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Review

High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling

by
Manel Dahmene
1,
Laura Quirion
2 and
Mélanie Laurin
1,3,*
1
Oncology Division, CHU de Québec–Université Laval Research Center, Québec, QC G1V 4G2, Canada
2
Montréal Clinical Research Institute (IRCM), Montréal, QC H2W 1R7, Canada
3
Université Laval Cancer Research Center, Québec, QC G1R 3S3, Canada
*
Author to whom correspondence should be addressed.
Cells 2020, 9(6), 1430; https://doi.org/10.3390/cells9061430
Submission received: 21 May 2020 / Revised: 5 June 2020 / Accepted: 7 June 2020 / Published: 9 June 2020
(This article belongs to the Special Issue Rho family of GTPases in Model Organisms and Systems)
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Abstract

:
Since their discovery, Rho GTPases have emerged as key regulators of cytoskeletal dynamics. In humans, there are 20 Rho GTPases and more than 150 regulators that belong to the RhoGEF, RhoGAP, and RhoGDI families. Throughout development, Rho GTPases choregraph a plethora of cellular processes essential for cellular migration, cell–cell junctions, and cell polarity assembly. Rho GTPases are also significant mediators of cancer cell invasion. Nevertheless, to date only a few molecules from these intricate signaling networks have been studied in depth, which has prevented appreciation for the full scope of Rho GTPases’ biological functions. Given the large complexity involved, system level studies are required to fully grasp the extent of their biological roles and regulation. Recently, several groups have tackled this challenge by using proteomic approaches to map the full repertoire of Rho GTPases and Rho regulators protein interactions. These studies have provided in-depth understanding of Rho regulators specificity and have contributed to expand Rho GTPases’ effector portfolio. Additionally, new roles for understudied family members were unraveled using high throughput screening strategies using cell culture models and mouse embryos. In this review, we highlight theses latest large-scale efforts, and we discuss the emerging opportunities that may lead to the next wave of discoveries.

1. Introduction

Rho GTPases, which are best known for their regulation of the actin cytoskeleton, play central roles in many physiological and pathological processes [1]. Due to their capacity to orchestrate the formation of tissue architecture, Rho GTPases have emerged as fundamental regulators of morphogenesis during embryonic development [2]. Their ability to coordinate cellular motility also makes them key mediators of tumor invasion. Moreover, since recent deep sequencing efforts have identified recurrent mutations in Rho GTPases in cancer, these molecules are rising as attractive therapeutic targets for the design of new cancer treatment regimens [3].
Rho GTPases are part of the Ras superfamily of small GTPases [4,5,6]. In humans, there are 20 Rho GTPases. Until now, a majority of their study has focused on signaling by the three prototypical members, RAC1, RHOA, and CDC42, which have long been appreciated for their respective contributions to lamellipodia, stress fiber, and filipodia formation [7]. While it is clear that the roles of Rho GTPase proteins extend far beyond cytoskeletal regulation, we still do not fully understand the complete spectrum of their biological functions. In fact, most of our understanding of Rho GTPases’ roles and regulation mechanisms has emerged from in vitro studies, during which single gene knockdown or overexpression of mutant forms were achieved in cell lines. As such, several family members remain understudied. Moreover, we still do not fully understand how different stimuli that converge on the same Rho GTPase trigger different responses in cells and the repertoire of Rho GTPases effectors remains incomplete. Given the complexity involved and the important crosstalk between Rho GTPases signaling networks, only large-scale global approaches are likely to mitigate for this current gap in knowledge. Recently, unbiased proteomic methodologies have contributed to significantly expand our understanding of Rho GTPases signaling interactions. Additionally, several groups have exploited high throughput screening approaches to identify new functional roles for some of the most understudied Rho GTPases network components. Here, we discuss the new insights provided by these system level approaches, and we highlight some of the remaining challenges the Rho GTPases field is facing.

2. Rho GTPases Cycle and Their Regulation

In mammals, there are 20 Rho GTPases divided into eight subfamilies (Figure 1). Classical Rho GTPases from the CDC42, RAC, RHO, and RHOF subfamilies act as molecular switches that cycle between an inactive GDP-bound and an active GTP-bound conformation. These Rho GTPases are largely regulated by the exchange of their GDP/GTP bound state. The four remaining subfamilies, namely the RHOU/RHOV, RND, RHOH, and RHOBTB subfamilies (Figure 1), are considered atypical because they either do not follow this canonical cycle of regulation or because they have additional structural and functional features that distinguish them from the classical Rho GTPases [8]. More specifically, RHOU and RHOV have unusual GDP/GTP cycling rate, and they are believed to be predominantly bound to GTP in cells due to their high intrinsic guanine nucleotide exchange activity when compared to CDC42 [9,10,11]. Intriguingly, RHOU has been shown to be highly regulated at the transcriptional level through the activation of several developmental pathways, such as WNT and NOTCH [11,12,13,14,15,16]. The RHOH and RND subfamilies do not cycle between GDP and GTP due to their lack of intrinsic GTPase activity and are therefore constitutively bound to GTP and active in cells [17,18]. The current view is that RHOH acts in cells to antagonize the action of the classical Rho GTPases [19,20,21] while RND proteins have been shown to have antagonistic effects with RHOA [17,22]. Lastly, RHOBTB GTPases are much larger than other Rho GTPases due to the presence of several additional domains, and their activation is thought to be partly regulated via protein–protein interactions that release their auto-inhibited conformation [23,24,25,26].
In addition to the 20 Rho GTPases found in human, RHOT1 and RHOT2, also known as MIRO-1 and 2 (for mitochondrial Rho), were identified during a search for proteins that contain a Rho consensus domain [27]. Due to this feature, these GTPases were initially classified as part of the atypical Rho GTPases subgroup [27,28]. RHOT1 and RHOT2 localize at the mitochondria where they regulate several aspects of mitochondria homeostasis and transport [28]. Due to their large sequence divergence, subsequent studies have since reclassified these two GTPases as a distinct subgroup in the Ras superfamily along with the Ras, Rho, Ran, Rab, and Arf GTPases [5].
Classical Rho GTPases are regulated by three families of proteins that entail the guanine nucleotide exchange factors (RhoGEFs), the GTPase-activating proteins (RhoGAPs), and the guanine nucleotide dissociation inhibitors (RhoGDIs) [29]. By binding to Rho GTPases, RhoGEFs favor GDP and Mg2+ dissociation. RhoGEFs then stabilize the Rho GTPases in nucleotide-free form that rapidly associate with GTP and dissociate from the RhoGEFs as a consequence of the relatively high concentration of GTP in cells when compared to GDP concentration (Figure 2) [30,31,32,33,34]. RhoGEFs are divided into two subfamilies, the Dbl-like and the DOCK subfamily, according to their respective GEF catalytic domain [30,35]. Upon GTP binding, Rho GTPases undergo a conformation change that enables their interaction with specific effectors, which promotes downstream signaling and ultimately triggers a biological output in cells (Figure 2) [36]. By interacting with a definite set of effectors and by bringing these effectors in the vicinity of the Rho GTPases they are activating, RhoGEFs play an important scaffolding function and orchestrate downstream signaling in response to an upstream cell stimulus (Figure 2) [35]. In contrast, RhoGAPs bind to active Rho GTPases and stimulate the Rho GTPases’ weak intrinsic GTPase activity. This promotes GTP hydrolysis and inactivate the Rho GTPases (Figure 2) [37]. Throughout this cycle, the majority of Rho GTPases are modified via the addition of isoprenoid lipids at the first cysteine residue of their C-terminal CAAX motif [38]. This posttranslational modification facilitates their association with membranes. Still, this lipid modification is not sufficient to determine the subcellular localization of Rho GTPases. This requires a second C-terminal signal in the Rho GTPases hypervariable region that allows targeting to specific membrane compartments [39,40]. Over the years, RhoGDIs have been generally recognized as Rho GTPases’ negative regulators. Notably, RhoGDIs allow the removal of Rho GTPases from membranes by binding to the GDP-bound form, which in a second step promote the transfer of the Rho GTPase’ C-terminal lipid extension from the lipid bilayer into the RhoGDI hydrophobic pocket [41,42,43,44,45,46,47]. This allows RhoGDIs to sequester Rho GTPases in the cytoplasm and to prevent their premature reactivation [48]. Yet, RhoGDIs have also been shown to stabilize the Rho GTPases proteins in the cytoplasm and to prevent their degradation via the proteasome [49]. While several studies have showed that RhoGDIs can bind active and inactive Rho GTPases in vitro [50,51,52,53,54,55,56], these regulators were found to be mainly in complex with the inactive GDP-bound Rho GTPases in cells [57]. By using membrane extraction assays and by visualizing Rho GTPases activity in living cells, Golding et al. showed that RhoGDIs are able to extract active GTP-bound Rho GTPases from membranes (Figure 2), a process proposed to be an important mechanism to allow spatiotemporal concentration of Rho GTPases in cells [58,59]. Finally, Rho GTPases can be regulated by their gene expression and they are also extensively modified via posttranslational modifications, which include phosphorylation, lipid addition, ubiquitination, and SUMOylation [60]. These modifications alter Rho GTPases localization, activity, and stability and, ultimately, fine-tune their signaling responses to a specific stimulus (Figure 2).
While Rho GTPases themselves are relatively simple molecules, the intricacy of Rho GTPases signaling networks is attributed to the large number of regulators and effectors that by far exceeds the number of Rho GTPases themselves. In mammals, we count 80 RhoGEFs, 69 RhoGAPs, 3 RhoGDIs, and a substantial number of effector proteins [29]. The complexity of these networks is further increased by the important crosstalk between them. Therefore, only large scale unbiased global approaches can help unravel all the signaling activities played by these networks.

