Figure 7.

Effect of E₂ treatment on the conditional distribution of ERα versus β1-integrin. (a) Images from STORM of filopodia of MCF7 cells treated as indicated for 15 min and stained for ERα or β1-integrin. Insets in the top left corners show the same images taken with widefield microscopy. Inside the zoomed areas, arrows show regions of superposition of the two markers (yellow pixels). Blue squares outline representative areas of 500 × 500 pixels used for subsequent analyses. In the treated cell, arrow inside the blue square shows a region of dense clustering between ERα and β1-integrin. (b) Tables showing the IF calculated as described previously (Bermudez-Hernandez et al., 2017) for 10 representative frames of filopodia of MCF7 cells under control (top) or treated (bottom) conditions. R-G, red–green correlation; G-R, green–red correlation. Red, β1-integrin; green, ERα. (c) IF calculated for one treated cell (frame 7) and for two sub-ROIs of this frame, showing how this index changes between areas of different β1-integrin/ERα densities. Bars 2 µm. (d) Histogram for normalized frequencies of MD between β1-integrin and ERα in filopodia of MCF7 cells among all the analyzed frames for each condition. For each domain detected, centroids were identified, and MDs were calculated from each β1-integrin to its nearest ERα domain throughout each 500 × 500–pixel frame. Frequencies were normalized to the highest value. The graph shows a slight shift toward smaller MDs for treated cells. (e) Mean density covariance between ERα and β1-integrin domains. Each frame was divided into square ROI of different sizes (window lengths ranging from 130 nm [10 pixels] to 2,000 nm [150 pixels] in side length). For each ROI size, the densities of ERα and β1-integrin were obtained, and the correlation coefficient (C) between these densities was calculated for all datasets. The mean of C among all the control (black full circles) or treated (pink empty squares) cells was plotted as a function of the window side length. Light-blue crosses show the z score (defined by the difference between the mean of the control group (for each window) and the mean of the treated group, and further divided by the square root of the sum of the SD of each group normalized by n). Thus, because the z score expresses, in units of SD, the distance between the two distributions, one may safely conclude that here there is no significant difference in density covariance between control and treated cells. (f) Two examples of a Voronoi partition for control (left) or treated (right) cells using the centroids of the ERα domains to compute the transformation. Colors indicated in the color bar on the right represent the size of each Voronoi shell (in square nanometers). Black small dots indicate the location of the centroids for β1-integrin domains. Empty big circles indicate the centroids of ERα domains; red circles denote those ERα that have β1-integrins closer than 160 nm, and blue circles indicate those ERα that have β1-integrins further than 160 nm away on the mean. The examples in these panels reveal a clear difference in ERα–β1-integrin bunching between control and treated conditions. (g) Histogram of frequencies for the ADs from each ERα centroid to the β1-integrins inside its Voronoi shell among all the analyzed data for each condition (note the semilog axis for presentation purposes). The graph shows a shift toward smaller distances for treated cells. Green arrows indicate as an example a region of the plot where the difference between treated and control fields is almost double. The inset shows the histogram for frequencies of the areas of the Voronoi regions among all the analyzed fields for each condition, demonstrating that treated cells present also relatively smaller Voronoi shells. (h) Graph of the bunching index for each cell, which is the ratio between the number of shells (normalized) that contains mean ERα–β1-integrin distances smaller than a threshold value of 160 nm. We named it bunching index as it quantifies the proportion of ERα–β1-integrin complexes among all the domains localized. Control image 1 and E₂-treated image 4 are the ones represented in f. Inset shows the z score, which was calculated as the difference between each bunching index for the treated cell and the mean of the bunching indexes for the control group divided by the SD of the control group. Z score results demonstrate for six cells a significant difference (abs[z score] >1) in the bunching index between control and treated cells. In all plots, control cells are represented with black full circles and treated cells with pink empty squares. Treatments: ethanol (vehicle) or 10⁻⁸ M E₂.