A general method to quantify ligand-driven oligomerization from fluorescence-based images

Abstract

Here, we introduce fluorescence intensity fluctuation spectrometry for determining the identity, abundance and stability of protein oligomers. This approach was tested on monomers and oligomers of known sizes and was used to uncover the oligomeric states of the epidermal growth factor receptor and the secretin receptor in the presence and absence of their agonist ligands. This method is fast and is scalable for high-throughput screening of drugs targeting protein-protein interactions.

Fig. 1. Illustration of the data reduction process in two-dimensional Fluorescence Fluctuation (2D-FIF) Spectrometry using single-photon excitation.

a, Typical fluorescence image of Flp-In™ T-REx™ 293 cells (out of 8 images containing 44 cells) expressing a plasma membrane-targeted mEGFP construct (PM-1-mEGFP). The overlaid polygon (P34) indicates a region of interest (ROI) comprising a patch of the basolateral membrane of a cell. b, Software-generated image segmentation of the ROI in (a) using the moving-squares method (see Methods). Inset, fluorescence intensity histogram (circles) of a single segment, together with its Gaussian curve fit (solid line). The mean and width of the Gaussian are used to calculate the brightness (ε_eff) and concentration for each segment (see Methods). c-d, Normalized frequency distribution assembled from (c) 3,582 and (d) 4,185 ε_eff values obtained from 8 images comprising several cells expressing monomeric (PM-1-mEGFP) or tandem (PM-2-mEGFP) mEGFP constructs was fit to a sum (solid black curves) of Gaussians (dashed lines with various colors), to find the brightness of single mEGFP protomers, ${\epsilon }_{eff}^{proto}=\mathrm{13.04.}$ Gaussian peak positions were set to $n{\epsilon }_{eff}^{proto},$ where n is the number of protomers in an oligomer, and their widths were set equal to one another and determined from data fitting (13.4 a.u.). The ε_eff distribution for PM-1-mEGFP is primarily comprised of monomers (dashed, red Gaussian curve), with its peak positioned at ${\epsilon }_{eff}^{proto},$ while the PM-2-mEGFP spectrogram is mostly captured by a dimer model (dashed, yellow Gaussian curve), with its peak at $2{\epsilon }_{eff}^{proto}.$

Fig. 2. 2D-FIF results obtained from single-photon excitation of fixed cells expressing wild-type EGFR in the absence of ligand (-L) or after ten-minute treatment with 100 nM agonist ligand (+L).

a,d, Frequency of occurrence of effective brightness (ε_eff) for each protomer concentration using (a) 25,740 and (d) 6,812 total ROI segments to construct the distribution, extracted from 48 and 26 images, respectively (each of which contain several cells). Data were collected from at least two separate experiments. b,e, Cross sections through the surface plots in panels a,d, respectively, for different total concentration ranges; average concentration for each range (in protomer/μm²) is indicated above each plot. The vertical dashed colored lines indicate the peak positions for the brightness spectra of monomers, dimers, tetramers, etc., obtained from (or predicted based on) the simultaneous fitting of the PM1- and PM2-mEGFP spectrograms in Fig. 1, which were used as standards of brightness in the analysis. The ε_eff distribution for each concentration range was fitted with a sum of six Gaussians; the peak of each Gaussian was set to $n{\epsilon }_{eff}^{proto},$ where n is the number of protomers in a given oligomer (e.g., 1, 2, 4, etc.), with the ε_eff and standard deviation obtained from measurements on cells expressing PM-1-mEGFP or PM-2-mEGFP (Fig. 1). Only the Gaussian amplitudes (A_n) were adjusted in the process of data fitting in b,e which gave the fraction of protomers (c,f) for each oligomeric species, i.e., n_iA_i/∑_n nA_n. Number of Gaussians in each fit was chosen as discussed in the Methods section. c,f, Relative concentration of protomers in each oligomeric species vs. total protomer concentration, as derived by decomposing the spectrograms in column 2 into Gaussian components. Each data point and its error bar represent the mean ± standard deviation, respectively, of 1,500 different relative fraction values resulting from bootstrapping and refitting the original set of images as described in the Methods section.

Fig. 3. 2D-FIF results obtained from two-photon excitation of fixed cells expressing wild-type secretin receptor in the absence of agonist ligand (-L) or after ten- or thirty-minute treatment with 100 nm ligand (+L).

a,d,g, Surface plots of the frequency of occurrence of ε_eff for each concentration of protomers using (a) 13,420, (d) 15,309 and (g) 12,979 total segments to construct the distribution, extracted from 82, 80, and 82 images, respectively (each of which contain several cells). b,e,h, Stacks of cross sections through the surface plots in panels (a), (d), and (g), respectively, i.e., frequency of occurrence vs. effective brightness for different concentration ranges; average concentration for each range (in protomer/μm²) is indicated above each plot. The vertical dashed lines indicate the peak positions for the brightness spectra of monomers, dimers, etc., obtained from (or predicted by) the simultaneous fitting of the PM-1- and PM-2-mEGFP spectrograms used as standards of brightness (Supplementary Fig. 1). Number of Gaussians in each fit was chosen as described in the Methods section. c,f,i, Relative concentration of protomers within each oligomeric species vs. total concentration of protomers, as derived from unmixing of the curves in (b), (e), and (h), respectively, into different Gaussian components. Samples were as follows: wild-type secretin receptor treated with vehicle (-L) (first row of graphs), secretin (+L) for 10 minutes (second row of graphs), or secretin (+L) for 30 minutes (third row of graphs). Each data point and its error bar represent the mean ± standard deviation, respectively, of 1,500 different relative fraction values resulting from bootstrapping and refitting the original set of images as described in the Methods section. Entire data analysis process followed the steps described in the caption to Fig. 2.