3. Complex Rho GTPases signaling Hubs Are Revealed by proteomic Approaches

Rho GTPases are required to bind to their protein regulators and effectors to integrate upstream stimuli and relay downstream signals. Yet, the identification of Rho GTPases protein partners has always been challenging due to their strong association with membranes and cytoskeletal components. The emergence of large-scale proteomic approaches has paved the way toward a more global view of these wide protein networks (Table 1). In a first study, Paul et al. developed a quantitative GTPase affinity purification (qGAP) combined with mass spectrometry strategy to identify protein partners of CDC42, RAC1, RHOA, RHOB, RHOC, and RHOD [61]. Briefly, beads loaded with each recombinant Rho GTPases were loaded with GDP or GTPγ and used to pull-down proteins from differentially SILAC (stable isotope labeling by amino acids in cell culture)-labeled HeLa cell lysates. More than 1000 proteins mainly enriched in Rho GTPases effectors were identified using this strategy. While this approach was compatible with the use of animal tissue, the uncovered interactions occurred in the context of cellular lysates. Whether these remained relevant in living cells still had to be determined.
The more recent unbiased proximity biotinylation (BioID) mass spectrometry-based strategies allow investigators to identify protein networks occurring directly in living cells. The BioID method relies on the fusion of a promiscuous version of Escherichia coli biotin ligase (BirA*) to a protein of interest [62,63]. Upon expression of the fusion protein in cells in the presence of biotin, endogenous proteins that are proximal to the bait are biotinylated on available lysine residues and recovered through streptavidin pull-down. Importantly, this allows for the identification of transient interactions as well as those that can take place in insoluble cellular compartments. A BioID approach was used to systematically define the proximity interactome of Rho GTPases in their wild-type, nucleotide-free, and active forms to obtain a global view of these wide networks [64]. Impressively, close to 10,000 proximal interactions with Rho GTPases in two cell lines (HEK293 and HeLa cells) were revealed. By using the nucleotide-free form of RHOA, RHOG, RAC1, and CDC42, that can trap RhoGEFs in cells, and the active form of all Rho GTPases that interact with RhoGAPs, the fundamental question of Rho regulators specificity was addressed [64]. With the help of this clever trick, it was revealed that a large fraction of RhoGEFs are highly specific and that their activity is limited toward a few Rho GTPases (Figure 3a). This is the case notably for the RHOA-specific RhoGEFs, ARHGEF1, ARHGEF2, ARHGEF5, ARHGEF17, NGEF, ECT2, and AKAP13 (Figure 3b). Still, some RhoGEFs such as FARP1 can bind to the nucleotide-free version of the three prototypical Rho GTPases, RAC1, RHO, and CDC42 (Figure 3b). As for RhoGAPs, the use of Rho GTPases active form (always bound to GTP), confirmed their previously described promiscuity (Figure 3c) [65]. RhoGAPs have the ability to bind and inactivate a broad spectrum of Rho GTPases from the same or from different subfamilies (Figure 3d) [64]. Together, this reinforce the model in which RhoGEFs, by interacting simultaneously with a limited set of Rho GTPases and a specific set of effectors, become key players to relay a precise downstream cellular response in response to a stimulation.
Over the years, several studies using various fluorescent biosensors have beautifully highlighted the spatiotemporal regulation of Rho GTPases in cells [66,67,68,69,70,71]. Notably, researchers were able to visualize concentric zones of CDC42 and RHOA activation during wound healing of Xenopus oocytes [67]. Distinct patterns of RAC1/2 and CDC42 activation were also observed during phagocytosis [72]. Still, understanding how these highly specific patterns are generated remains a challenge. Rho GTPases regulators are likely to play an important role in this process. The visualization of the steady-state distribution of RhoGEFs and RhoGAPs in MDCK epithelial cells by confocal live-cell imaging revealed the presence of these proteins in virtually all cellular compartments, which would allow them to regulate Rho GTPases in all of these locations [73]. Among the 77 RhoGEFs and 66 RhoGAPs tested, a majority of these proteins was found enriched in specific cellular structures rather than broadly distributed in cells [73]. Intriguingly, structures that were not known to harbor Rho GTPases signaling, such as endomembrane, the Golgi, and mitochondria, only hosted RhoGAPs (Figure 4). One hypothesis, is that the RhoGAPs located in these locations display a housekeeping function, and they allow the inactivation of GTP-bound Rho GTPases that would have diffused away from their desired site of action [73].
During cell spreading, active and inactive zones of RAC have been described (Figure 4) [74]. At the core of this process, focal adhesions are multi-protein structures that link the actin cytoskeleton with the extracellular matrix. Rho GTPases regulation is essential to focal adhesion dynamics, and quite strikingly, 25% of Rho regulators can be found at these adhesion sites [73]. Importantly, by measuring RhoGEFs and RhoGAPs localization, RAC1-GEFs were shown to localize preferentially at nascent adhesions along the cell periphery, while RAC1-GAPs were shown to be located along more mature focal adhesions in the center of cells (Figure 4). This segregation of regulators contributes to establish active and inactive zones of Rho GTPase signaling [73]. Overall, these results support the idea that a large fraction of Rho GTPases’ spatiotemporal regulation is conveyed by the regulators themselves that delimit the diffusion of the Rho GTPases forms in cells (Figure 4).
Establishing the interactome of RhoGEFs and RhoGAPs has also revealed the existence of important homotypic interactions between these regulatory proteins [73]. Several interactions were confirmed between RhoGEFs and RhoGAPs, in between RhoGEFs, while fewer interactions were detected in between the RhoGAPs themselves. The association of regulatory proteins in complexes increases their combinatorial possibilities to control downstream signaling and enables a coordination of cellular responses through the crosstalk between Rho GTPases. This important interplay emphasizes the value of studying the Rho GTPases networks from a larger perspective. Altogether, all of these publicly available interactome data sets are a treasure trove of information likely to be highly valuable resources for the Rho GTPases community [64,73].

