fluorescence intensities and developed a novel way to calculate a factor (alpha) that characterized the fluorescence intensity of acceptor molecules relative to the same number of excited donor molecules, which is essential for quantifying FRET efficiency. This was achieved by calculating FRET efficiency in two different ways and minimizing the squared difference between the two results by changing alpha. Our method reliably detected the association of Cdk2 with its inhibitor, Kip1, whereas the nonspecific FRET efficiency between Cdk2 and a random peptide was negligible. We identified and sorted subpopulations of yeast cells showing interaction between the studied proteins.

CONCLUSIONS

We have described a straightforward novel calibration method to accurately quantitate FRET efficiency between GFP derivatives in flow cytometry.

Dynamic, yet structured: The cell membrane three decades after the Singer-Nicolson model

The fluid mosaic membrane model proved to be a very useful hypothesis in explaining many, but certainly not all, phenomena taking place in biological membranes. New experimental data show that the compartmentalization of membrane components can be as important for effective signal transduction as is the fluidity of the membrane. In this work, we pay tribute to the Singer-Nicolson model, which is near its 30th anniversary, honoring its basic features, "mosaicism" and "diffusion," which predict the interspersion of proteins and lipids and their ability to undergo dynamic rearrangement via Brownian motion. At the same time, modifications based on quantitative data are proposed, highlighting the often genetically predestined, yet flexible, multilevel structure implementing a vast complexity of cellular functions. This new "dynamically structured mosaic model" bears the following characteristics: emphasis is shifted from fluidity to mosaicism, which, in our interpretation, means nonrandom codistribution patterns of specific kinds of membrane proteins forming small-scale clusters at the molecular level and large-scale clusters (groups of clusters, islands) at the submicrometer level. The cohesive forces, which maintain these assemblies as principal elements of the membranes, originate from within a microdomain structure, where lipid-lipid, protein-protein, and protein-lipid interactions, as well as sub- and supramembrane (cytoskeletal, extracellular matrix, other cell) effectors, many of them genetically predestined, play equally important roles. The concept of fluidity in the original model now is interpreted as permissiveness of the architecture to continuous, dynamic restructuring of the molecular- and higher-level clusters according to the needs of the cell and as evoked by the environment.