Cells migrate by assembling and disassembling clusters of cellular proteins known as focal adhesions or focal complexes. Focal adhesions connect cells and their extra-cellular environment, thereby creating points for adhesion and signaling. Within these clusters, cytoplasmic and transmembrane proteins gather to form meeting points between the cell cytoskeleton and cell attachment points. Integrins are transmembrane proteins that anchor cells to the extra-cellular matrix (ECM). By creating the base upon which focal adhesions form, integrins provide a platform for signal transduction and cytoskeletal attachment inside cells (1). The formation of these clusters is a dynamic, spatially heterogeneous process that effects cell growth and movement via various signaling events (2). However, our understanding of integrin signaling and focal adhesion formation has been limited by our inability to capture the temporal and spatial complexity that is the very basis for integrin clustering and subsequent signaling events. We previously presented a mathematical model of integrin movement and clustering that captures different integrin clustering patterns depending on values chosen for certain model parameters (3). By manipulating model parameters to reflect integrin behavior, the model quantitatively relates collective integrin behavior, such as clustering, to specific integrin characteristics. Cells control the size, number, and temporal characteristics of integrin clusters and the subsequent cellular signals in part by controlling integrin behavior. The present work relates model predictions to actual cell behavior by measuring the focal adhesion size and dynamics in response to changes in integrin stimulation and related cell signaling. In this presentation we will show how clusters of focal adhesion proteins may be quantified and compared to model predictions, by using immunofluorescence imaging to measure the size and relative concentration of integrins and focal adhesion proteins. This approach facilitates the use of our modeling framework to understand how cell signaling and the extra-cellular environment relate to quantitative changes in integrin clustering. Data gathered under different adhesion conditions are interpreted with respect to the modeling framework. Integrin clustering and focal adhesion formation have been previously imaged, but to our knowledge have not been quantified (4,5,6). Previous studies implicate various integrin effectors in causing changes in the adhesion of endothelial cells. Endothelial cells provide a good model for studying integrin dynamics because several well-characterized integrin heterodimers (i.e. αvβ3, αvβ5, α1β1) act in conjunction with growth factors (i.e. VEGF, bFGF) to provide controlled adhesion (7) to several different ECM proteins (i.e. vitronection, fibronection) (8). Examples of integrin effectors that have been previously implicated in controlling integrin behavior and focal adhesion formation include metal ions (9,10), growth factors (11), ECM modifiers (12,13), and cytoskeletal effectors, such as nocodazole (14). This work utilizes the application of integrin effectors to obtain quantitative information on the impact of different effectors on the size distributions and dynamic characteristics of integrin clusters and focal adhesions. Human Umbilical Vein Endothelial Cells (HUVECs) were grown to confluency, suspended, and allowed to adhere under various conditions. Confocal microscopy was used to capture images of adherent HUVECs labeled for integrins and focal adhesion proteins. The two-dimensional images obtained were converted to RGB-scale data, which gives fluorescence intensity information across two spatial dimensions. This intensity information was obtained from multiple cells per treatment condition and used to characterize the focal adhesion behavior of a population of cells under different conditions. The intensity data was used to define areas of high fluorescence intensity that are indicative of the high concentration of proteins within focal adhesions. Areas of high concentration were considered focal adhesions, and were quantified based on their area, relative concentration, and formation dynamics. Quantitation of protein clusters from multiple cells under different conditions allows us to create large data sets that give insight into how protein cluster size distributions change over time and in response to cell signaling effectors. Overall, we show how a combined experimental and computational approach is used to characterize changes in integrin clustering and focal adhesion formation. Effectors of integrin activation and clustering were used to alter integrin clustering, and the effects on the focal adhesion size distributions were quantified using immunofluorescence. Experimental observations were compared with previously presented model predictions to explore the ability of the model to represent changes in signaling that relate to integrin behavior in HUVEC cells. These results illustrate how the proposed model is tailored to represent physical characteristics of focal adhesion formation as observed in a specific cell type.

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