4. High throughput screening Strategies Uncover New Functions for Rho GTPases Network Components

Over the years, several screens have contributed to identify new genes involved in cell migration, and it is not surprising that several Rho GTPases were amongst the unearthed molecules [75,76,77,78,79]. More recently, several groups have relied on RNA interference (RNAi) screens to systematically test the requirement of Rho GTPases, RhoGEFs, RhoGAPs, and RhoGDIs in distinct biological processes. These approaches facilitated the discovery of new roles for understudied Rho GTPases family members (Table 1).
Rho GTPases signaling networks have emerged as key regulators of tumor invasion, and the use of unbiased high throughput screening approaches has largely contributed to delineate the role of individual network components during specific steps of the invasion process. Two studies by the group of Christopher Marshall pioneered this approach and contributed to highlighting that cancer cells rely on distinctive regulators to mediate different migration modes [80,81]. The crucial requirement of RhoGEFs during cellular invasion was emphasized when each of these Rho GTPases regulators was tested for its ability to regulate the amoeboid or the mesenchymal motility of melanoma cells [80,81]. Amoeboid movement is characterized by the blebbing of cells through the extracellular matrix without proteolysis. This migration mode requires high levels of actomyosin contractility, and it differs from mesenchymal movement, which is characterized by cells with an elongated morphology that assemble a leading edge [82]. Cancer cells are known to alternate between these modes as a way to adapt to their microenvironment [83]. In these screens, several RhoGEFs were shown to control melanoma cell migration. Still, only DOCK10 regulated ameboid features. In fact, silencing of DOCK10 led cells to switch migration mode and to instead rely on mesenchymal motility to invade a 3D environment [80]. In contrast, DOCK3 was shown to rather regulate cells amoeboid features and silencing of DOCK3 increased the proportion of melanoma cells that invade a 3D matrices in an amoeboid manner [81]. The ability of cancer cells to alternate modes of motility driven by different Rho GTPases as a way to adapt to their surrounding raises the important issue as to why MMP protease treatments may not be therapeutically viable in targeting cancer metastasis [84,85]. Altogether, these studies underscore the many challenges associated with the treatment of metastatic cancer patients.
Since, several groups have harnessed similar approaches. With the aim of isolating regulators of prostate cancer cell migration, Tajadura-Ortega et al., designed an RNAi screen targeting 202 genes among the Rho GTPases network components [21]. By using wound healing assays and threshold image analyses, they revealed that 25% of Rho GTPases signaling molecules contribute either positively or negatively to the migration of prostate cancer cells [21]. The large fraction of regulators revealed by this screen emphasizes the low level of functional redundancy amongst this family as well as the key role played by these factors. One unexpected hit from this screen was RHOH, whose role had been thought thus far to be restricted to hematopoietic cells [19,20]. Depletion of RHOH was shown to reduce the speed and the persistence of prostate cancer cells. Intriguingly, RHOH expression is not limited to prostate cancer cells, but this Rho GTPase is broadly expressed in other epithelial cancer cell lines, which suggest it might also contributes to cancer progression in these contexts [21]. In another study, Pascual-Vargas et al., rather focused on identifying RhoGEFs and RhoGAPs that orchestrate the morphology of highly metastatic breast cancer cells. For this, 142 genes among the Rho GTPases regulators were depleted using RNAi in one poorly and one highly metastatic breast cancer cell line, i.e., the MDA-MB231 and the LM2 cells, respectively. Following depletion, a total of 127 individual features characterizing the cellular shape and the activation of the YAP signaling pathway were measured for each condition. This large dataset was further probed and a list of top hits for each parameter was identified for more in-depth analyses [86]. Kang et al. rather focused on identifying RhoGAPs that contribute to epithelial to mesenchymal transition (EMT), a process often correlated with metastasis progression [87]. To do so, they used the MCF10A cell lines and revealed that 57 RhoGAPs were expressed in these cells. Using siRNA, they individually silenced the 57 RhoGAPs expressed and characterized in detail the MCF10A cell morphology. Using this approach, they revealed that depletion of 15 RhoGAPs led cells to adopt a spindle-like morphology in comparison to their baseline polygonal shape. Altogether, these screens underline that signaling specificity is often controlled by the Rho GTPases regulators themselves.
Screening approaches in mammalian cells were also useful to probe the function of Rho GTPases in physiological processes. Notably, Rho GTPases network components involved in thrombin-induced endothelial permeability in primary umbilical vein endothelial cells were identified using a siRNA screen that functionally tested 270 human Rho GTPases and Rho-associated genes [88]. A total of 15 top hits that modify the response to thrombin were identified [88]. Intriguingly, the depletion of the Rho GTPase RHOD led to the most potent disruption of endothelial barrier integrity, which revealed its important role in this process [88]. In another study, Zaritsky et al. rather designed a shRNA screen targeting 80 RhoGEFs in human bronchial epithelial cell monolayers to identify the ones that regulate the long-range collective migration in these cells [89]. Quite strikingly, 75 RhoGEFs were shown to be expressed in bronchial epithelial cells, which allows tremendous functional specification. A total of 10 RhoGEFs were revealed as specific regulators of the collective migration of these cells. In general, these in vitro screening approaches offered a powerful lens through which to examine the cellular response to specific stimuli and when looking at a predetermined cellular phenotype. While all of these approaches certainly revealed important functions of Rho GTPases network components, they all still rely on in vitro culture models and further validations will be required to see if these findings translate in vivo.
The development of in vivo models is in fact crucial since not all biological processes, such as the complex cellular rearrangements required for morphogenesis, can be recapitulated using in vitro cell culture models. Due to their ability to coordinate cytoskeletal dynamics, Rho GTPases have emerged as key regulators of morphogenesis [2]. Yet, only a fraction of Rho GTPases network components has been studied in regard to their ability to orchestrate embryonic development in mammals [90]. It is therefore important to use in vivo models to test the requirement of all Rho GTPases network components during morphogenesis. The mouse skin is an excellent system to tackle this challenge since the skin rely on complex cytoskeletal rearrangements for its formation [91,92,93]. Additionally, the development of an ultrasound-guided method of in utero lentiviral injection that allows the specific transduction of mouse skin progenitors has opened the door for high throughput studies that are otherwise impossible using conventional knockout strategies [94,95,96,97,98,99,100,101]. Intriguingly, majority of the Rho GTPases, RhoGEFs, RhoGAPs, and RhoGDIs are expressed in mouse skin progenitors during embryonic development suggesting the important contributions of these molecules to skin formation [97,102,103]. By building a lentiviral shRNA library targeting 166 genes from Rho GTPases network components, namely 20 Rho GTPases, 77 RhoGEFs, 66 RhoGAPs, and 3 RhoGDIs; and by taking advantage of the lentivirus delivery system that targets skin progenitors [94], we designed and validated a novel skin morphogenesis screen in live mouse embryos [97]. Our screen revealed that 42% of the genes targeted are essential for proper skin development. More specifically, seven genes were candidate regulators of epidermal differentiation, 26 genes acted as regulators of hair follicle development and 35 genes were candidate regulators of both processes. The validation of several candidates revealed that these were essential for a plethora of steps required for proper skin development. Notably, we revealed that the RhoGEF FGD2 is required for hair follicle specification and that hair follicle downgrowth is perturbed in the absence of the RhoGEF TRIO. Altogether, the variety and the large number of regulators uncovered using an in vivo RNAi morphogenesis screen emphasizes the power of this strategy as well as the low level of functional redundancy between Rho GTPases network components.
Among the top hits identified in the in vivo morphogenesis screen, the atypical Rho GTPases RHOU was revealed as a key regulator of the establishment of planar cell polarity (PCP) cues in the skin [97]. PCP signaling pathways have been shown to orchestrate hair follicle orientation in the developing skin [104] and defects in PCP organization and hair follicle orientation are often associated with perturbation of cellular contractility in epidermal cells [104,105,106,107,108]. In order to understand the molecular mechanism by which RHOU acts in the skin, the proximity interactome of this atypical Rho GTPase in primary mouse keratinocytes was determined. PAK2 was shown to be the most abundant partner in these cells. Overexpression of RHOU in keratinocytes triggers PAK1/2 activation, which inversely correlated with the phosphorylation of myosin light chain 2. Altogether, the proteomic analyses revealed that RHOU interacts with proteins that shuttle between focal adhesions and cell–cell junctions. By regulating the assembly of these structures, RHOU is required to generate a prototypical epidermal shape in skin progenitors that is required for PCP establishment. Additionally, RHOU acts to restrict hair follicle downgrowth by maintaining epidermal integrity; a similar mechanism is also utilized in the foregut endoderm to restrict the formation of organ primordia [14]. Our findings underscore the advantages of combining large-scale screening and proteomic studies to simultaneously gain insights into the functional and molecular mechanism of top screen hits.

5. Discussion

Recent interactome approaches have provided us with a clearer picture of the intricate signaling hubs that assemble around Rho GTPases. Still, our understanding of these modules’ dynamics is far from being reached. In particular, it remains to be determined how the Rho GTPases interactome is reshuffled when cells integrate various stimuli and when they are surrounded by different micro-environments. Notably, Rho GTPases have been shown to be highly post-translationally modified via ubiquitination and phosphorylation [60]. These modifications are likely potent ways to dynamically remodel their interactome. Moreover, the extent of the crosstalk between Rho GTPases signaling hubs is not fully understood. Only global network analyses following cellular treatments will resolve these issues. These questions will also certainly benefit from new enzyme-catalyzed proximity labeling methods such as miniTurbo, TurboID, and APEX, which allow the identification of quick temporal changes in protein networks subsequent to cellular stimulations [109,110,111]. Inversely, these approaches could be taken advantage of to elucidate the signals required to activate specific pathways. The recent interactome studies have also proved useful in effector landscape definition, and they have contributed to significatively increasing the size of Rho GTPases’ effector repertoire. One important aspect to keep in mind is that all of the proximity labelling approaches allow the identification of proteins that are present in a define perimeter of the protein bait in cells. Therefore, significant non-direct interactions are also revealed by these strategies. Still, by digging into the uncharted datasets, the list of cellular functions regulated by Rho GTPases networks is likely to expand greatly in the near future.
A critical aspect exposed by interactome approaches is the necessity of generating physiological models to study Rho GTPases’ functions. Remarkably, Bagci et al. revealed that only 33% of the Rho GTPases proximity interactions were shared between HEK293 and HeLa cells lines, which highlights that cellular context matters deeply [64]. Since not all biological processes can be recapitulated in vitro, we might still be severely underestimating the biological functions played by these proteins. Therefore, it is instrumental to develop high throughput methods that are compatible with physiological and disease in vivo models. Notably, organoid models have the potential to form a bridge between in vitro and in vivo studies and would allow to get a handle on physiological relevance. Still, even if siRNA and shRNA screens were to move to organoids or in vivo models, these types of screens would continue to have limitations. Indeed, while false positive hits can be reduced in these screens by using multiple siRNAs or shRNAs that target the same gene, false negative hits attributed to a failure to properly knockdown a target of interest will remain an issue. Therefore, full knockout approaches will always have their relevance in follow up studies to investigate biological functions of genes.
Finally, it is becoming clear that Rho GTPases signaling plays a crucial role during tumor progression and that signaling by Rho GTPases is perturbed by a wide range of mechanisms in cancer [3]. One indirect way by which Rho GTPases signaling is disrupted is through their regulators, the RhoGEFs and RhoGAPs [3,112]. Mutations of these regulators as well as changes in their expression levels have been shown to either promote or suppress tumor progression and growth [3,112,113]. Overall, these perturbations are likely to affect Rho GTPases’ interactome. The expression of the Rho GTPases RAC1, RHOA, and CDC42 is also altered in several cancer types [75,114,115,116,117,118,119,120,121,122,123,124,125,126]. The recent efforts in next-generation sequencing have revealed that Rho GTPases are mutated in a variety of cancers, and recurrent mutations in RAC1 and RHOA have been identified [3,127,128,129,130,131,132,133,134,135]. Intriguingly, several mutations identified in RAC1, namely RAC1P29S, RAC1N92I, and RAC1C157Y, create a fast cycling Rho GTPase with an enhanced exchange capacity for GDP and GTP [128,129]. While these mutations are thought to enhance RAC1 interaction with its effectors, it would be worth investigating if some de novo interactions are created and if some are lost. Similarly, the various mutations identified in RHOA in cancer cells are likely to perturb its interactome [136]. Altogether, gaining a broader picture of these changes could clarify how these mutated Rho GTPases contribute to tumor progression, and ultimately, this could lead to new therapeutic opportunities.

Author Contributions

Writing—original draft preparation, M.D., L.Q., M.L.; Writing—review and editing, M.L. All authors have read and agreed to the published version of the manuscript.

Funding

Mélanie Laurin is the recipient of a Scholarship for the Next Generation of Scientists from the Cancer Research Society and a NSERC Discovery Grant. Laura Quirion is supported by a Molecular and Cellular Medicine Option scholarship provided by the IRCM Foundation.

