Differential RhoA Dynamics in Migratory and Stationary Cells Measured by FRET and Automated Image Analysis John Paul Eichorst1., Shaoying Lu2., Jing Xu 2 , Yingxiao Wang1,2,3* 1 Center of Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 2 Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 3 Beckman Institute for Advanced Science and Technology, Department of Molecular and Integrative Physiology and Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America Abstract Genetically-encoded biosensors based on fluorescence resonance energy transfer (FRET) have been widely applied to study the spatiotemporal regulation of molecular activity in live cells with high resolution. The efficient and accurate quantification of the large amount of imaging data from these single-cell FRET measurements demands robust and automated data analysis. However, the nonlinear movement of live cells presents tremendous challenge for this task. Based on image registration of the single-cell movement, we have developed automated image analysis methods to track and quantify the FRET signals within user-defined subcellular regions. In addition, the subcellular pixels were classified according to their associated FRET signals and the dynamics of the clusters analyzed. The results revealed that the EGF-induced reduction of RhoA activity in migratory HeLa cells is significantly less than that in stationary cells. Furthermore, the RhoA activity is polarized in the migratory cells, with the gradient of polarity oriented toward the opposite direction of cell migration. In contrast, there is a lack of consistent preference in RhoA polarity among stationary cells. Therefore, our image analysis methods can provide powerful tools for high-throughput and systematic investigation of the spatiotemporal molecular activities in regulating functions of live cells with their shapes and positions continuously changing in time. Citation: Eichorst JP, Lu S, Xu J, Wang Y (2008) Differential RhoA Dynamics in Migratory and Stationary Cells Measured by FRET and Automated Image Analysis. PLoS ONE 3(12): e4082. doi:10.1371/journal.pone.0004082 Editor: Terry Means, Massachusetts General Hospital/Harvard University, United States of America Received November 6, 2008; Accepted November 26, 2008; Published December 30, 2008 Copyright: 2008 Eichorst et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported in part by the Bioengineering Department of the University of Illinois, Urbana-Champaign, the Wallace H. Coulter Foundation, Beckman Laser Institute Inc., NSF grant 08-00870, and NIH grant NS-063405. The funding agencies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: yingxiao@uiuc.edu . These authors contributed equally to this work. Introduction Cell migration plays important roles in embryonic development, tissue repair, cancer invasion and atherosclerosis [1]. It is a highly integrated process modulated by multiple signaling pathways, consisting of cytoskeleton extension and focal complex formation at the front, and focal adhesion disassembly and cytoskeleton contraction at the back [1]. The family of small Rho GTPases plays key roles in regulating actin cytoskeleton and hence migration [1–3]. These GTPases function as molecular switches in the cell by alternating between active GTP-bound and inactive GDP-bound states, mediated by guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs), respec- tively [1–4]. Among the prominent members of small Rho GTPases, such as RhoA, Rac1, and Cdc42 [2,3], RhoA was reported to mediate the assembly of contractile actomyosin filaments at the rear of migrating cells via one of its downstream effectors, ROCK [3–5]. Therefore, it has been suggested that RhoA activity may concentrate at the tail of migrating cells [3]. However, by using biosensors based on fluorescence resonant energy transfer (FRET) [6], a surprisingly high RhoA activity has recently been observed to present not only at the tail but also at the front of migrating cells [7,8]. These results suggest that RhoA may have different functions at different subcellular locations. FRET is a phenomenon of quantum mechanics. When two fluorescent proteins (FPs), a donor and an acceptor, are in proximity with favorable orientation, the excitation of donor FP can induce the emission from the acceptor [9]. FRET has enabled the development of a variety of biosensors capable of detecting molecular activities or protein-protein interactions in live cells [10,11]. Two FRET-based RhoA biosensors have been developed to visualize spatiotemporal dynamics of RhoA activities in live cells [7,12]. Matsuda’s group developed a RhoA biosensor (Raichu- RhoA) which contains RhoA (amino acid 1–189), a flexible linker, and the RhoA-binding (RBD) domain from its substrate molecule PKN, concatenated in between a cyan and a yellow fluorescent protein (CFP and YFP) [12]. The activation of RhoA can induce the intramolecular binding between RhoA and the RBD domain in the biosensor. The resulting conformational change can bring the CFP and YFP into close proximity and enhance FRET signals. The Raichu-RhoA biosensor has enabled the monitoring of RhoA activity during cell division, polarization and focal adhesion turnover in different cells [8,12–15]. Another FRET RhoA biosensor was independently developed, containing sequentially a full-length RhoA, CFP, a flexible linker, YFP, and the RBD domain of rhotekin [7]. This biosensor has also been successfully applied to study various cellular functions, including migration and polarity during chemotaxis [7,16,17]. PLoS ONE | www.plosone.org 1 December 2008 | Volume 3 | Issue 12 | e4082