Acknowledgments

We would like to thank Sanjeethan Baksh, Stephanie Ellis, and Jean-François Côté for feedback on this manuscript.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Heasman, S.J.; Ridley, A.J. Mammalian Rho GTPases: New insights into their functions from in vivo studies. Nat. Rev. Mol. Cell Biol. 2008, 9, 690–701. [Google Scholar] [CrossRef]
  2. Van Aelst, L.; Symons, M. Role of Rho family GTPases in epithelial morphogenesis. Genes Dev. 2002, 16, 1032–1054. [Google Scholar] [CrossRef] [Green Version]
  3. Porter, A.P.; Papaioannou, A.; Malliri, A. Deregulation of Rho GTPases in cancer. Small GTPases 2016, 7, 123–138. [Google Scholar] [CrossRef]
  4. Wennerberg, K.; Rossman, K.L.; Der, C.J. The Ras superfamily at a glance. J. Cell Sci. 2005, 118, 843–846. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Rojas, A.M.; Fuentes, G.; Rausell, A.; Valencia, A. The Ras protein superfamily: Evolutionary tree and role of conserved amino acids. J. Cell Biol. 2012, 196, 189–201. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Goitre, L.; Trapani, E.; Trabalzini, L.; Retta, S.F. The ras superfamily of small GTPases: The unlocked secrets. Methods Mol. Biol. 2014, 1120, 1–18. [Google Scholar] [PubMed]
  7. Tapon, N.; Hall, A. Rho, Rac and Cdc42 GTPases regulate the organization of the actin cytoskeleton. Curr. Opin. Cell Biol. 1997, 9, 86–92. [Google Scholar] [CrossRef]
  8. Aspenström, P.; Ruusala, A.; Pacholsky, D. Taking Rho GTPases to the next level: The cellular functions of atypical Rho GTPases. Exp. Cell Res. 2007, 313, 3673–3679. [Google Scholar] [CrossRef] [PubMed]
  9. Saras, J.; Wollberg, P.; Aspenström, P. Wrch1 is a GTPase-deficient Cdc42-like protein with unusual binding characteristics and cellular effects. Exp. Cell Res. 2004, 299, 356–369. [Google Scholar] [CrossRef]
  10. Shutes, A.; Berzat, A.C.; Cox, A.D.; Der, C.J. Atypical Mechanism of Regulation of the Wrch-1 Rho Family Small GTPase. Curr. Boil. 2004, 14, 2052–2056. [Google Scholar] [CrossRef] [Green Version]
  11. Hodge, R.G.; Ridley, A.J. Regulation and functions of RhoU and RhoV. Small GTPases 2017, 11, 8–15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Schiavone, D.; Dewilde, S.; Vallania, F.; Turkson, J.; Di Cunto, F.; Poli, V. The RhoU/Wrch1 Rho GTPase gene is a common transcriptional target of both the gp130/STAT3 and Wnt-1 pathways. Biochem. J. 2009, 421, 283–292. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Na, J.; Shin, J.Y.; Jeong, H.; Lee, J.Y.; Kim, B.J.; Kim, W.S.; Yune, T.; Ju, B.-G. JMJD3 and NF-κB-dependent activation of Notch1 gene is required for keratinocyte migration during skin wound healing. Sci. Rep. 2017, 7, 6494. [Google Scholar] [CrossRef] [Green Version]
  14. Loebel, D.A.F.; Studdert, J.B.; Power, M.; Radziewic, T.; Jones, V.; Coultas, L.; Jackson, Y.; Rao, R.S.; Steiner, K.; Fossat, N.; et al. Rhou maintains the epithelial architecture and facilitates differentiation of the foregut endoderm. Development 2011, 138, 4511–4522. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Dickover, M.; Hegarty, J.M.; Ly, K.; López, D.; Yang, H.; Zhang, R.; Tedeschi, N.; Hsiai, T.K.; Chi, N.C. The atypical Rho GTPase, RhoU, regulates cell-adhesion molecules during cardiac morphogenesis. Dev. Boil. 2014, 389, 182–191. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Tao, W.; Pennica, D.; Xu, L.; Kalejta, R.F.; Levine, A.J. Wrch-1, a novel member of the Rho gene family that is regulated by Wnt-1. Genome Res. 2001, 15, 1796–1807. [Google Scholar] [CrossRef] [Green Version]
  17. Chardin, P. Function and regulation of Rnd proteins. Nat. Rev. Mol. Cell Boil. 2006, 7, 54–62. [Google Scholar] [CrossRef]
  18. Fueller, F.; Kubatzky, K.F. The small GTPase RhoH is an atypical regulator of haematopoietic cells. Cell Commun. Signal. 2008, 6, 6. [Google Scholar] [CrossRef] [Green Version]
  19. Li, X.; Bu, X.; Lu, B.; Avraham, H.; Flavell, R.A.; Lim, B. The Hematopoiesis-Specific GTP-Binding Protein RhoH Is GTPase Deficient and Modulates Activities of Other Rho GTPases by an Inhibitory Function. Mol. Cell. Boil. 2002, 22, 1158–1171. [Google Scholar] [CrossRef] [Green Version]
  20. Gu, Y.; Jasti, A.C.; Jansen, M.; Siefring, J.E. RhoH, a hematopoietic-specific Rho GTPase, regulates proliferation, survival, migration, and engraftment of hematopoietic progenitor cells. Blood 2005, 105, 1467–1475. [Google Scholar] [CrossRef] [Green Version]
  21. Tajadura-Ortega, V.; Garg, R.; Allen, R.; Owczarek, C.; Bright, M.D.; Kean, S.; Mohd-Noor, A.; Grigoriadis, A.; Elston, T.C.; Hahn, K.M.; et al. An RNAi screen of Rho signalling networks identifies RhoH as a regulator of Rac1 in prostate cancer cell migration. BMC Boil. 2018, 16, 29. [Google Scholar] [CrossRef] [PubMed]
  22. Wennerberg, K.; Forget, M.-A.; Ellerbroek, S.M.; Arthur, W.T.; Burridge, K.; Settleman, J.; Der, C.J.; Hansen, S.H. Rnd Proteins Function as RhoA Antagonists by Activating p190 RhoGAP. Curr. Boil. 2003, 13, 1106–1115. [Google Scholar] [CrossRef] [Green Version]
  23. Ramos, S.; Khademi, F.; Somesh, B.P.; Rivero, F. Genomic organization and expression profile of the small GTPases of the RhoBTB family in human and mouse. Gene 2002, 298, 147–157. [Google Scholar] [CrossRef]
  24. Berthold, J.; Schenková, K.; Ramos, S.; Miura, Y.; Furukawa, M.; Aspenström, P.; Rivero, F. Characterization of RhoBTB-dependent Cul3 ubiquitin ligase complexes—Evidence for an autoregulatory mechanism. Exp. Cell Res. 2008, 314, 3453–3465. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Manjarrez, J.R.; Sun, L.; Prince, T.; Matts, R.L. Hsp90-Dependent Assembly of the DBC2/RhoBTB2-Cullin3 E3-Ligase Complex. PLoS ONE 2014, 9, e90054. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Ji, W.; Rivero, F. Atypical Rho GTPases of the RhoBTB Subfamily: Roles in Vesicle Trafficking and Tumorigenesis. Cells 2016, 5, 28. [Google Scholar] [CrossRef] [Green Version]
  27. Fransson, A.; Ruusala, A.; Aspenström, P. Atypical Rho GTPases Have Roles in Mitochondrial Homeostasis and Apoptosis. J. Boil. Chem. 2002, 278, 6495–6502. [Google Scholar] [CrossRef] [Green Version]
  28. Tang, B.L. MIRO GTPases in Mitochondrial Transport, Homeostasis and Pathology. Cells 2015, 5, 1. [Google Scholar] [CrossRef]
  29. Cherfils, J.; Zeghouf, M. Regulation of Small GTPases by GEFs, GAPs, and GDIs. Physiol. Rev. 2013, 93, 269–309. [Google Scholar] [CrossRef] [Green Version]
  30. Laurin, M.; Coté, J.-F. Insights into the biological functions of Dock family guanine nucleotide exchange factors. Genes Dev. 2014, 28, 533–547. [Google Scholar] [CrossRef] [Green Version]
  31. Fort, P.; Blangy, A. The Evolutionary Landscape of Dbl-Like RhoGEF Families: Adapting Eukaryotic Cells to Environmental Signals. Genome Boil. Evol. 2017, 9, 1471–1486. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Yang, J.; Zhang, Z.; Roe, S.M.; Marshall, C.J.; Barford, D. Activation of Rho GTPases by DOCK Exchange Factors Is Mediated by a Nucleotide Sensor. Science 2009, 325, 1398–1402. [Google Scholar] [CrossRef] [PubMed]
  33. Rossman, K.L.; Der, C.J.; Sondek, J. GEF means go: Turning on RHO GTPases with guanine nucleotide-exchange factors. Nat. Rev. Mol. Cell Boil. 2005, 6, 167–180. [Google Scholar] [CrossRef] [PubMed]
  34. Worthylake, D.K.; Rossman, K.L.; Sondek, J. Crystal structure of Rac1 in complex with the guanine nucleotide exchange region of Tiam1. Nature 2000, 408, 682–688. [Google Scholar] [CrossRef] [PubMed]
  35. Cook, D.R.; Rossman, K.L.; Der, C.J. Rho guanine nucleotide exchange factors: Regulators of Rho GTPase activity in development and disease. Oncogene 2013, 33, 4021–4035. [Google Scholar] [CrossRef] [Green Version]
  36. Vetter, I.R.; Wittinghofer, A. The Guanine Nucleotide-Binding Switch in Three Dimensions. Science 2001, 294, 1299–1304. [Google Scholar] [CrossRef] [Green Version]
  37. Tcherkezian, J.; Lamarche-Vane, N. Current knowledge of the large RhoGAP family of proteins. Boil. Cell 2007, 99, 67–86. [Google Scholar] [CrossRef]
  38. Wennerberg, K.; Der, C.J. Rho-family GTPases: It’s not only Rac and Rho (and I like it). J. Cell Sci. 2004, 117, 1301–1312. [Google Scholar] [CrossRef] [Green Version]
  39. Michaelson, D.; Silletti, J.; Murphy, G.; D’Eustachio, P.; Rush, M.; Philips, M.R. Differential Localization of Rho Gtpases in Live Cells. J. Cell Boil. 2001, 152, 111–126. [Google Scholar] [CrossRef] [Green Version]
  40. Mitin, N.; Roberts, P.J.; Chenette, E.; Der, C.J. Posttranslational Lipid Modification of Rho Family Small GTPases. Adv. Struct. Saf. Stud. 2011, 827, 87–95. [Google Scholar] [CrossRef]
  41. DerMardirossian, C.; Bokoch, G.M. GDIs: Central regulatory molecules in Rho GTPase activation. Trends Cell Boil. 2005, 15, 356–363. [Google Scholar] [CrossRef] [PubMed]
  42. Hoffman, G.R.; Nassar, N.; Cerione, R.A. Structure of the Rho Family GTP-Binding Protein Cdc42 in Complex with the Multifunctional Regulator RhoGDI. Cell 2000, 100, 345–356. [Google Scholar] [CrossRef] [Green Version]
  43. Longenecker, K.; Read, P.; Derewenda, U.; Dauter, Z.; Liu, X.; Garrard, S.; Walker, L.; Somlyo, A.V.; Nakamoto, R.K.; Somlyo, A.P.; et al. How RhoGDI binds Rho. Acta Crystallogr. Sect. D Boil. Crystallogr. 1999, 55, 1503–1515. [Google Scholar] [CrossRef] [Green Version]
  44. Grizot, S.; Fauré, J.; Fieschi, F.; Vignais, P.V.; Dagher, M.-C.; Pebay-Peyroula, E. Crystal Structure of the Rac1−RhoGDI Complex Involved in NADPH Oxidase Activation. Biochemistry 2001, 40, 10007–10013. [Google Scholar] [CrossRef] [PubMed]
  45. Scheffzek, K.; Stephan, I.; Jensen, O.N.; Illenberger, D.; Gierschik, P. The Rac-RhoGDI complex and the structural basis for the regulation of Rho proteins by RhoGDI. Nat. Genet. 2000, 7, 122–126. [Google Scholar] [CrossRef]
  46. Gosser, Y.Q.; Nomanbhoy, T.K.; Aghazadeh, B.; Manor, D.; Combs, C.; Cerione, R.A.; Rosen, M.K. C-terminal binding domain of Rho GDP-dissociation inhibitor directs N-terminal inhibitory peptide to GTPases. Nature 1997, 387, 814–819. [Google Scholar] [CrossRef]
  47. Keep, N.H.; Barnes, M.; Barsukov, I.; Badii, R.; Lian, L.-Y.; Segal, A.W.; Moody, P.C.E.; Roberts, G. A modulator of rho family G proteins, rhoGDI, binds these G proteins via an immunoglobulin-like domain and a flexible N-terminal arm. Structure 1997, 5, 623–633. [Google Scholar] [CrossRef] [Green Version]
  48. Garcia-Mata, R.; Boulter, E.; Burridge, K. The ‘invisible hand’: Regulation of RHO GTPases by RHOGDIs. Nat. Rev. Mol. Cell Boil. 2011, 12, 493–504. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Boulter, E.; Garcia-Mata, R.; Guilluy, C.; Dubash, A.; Rossi, G.; Brennwald, P.J.; Burridge, K. Regulation of Rho GTPase crosstalk, degradation and activity by RhoGDI1. Nature 2010, 12, 477–483. [Google Scholar] [CrossRef] [Green Version]
  50. Hancock, J.F.; Hall, A. A novel role for RhoGDI as an inhibitor of GAP proteins. EMBO J. 1993, 12, 1915–1921. [Google Scholar] [CrossRef]
  51. Hart, M.; Maru, Y.; Leonard, D.; Witte, O.; Evans, T.; Cerione, R. A GDP dissociation inhibitor that serves as a GTPase inhibitor for the Ras-like protein CDC42Hs. Science 1992, 258, 812–815. [Google Scholar] [CrossRef] [PubMed]
  52. Nomanbhoy, T.K.; Cerione, R.A. Characterization of the Interaction between RhoGDI and Cdc42Hs Using Fluorescence Spectroscopy. J. Boil. Chem. 1996, 271, 10004–10009. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Tnimov, Z.; Guo, Z.; Gambin, Y.; Nguyen, U.T.T.; Wu, Y.; Abankwa, D.; Stigter, A.; Collins, B.M.; Waldmann, H.; Goody, R.S.; et al. Quantitative Analysis of Prenylated RhoA Interaction with Its Chaperone, RhoGDI*. J. Boil. Chem. 2012, 287, 26549–26562. [Google Scholar] [CrossRef] [Green Version]
  54. DerMardirossian, C.; Schnelzer, A.; Bokoch, G.M. Phosphorylation of RhoGDI by Pak1 Mediates Dissociation of Rac GTPase. Mol. Cell 2004, 15, 117–127. [Google Scholar] [CrossRef] [PubMed]
  55. Sasaki, T.; Kato, M.; Takai, Y. Consequences of weak interaction of rho GDI with the GTP-bound forms of rho p21 and rac p21. J. Boil. Chem. 1993, 268, 23959–23963. [Google Scholar]
  56. Chuang, T.H.; Xu, X.; Knaus, U.G.; Hart, M.J.; Bokoch, G.M. GDP dissociation inhibitor prevents intrinsic and GTPase activating protein-stimulated GTP hydrolysis by the Rac GTP-binding protein. J. Boil. Chem. 1993, 268, 775–778. [Google Scholar]
  57. Abo, A.; Webb, M.; Grogan, A.; Segal, A.W. Activation of NADPH oxidase involves the dissociation of p21rac from its inhibitory GDP/GTP exchange protein (rhoGDI) followed by its translocation to the plasma membrane. Biochem. J. 1994, 298, 585–591. [Google Scholar] [CrossRef] [Green Version]
  58. Perry, J.A.; Maddox, A.S. Uncovering the secret life of Rho GTPases. eLife 2019, 8, e53276. [Google Scholar] [CrossRef]
  59. Golding, A.E.; Visco, I.; Bieling, P.; Bement, W.M. Extraction of active RhoGTPases by RhoGDI regulates spatiotemporal patterning of RhoGTPases. eLife 2019, 8, e50471. [Google Scholar] [CrossRef]
  60. Hodge, R.G.; Ridley, A.J. Regulating Rho GTPases and their regulators. Nat. Rev. Mol. Cell Boil. 2016, 17, 496–510. [Google Scholar] [CrossRef] [PubMed]
  61. Paul, F.; Zauber, H.; Von Berg, L.; Rocks, O.; Daumke, O.; Selbach, M. Quantitative GTPase Affinity Purification Identifies Rho Family Protein Interaction Partners. Mol. Cell. Proteom. 2016, 16, 73–85. [Google Scholar] [CrossRef] [Green Version]
  62. Roux, K.J.; Kim, D.I.; Raida, M.; Burke, B. A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J. Cell Boil. 2012, 196, 801–810. [Google Scholar] [CrossRef] [Green Version]
  63. Gingras, A.-C.; Abe, K.T.; Raught, B. Getting to know the neighborhood: Using proximity-dependent biotinylation to characterize protein complexes and map organelles. Curr. Opin. Chem. Boil. 2019, 48, 44–54. [Google Scholar] [CrossRef]
  64. Bagci, H.; Sriskandarajah, N.; Robert, A.; Boulais, J.; Elkholi, I.E.; Tran, V.; Lin, Z.-Y.; Thibault, M.-P.; Dubé, N.; Faubert, D.; et al. Mapping the proximity interaction network of the Rho-family GTPases reveals signalling pathways and regulatory mechanisms. Nature 2019, 22, 120–134. [Google Scholar] [CrossRef]
  65. Amin, E.; Jaiswal, M.; Derewenda, U.; Reis, K.; Nouri, K.; Koessmeier, K.T.; Aspenström, P.; Somlyo, A.V.; Dvorsky, R.; Ahmadian, M.R. Deciphering the Molecular and Functional Basis of RHOGAP Family Proteins. J. Boil. Chem. 2016, 291, 20353–20371. [Google Scholar] [CrossRef] [Green Version]
  66. Pertz, O. Spatio-temporal Rho GTPase signaling - where are we now? J. Cell Sci. 2010, 123, 1841–1850. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Benink, H.A.; Bement, W.M. Concentric zones of active RhoA and Cdc42 around single cell wounds. J. Cell Boil. 2005, 168, 429–439. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Machacek, M.; Hodgson, L.; Welch, C.; Elliott, H.; Pertz, O.; Nalbant, P.; Abell, A.; Johnson, G.L.; Hahn, K.M.; Danuser, G. Coordination of Rho GTPase activities during cell protrusion. Nature 2009, 461, 99–103. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Bravo-Cordero, J.J.; Oser, M.; Chen, X.; Eddy, R.; Hodgson, L.; Condeelis, J. A Novel Spatiotemporal RhoC Activation Pathway Locally Regulates Cofilin Activity at Invadopodia. Curr. Boil. 2011, 21, 635–644. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Fritz, R.D.; Letzelter, M.; Reimann, A.; Martin, K.; Fusco, L.; Ritsma, L.; Ponsioen, B.; Fluri, E.; Schulte-Merker, S.; Van Rheenen, J.; et al. A Versatile Toolkit to Produce Sensitive FRET Biosensors to Visualize Signaling in Time and Space. Sci. Signal. 2013, 6, rs12. [Google Scholar] [CrossRef] [PubMed]
  71. Graessl, M.; Koch, J.; Calderon, A.; Kamps, D.; Banerjee, S.; Mazel, T.; Schulze, N.; Jungkurth, J.K.; Patwardhan, R.; Solouk, D.; et al. An excitable Rho GTPase signaling network generates dynamic subcellular contraction patterns. J. Cell Boil. 2017, 216, 4271–4285. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Hoppe, A.D.; Swanson, J.A. Cdc42, Rac1, and Rac2 Display Distinct Patterns of Activation during Phagocytosis. Mol. Boil. Cell 2004, 15, 3509–3519. [Google Scholar] [CrossRef] [PubMed]
  73. Müller, P.M.; Rademacher, J.; Bagshaw, R.D.; Wortmann, C.; Barth, C.; Van Unen, J.; Alp, K.M.; Giudice, G.; Eccles, R.L.; Heinrich, L.E.; et al. Systems analysis of RhoGEF and RhoGAP regulatory proteins reveals spatially organized RAC1 signalling from integrin adhesions. Nature 2020, 22, 498–511. [Google Scholar] [CrossRef] [PubMed]
  74. Martin, K.; Reimann, A.; Fritz, R.D.; Ryu, H.; Jeon, N.L.; Pertz, O. Spatio-temporal co-ordination of RhoA, Rac1 and Cdc42 activation during prototypical edge protrusion and retraction dynamics. Sci. Rep. 2016, 6, 21901. [Google Scholar] [CrossRef] [Green Version]
  75. Yang, J.; Fan, J.; Li, Y.; Li, F.; Chen, P.; Fan, Y.; Xia, X.; Wong, S.T. Genome-Wide RNAi Screening Identifies Genes Inhibiting the Migration of Glioblastoma Cells. PLoS ONE 2013, 8, e61915. [Google Scholar] [CrossRef] [Green Version]
  76. Rohn, J.L.; Sims, D.; Liu, T.; Fedorova, M.; Schöck, F.; Dopie, J.; Vartiainen, M.K.; Kiger, A.A.; Perrimon, N.; Baum, B. Comparative RNAi screening identifies a conserved core metazoan actinome by phenotype. J. Cell Boil. 2011, 194, 789–805. [Google Scholar] [CrossRef] [Green Version]
  77. Bai, S.W.; Herrera-Abreu, M.T.; Rohn, J.L.; Racine, V.; Tajadura-Ortega, V.; Suryavanshi, N.; Bechtel, S.; Wiemann, S.; Baum, B.; Ridley, A.J. Identification and characterization of a set of conserved and new regulators of cytoskeletal organization, cell morphology and migration. BMC Boil. 2011, 9, 54. [Google Scholar] [CrossRef] [Green Version]
  78. Smolen, G.A.; Zhang, J.; Zubrowski, M.J.; Edelman, E.J.; Luo, B.; Yu, M.; Ng, L.W.; Scherber, C.M.; Schott, B.J.; Ramaswamy, S.; et al. A genome-wide RNAi screen identifies multiple RSK-dependent regulators of cell migration. Genome Res. 2010, 24, 2654–2665. [Google Scholar] [CrossRef] [Green Version]
  79. Simpson, K.J.; Selfors, L.M.; Bui, J.; Reynolds, A.; Leake, D.; Khvorova, A.; Brugge, J.S. Identification of genes that regulate epithelial cell migration using an siRNA screening approach. Nature 2008, 10, 1027–1038. [Google Scholar] [CrossRef]
  80. Gadéa, G.; Sanz-Moreno, V.; Self, A.; Godi, A.; Marshall, C.J. DOCK10-Mediated Cdc42 Activation Is Necessary for Amoeboid Invasion of Melanoma Cells. Curr. Boil. 2008, 18, 1456–1465. [Google Scholar] [CrossRef] [Green Version]
  81. Sanz-Moreno, V.; Gadéa, G.; Ahn, J.; Paterson, H.; Marra, P.; Pinner, S.; Sahai, E.; Marshall, C.J. Rac Activation and Inactivation Control Plasticity of Tumor Cell Movement. Cell 2008, 135, 510–523. [Google Scholar] [CrossRef] [Green Version]
  82. Sahai, E.; Marshall, C.J. Differing modes of tumour cell invasion have distinct requirements for Rho/ROCK signalling and extracellular proteolysis. Nature 2003, 5, 711–719. [Google Scholar] [CrossRef]
  83. Friedl, P.; Wolf, K. Tumour-cell invasion and migration: Diversity and escape mechanisms. Nat. Rev. Cancer 2003, 3, 362–374. [Google Scholar] [CrossRef] [PubMed]
  84. Fingleton, B. MMPs as therapeutic targets-Still a viable option? In Seminars in Cell & Developmental Biology; Academic Press: Cambridge, MA, USA, 2008. [Google Scholar]
  85. Fields, G.B. The Rebirth of Matrix Metalloproteinase Inhibitors: Moving Beyond the Dogma. Cells 2019, 8, 984. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  86. Pascual-Vargas, P.; Cooper, S.; Sero, J.E.; Bousgouni, V.; Arias-Garcia, M.; Bakal, C. RNAi screens for Rho GTPase regulators of cell shape and YAP/TAZ localisation in triple negative breast cancer. Sci. Data 2017, 4, 170018. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Kang, N.; Matsui, T.S.; Liu, S.; Fujiwara, S.; Deguchi, S. Comprehensive analysis on the whole Rho-GAP family reveals that ARHGAP4 suppresses EMT in epithelial cells under negative regulation by Septin9. FASEB J. 2020. [Google Scholar] [CrossRef] [PubMed]
  88. Amado-Azevedo, J.; De Menezes, R.X.; Amerongen, G.P.V.N.; Van Hinsbergh, V.W.M.; Hordijk, P. A functional siRNA screen identifies RhoGTPase-associated genes involved in thrombin-induced endothelial permeability. PLoS ONE 2018, 13, e0201231. [Google Scholar] [CrossRef]
  89. Zaritsky, A.; Tseng, Y.-Y.; Rabadan, M.A.; Krishna, S.; Overholtzer, M.; Danuser, G.; Hall, A. Diverse roles of guanine nucleotide exchange factors in regulating collective cell migration. J. Cell Boil. 2017, 216, 1543–1556. [Google Scholar] [CrossRef] [Green Version]
  90. Duquette, P.M.; Lamarche-Vane, N. Rho GTPases in embryonic development. Small GTPases 2014, 5, 1–9. [Google Scholar] [CrossRef] [Green Version]
  91. Luxenburg, C.; Zaidel-Bar, R. From cell shape to cell fate via the cytoskeleton—Insights from the epidermis. Exp. Cell Res. 2019, 378, 232–237. [Google Scholar] [CrossRef]
  92. Niessen, M.T.; Iden, S.; Niessen, C.M. The in vivo function of mammalian cell and tissue polarity regulators—How to shape and maintain the epidermal barrier. J. Cell Sci. 2012, 125, 3501–3510. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Simpson, C.L.; Patel, D.M.; Green, K.J. Deconstructing the skin: Cytoarchitectural determinants of epidermal morphogenesis. Nat. Rev. Mol. Cell Boil. 2011, 12, 565–580. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Beronja, S.; Livshits, G.; Williams, S.E.; Fuchs, E. Rapid functional dissection of genetic networks via tissue-specific transduction and RNAi in mouse embryos. Nat. Med. 2010, 16, 821. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Schramek, D.; Sendoel, A.; Segal, J.P.; Beronja, S.; Heller, E.; Oristian, D.; Reva, B.; Fuchs, E. Direct in Vivo RNAi Screen Unveils Myosin IIa as a Tumor Suppressor of Squamous Cell Carcinomas. Science 2014, 343, 309–313. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. Loganathan, S.K.; Schleicher, K.; Malik, A.; Quevedo, R.; Langille, E.; Teng, K.; Oh, R.H.; Rathod, B.; Tsai, R.; Samavarchi-Tehrani, P.; et al. Rare driver mutations in head and neck squamous cell carcinomas converge on NOTCH signaling. Science 2020, 367, 1264–1269. [Google Scholar] [CrossRef]
  97. Laurin, M.; Gomez, N.C.; Levorse, J.; Sendoel, A.; Sribour, M.; Fuchs, E. An RNAi screen unravels the complexities of Rho GTPase networks in skin morphogenesis. eLife 2019, 8. [Google Scholar] [CrossRef]
  98. Sendoel, A.; Dunn, J.G.; Rodriguez, E.H.; Naik, S.; Gomez, N.C.; Hurwitz, B.; Levorse, J.; Dill, B.D.; Schramek, D.; Molina, H.; et al. Translation from unconventional 5′ start sites drives tumour initiation. Nature 2017, 541, 494–499. [Google Scholar] [CrossRef]
  99. Asare, A.; Levorse, J.; Fuchs, E. Coupling organelle inheritance with mitosis to balance growth and differentiation. Science 2017, 355, eaah4701. [Google Scholar] [CrossRef] [Green Version]
  100. Ge, Y.; Zhang, L.; Nikolova, M.; Reva, B.; Fuchs, E. Strand-specific in vivo screen of cancer-associated miRNAs unveils a role for miR-21∗ in SCC progression. Nature 2015, 18, 111–121. [Google Scholar] [CrossRef] [Green Version]
  101. Beronja, S.; Janki, P.; Heller, E.; Lien, W.-H.; Keyes, B.E.; Oshimori, N.; Fuchs, E. RNAi screens in mice identify physiological regulators of oncogenic growth. Nature 2013, 501, 185–190. [Google Scholar] [CrossRef] [Green Version]
  102. Sennett, R.; Wang, Z.; Rezza, A.; Grisanti, L.; Roitershtein, N.; Sicchio, C.; Mok, K.W.; Heitman, N.; Clavel, C.; Ma’Ayan, A.; et al. An Integrated Transcriptome Atlas of Embryonic Hair Follicle Progenitors, Their Niche, and the Developing Skin. Dev. Cell 2015, 34, 577–591. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Rezza, A.; Wang, Z.; Sennett, R.; Qiao, W.; Wang, N.; Heitman, N.; Mok, K.W.; Clavel, C.; Yi, R.; Zandstra, P.; et al. Signaling Networks among Stem Cell Precursors, Transit-Amplifying Progenitors, and their Niche in Developing Hair Follicles. Cell Rep. 2016, 14, 3001–3018. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  104. Devenport, D.; Fuchs, E. Planar polarization in embryonic epidermis orchestrates global asymmetric morphogenesis of hair follicles. Nature 2008, 10, 1257–1268. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Luxenburg, C.; Heller, E.; Pasolli, H.A.; Chai, S.; Nikolova, M.; Stokes, N.; Fuchs, E. Wdr1-mediated cell shape dynamics and cortical tension are essential for epidermal planar cell polarity. Nature 2015, 17, 592–604. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  106. Ahtiainen, L.; Lefebvre, S.; Lindfors, P.H.; Renvoisé, E.; Shirokova, V.; Vartiainen, M.K.; Thesleff, I.; Mikkola, M.L. Directional Cell Migration, but Not Proliferation, Drives Hair Placode Morphogenesis. Dev. Cell 2014, 28, 588–602. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  107. Le, H.; Ghatak, S.; Yeung, C.-Y.C.; Tellkamp, F.; Günschmann, C.; Dieterich, C.; Yeroslaviz, A.; Habermann, B.; Pombo, A.; Niessen, C.M.; et al. Mechanical regulation of transcription controls Polycomb-mediated gene silencing during lineage commitment. Nature 2016, 18, 864–875. [Google Scholar] [CrossRef]
  108. Aw, W.Y.; Heck, B.W.; Joyce, B.; Devenport, D. Transient Tissue-Scale Deformation Coordinates Alignment of Planar Cell Polarity Junctions in the Mammalian Skin. Curr. Boil. 2016, 26, 2090–2100. [Google Scholar] [CrossRef] [Green Version]
  109. Rhee, H.-W.; Zou, P.; Udeshi, N.D.; Martell, J.D.; Mootha, V.K.; Carr, S.A.; Ting, A.Y. Proteomic Mapping of Mitochondria in Living Cells via Spatially Restricted Enzymatic Tagging. Science 2013, 339, 1328–1331. [Google Scholar] [CrossRef] [Green Version]
  110. Branon, T.C.; Bosch, J.A.; Sanchez, A.D.; Udeshi, N.D.; Svinkina, T.; Carr, S.A.; Feldman, J.L.; Perrimon, N.; Ting, A.Y. Efficient proximity labeling in living cells and organisms with TurboID. Nat. Biotechnol. 2018, 36, 880–887. [Google Scholar] [CrossRef]
  111. Doerr, A. Proximity labeling with TurboID. Nat. Methods 2018, 15, 764. [Google Scholar] [CrossRef]
  112. Vigil, M.; Cherfils, J.; Rossman, K.L.; Der, C.J. Ras superfamily GEFs and GAPs: Validated and tractable targets for cancer therapy? Nat. Rev. Cancer 2010, 10, 842–857. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Barrio-Real, L.; Kazanietz, M.G. Rho GEFs and Cancer: Linking Gene Expression and Metastatic Dissemination. Sci. Signal. 2012, 5, pe43. [Google Scholar] [CrossRef] [PubMed]
  114. Fritz, G.; Brachetti, C.; Bahlmann, F.; Schmidt, M.; Kaina, B. Rho GTPases in human breast tumours: Expression and mutation analyses and correlation with clinical parameters. Br. J. Cancer 2002, 87, 635–644. [Google Scholar] [CrossRef] [PubMed]
  115. Liu, Y.; Wang, Y.; Zhang, Y.; Miao, Y.; Zhao, Y.; Zhang, P.-X.; Jiang, G.; Zhang, J.-Y.; Han, Y.; Lin, X.-Y.; et al. Abnormal expression of p120-catenin, E-cadherin, and small GTPases is significantly associated with malignant phenotype of human lung cancer. Lung Cancer 2009, 63, 375–382. [Google Scholar] [CrossRef]
  116. Arias-Romero, L.E.; Chernoff, J. Targeting Cdc42 in cancer. Expert Opin. Ther. Targets 2013, 17, 1263–1273. [Google Scholar] [CrossRef] [Green Version]
  117. Ji, J.; Feng, X.; Shi, M.; Cai, Q.; Yu, Y.; Zhu, Z.; Zhang, J. Rac1 is correlated with aggressiveness and a potential therapeutic target for gastric cancer. Int. J. Oncol. 2015, 46, 1343–1353. [Google Scholar] [CrossRef] [Green Version]
  118. Fritz, G.; Just, I.; Kaina, B. Rho GTPases are over-expressed in human tumors. Int. J. Cancer 1999, 81, 682–687. [Google Scholar] [CrossRef]
  119. Pan, Y.; Bi, F.; Liu, N.; Xue, Y.; Yao, X.; Zheng, Y.; Fan, D. Expression of seven main Rho family members in gastric carcinoma. Biochem. Biophys. Res. Commun. 2004, 315, 686–691. [Google Scholar] [CrossRef]
  120. Kamai, T.; Yamanishi, T.; Shirataki, H.; Takagi, K.; Asami, H.; Ito, Y.; Yoshida, K.-I. Overexpression of RhoA, Rac1, and Cdc42 GTPases Is Associated with Progression in Testicular Cancer. Clin. Cancer Res. 2004, 10, 4799–4805. [Google Scholar] [CrossRef] [Green Version]
  121. Mazieres, J.; Antonia, T.; Daste, G.; Muro-Cacho, C.; Berchery, D.; Tillement, V.; Pradines, A.; Sebti, S.; Favre, G. Loss of RhoB expression in human lung cancer progression. Clin. Cancer Res. 2004, 10, 2742–2750. [Google Scholar] [CrossRef] [Green Version]
  122. Engers, R.; Ziegler, S.; Mueller, M.; Walter, A.; Willers, R.; E Gabbert, H. Prognostic relevance of increased Rac GTPase expression in prostate carcinomas. Endocr. Relat. Cancer 2007, 14, 245–256. [Google Scholar] [CrossRef] [PubMed]
  123. Sato, N.; Fukui, T.; Taniguchi, T.; Yokoyama, T.; Kondo, M.; Nagasaka, T.; Goto, Y.; Gao, W.; Ueda, Y.; Yokoi, K.; et al. RhoB is frequently downregulated in non-small-cell lung cancer and resides in the 2p24 homozygous deletion region of a lung cancer cell line. Int. J. Cancer 2006, 120, 543–551. [Google Scholar] [CrossRef] [PubMed]
  124. Tucci, M.; Lucarini, G.; Brancorsini, D.; Zizzi, A.; Pugnaloni, A.; Giacchetti, A.; Ricotti, G.; Biagini, G. Involvement of E-cadherin, β-catenin, Cdc42 and CXCR4 in the progression and prognosis of cutaneous melanoma. Br. J. Dermatol. 2007, 157, 1212–1216. [Google Scholar] [CrossRef] [PubMed]
  125. Faried, A.; Faried, L.S.; Usman, N.; Kato, H.; Kuwano, H. Clinical and Prognostic Significance of RhoA and RhoC Gene Expression in Esophageal Squamous Cell Carcinoma. Ann. Surg. Oncol. 2007, 14, 3593–3601. [Google Scholar] [CrossRef]
  126. Del Pulgar, T.G.; Valdés-Mora, F.; Bandrés, E.; Pérez-Palacios, R.; Espina, C.; Cejas, P.; García-Cabezas, M.Á.; Nistal, M.; Casado, E.; González-Barón, M.; et al. Cdc42 is highly expressed in colorectal adenocarcinoma and downregulates ID4 through an epigenetic mechanism. Int. J. Oncol. 2008, 33, 185–193. [Google Scholar] [CrossRef]
  127. Krauthammer, M.; Kong, Y.; Ha, B.H.; Evans, P.; Bacchiocchi, A.; McCusker, J.P.; Cheng, E.; Davis, M.J.; Goh, G.; Choi, M.; et al. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nat. Genet. 2012, 44, 1006–1014. [Google Scholar] [CrossRef] [Green Version]
  128. Davis, M.J.; Ha, B.H.; Holman, E.; Halaban, R.; Schlessinger, J.; Boggon, T.J. RAC1P29S is a spontaneously activating cancer-associated GTPase. Proc. Natl. Acad. Sci. USA 2013, 110, 912–917. [Google Scholar] [CrossRef] [Green Version]
  129. Kawazu, M.; Ueno, T.; Kontani, K.; Ogita, Y.; Ando, M.; Fukumura, K.; Yamato, A.; Soda, M.; Takeuchi, K.; Miki, Y.; et al. Transforming mutations of RAC guanosine triphosphatases in human cancers. Proc. Natl. Acad. Sci. USA 2013, 110, 3029–3034. [Google Scholar] [CrossRef] [Green Version]
  130. Kakiuchi, M.; Nishizawa, T.; Ueda, H.; Gotoh, K.; Tanaka, A.; Hayashi, A.; Yamamoto, S.; Tatsuno, K.; Katoh, H.; Watanabe, Y.; et al. Recurrent gain-of-function mutations of RHOA in diffuse-type gastric carcinoma. Nat. Genet. 2014, 46, 583–587. [Google Scholar] [CrossRef]
  131. Manso, R.; Sánchez-Beato, M.; Monsalvo, S.; Gómez, S.; Cereceda, L.; Llamas, P.; Rojo, F.; Mollejo, M.; Menárguez, J.; Alves, J.; et al. The RHOA G17V gene mutation occurs frequently in peripheral T-cell lymphoma and is associated with a characteristic molecular signature. Blood 2014, 123, 2893–2894. [Google Scholar] [CrossRef] [Green Version]
  132. Mar, V.J.; Wong, S.Q.; Logan, A.; Nguyen, T.; Cebon, J.; Kelly, J.W.; Wolfe, R.; Dobrovic, A.; McLean, C.; McArthur, G. Clinical and pathological associations of the activatingRAC1P29S mutation in primary cutaneous melanoma. Pigment. Cell Melanoma Res. 2014, 27, 1117–1125. [Google Scholar] [CrossRef] [PubMed]
  133. Palomero, T.; Couronné, L.; Khiabanian, H.; Kim, M.-Y.; Ambesi-Impiombato, A.; Perez-Garcia, A.; Carpenter, Z.; Abate, F.; Allegretta, M.; Haydu, J.E.; et al. Recurrent mutations in epigenetic regulators, RHOA and FYN kinase in peripheral T cell lymphomas. Nat. Genet. 2014, 46, 166–170. [Google Scholar] [CrossRef] [PubMed]
  134. Yoo, H.Y.; Sung, M.; Lee, S.H.; Kim, S.; Lee, H.; Park, S.; Kim, S.C.; Lee, B.; Rho, K.; Lee, W.T.; et al. A recurrent inactivating mutation in RHOA GTPase in angioimmunoblastic T cell lymphoma. Nat. Genet. 2014, 46, 371–375. [Google Scholar] [CrossRef] [PubMed]
  135. Vu, H.L.; Rosenbaum, S.; Purwin, T.J.; Davies, M.A.; Aplin, A.E. RAC1 P29S regulates PD-L1 expression in melanoma. Pigment. Cell Melanoma Res. 2015, 28, 590–598. [Google Scholar] [CrossRef] [PubMed]
  136. Sahai, E.; Alberts, A.S.; Treisman, R. RhoA effector mutants reveal distinct effector pathways for cytoskeletal reorganization, SRF activation and transformation. EMBO J. 1998, 17, 1350–1361. [Google Scholar] [CrossRef] [Green Version]
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Figure 1. Rho GTPases classification in mammals. Rho GTPases are divided into eight subfamilies, namely the CDC42, RAC, RHO, RHOF, RHOBTB, RHOH, RHOU/RHOV, and RND subfamilies. These are further divided between classical and atypical Rho GTPases. Classical Rho GTPases cycle between an inactive GDP and an activate GTP-bound state while atypical Rho GTPases are mainly regulated through other mechanisms.
Figure 1. Rho GTPases classification in mammals. Rho GTPases are divided into eight subfamilies, namely the CDC42, RAC, RHO, RHOF, RHOBTB, RHOH, RHOU/RHOV, and RND subfamilies. These are further divided between classical and atypical Rho GTPases. Classical Rho GTPases cycle between an inactive GDP and an activate GTP-bound state while atypical Rho GTPases are mainly regulated through other mechanisms.
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Figure 2. The classical Rho GTPase cycle and its spatiotemporal regulation. RhoGEFs activate Rho GTPases by destabilizing Rho GTPase nucleotide and Mg2+ interaction and by promoting GTP loading, which is in excess in cells when compared to GDP. RhoGEFs also act as protein scaffolds by bringing appropriate effectors in close proximity to active Rho GTPases. Once active, Rho GTPases bind with their effectors and trigger biological effects in cells such as cell migration, cell adhesion, and cell polarity. RhoGAPs inactivate Rho GTPases by enhancing their weak intrinsic GTPase activity, which triggers the hydrolysis of GTP in GDP. RhoGDIs bind to Rho GTPases and promote the extraction of the Rho GTPases C-terminal lipid extension from the membrane which becomes ultimately hidden into the RhoGDIs hydrophobic pocket. RhoGDIs are known to sequester Rho GTPases in the cytosol and to prevent their interaction with other regulators. Rho GTPases are also heavily regulated through post-translational modifications, gene expression and their degradation.
Figure 2. The classical Rho GTPase cycle and its spatiotemporal regulation. RhoGEFs activate Rho GTPases by destabilizing Rho GTPase nucleotide and Mg2+ interaction and by promoting GTP loading, which is in excess in cells when compared to GDP. RhoGEFs also act as protein scaffolds by bringing appropriate effectors in close proximity to active Rho GTPases. Once active, Rho GTPases bind with their effectors and trigger biological effects in cells such as cell migration, cell adhesion, and cell polarity. RhoGAPs inactivate Rho GTPases by enhancing their weak intrinsic GTPase activity, which triggers the hydrolysis of GTP in GDP. RhoGDIs bind to Rho GTPases and promote the extraction of the Rho GTPases C-terminal lipid extension from the membrane which becomes ultimately hidden into the RhoGDIs hydrophobic pocket. RhoGDIs are known to sequester Rho GTPases in the cytosol and to prevent their interaction with other regulators. Rho GTPases are also heavily regulated through post-translational modifications, gene expression and their degradation.
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Figure 3. Mapping of Rho GTPases regulators specificities. (a) RhoGEFs exhibit specificity towards few Rho GTPases. (b) Examples of RhoGEFs and their specificity towards Rho GTPases as mapped by proximity labeling coupled with mass spectrometry. (c) RhoGAPs are promiscuous and display broad activity towards Rho GTPases. (d) Examples of Rho GAPs and their specificity towards Rho GTPases as mapped by proximity labeling coupled with mass spectrometry.
Figure 3. Mapping of Rho GTPases regulators specificities. (a) RhoGEFs exhibit specificity towards few Rho GTPases. (b) Examples of RhoGEFs and their specificity towards Rho GTPases as mapped by proximity labeling coupled with mass spectrometry. (c) RhoGAPs are promiscuous and display broad activity towards Rho GTPases. (d) Examples of Rho GAPs and their specificity towards Rho GTPases as mapped by proximity labeling coupled with mass spectrometry.
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Figure 4. The spatial distribution of Rho GTPases by their regulators the RhoGEFs and RhoGAPs determines Rho GTPase activity. Schematic representation showing that the spatial distribution of RhoGEFs and RhoGAPs helps to create Rho GTPases active and inactive zones in cells The Golgi and mitochondria only host RhoGAPs. This could allow the inactivation of Rho GTPases that would have diffused away from their desired site of action.
Figure 4. The spatial distribution of Rho GTPases by their regulators the RhoGEFs and RhoGAPs determines Rho GTPase activity. Schematic representation showing that the spatial distribution of RhoGEFs and RhoGAPs helps to create Rho GTPases active and inactive zones in cells The Golgi and mitochondria only host RhoGAPs. This could allow the inactivation of Rho GTPases that would have diffused away from their desired site of action.
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Table
Table 1. Overview of high throughput studies.
Table 1. Overview of high throughput studies.
ApproachGoalCell TypesReference
qGAPIdentify Rho GTPases binding partnersHEK293
Mouse brain lysate		[61]
BioIDDefine Rho family proximity interactomeHEK293
HeLa		[64]
Flag-IPDefine RhoGEFs and RhoGAPs interactomeHEK293[73]
In vitro siRNA screenIdentify RhoGEFs required for amoeboid movement in melanoma cellsA375M2[80]
In vitro siRNA screenIdentify RhoGEFs that regulate amoeboid and mesenchymal featuresA375M2[81]
In vitro siRNA screenInvestigate the role of Rho GTPases network components during prostate cancer cell migrationPC3[21]
In vitro siRNA screenIdentify RhoGEFs and RhoGAPs that regulate breast cancer cell morphologyLM2
MDA-MB-231		[86]
In vitro siRNA screenIdentify RhoGAPs that contribute to EMTMCF10A[87]
In vitro siRNA screenIdentify regulators of the endothelial barrier among Rho GTPases network components.HUVEC[88]
In vitro shRNA screenIdentify RhoGEFs regulating collective migration16HBE14o[89]
In vivo shRNA morphogenesis screenIdentify regulators of skin morphogenesis among Rho GTPases network componentsMouse embryos
Primary mouse keratinocytes		[97]

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Dahmene, M.; Quirion, L.; Laurin, M. High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling. Cells 2020, 9, 1430. https://doi.org/10.3390/cells9061430

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Dahmene M, Quirion L, Laurin M. High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling. Cells. 2020; 9(6):1430. https://doi.org/10.3390/cells9061430

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Dahmene, Manel, Laura Quirion, and Mélanie Laurin. 2020. "High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling" Cells 9, no. 6: 1430. https://doi.org/10.3390/cells9061430

APA Style

Dahmene, M., Quirion, L., & Laurin, M. (2020). High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling. Cells, 9(6), 1430. https://doi.org/10.3390/cells9061430

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