Computational analysis for GNAQ mutations: New insights on the molecular etiology of Sturge-Weber syndrome

Accepted Manuscript Title: Computational Analysis for GNAQ Mutations: New insights on the molecular etiology of Sturge-Weber Syndrome Authors: Luciane Martins, Priscila Alves Giovani, Pedro Diniz Rebouc¸as, Danieli Moura Brasil, Francisco Haiter Neto, Ricardo D. Coletta, Renato Assis Machado, Regina Maria Puppin-Rontani, Francisco Humberto Nociti Jr., Kamila Rosamilia Kantovitz PII: DOI: Reference:

S1093-3263(17)30425-4 http://dx.doi.org/doi:10.1016/j.jmgm.2017.07.011 JMG 6970

To appear in:

Journal of Molecular Graphics and Modelling

Received date: Revised date: Accepted date:

6-6-2017 11-7-2017 12-7-2017

Please cite this article as: Luciane Martins, Priscila Alves Giovani, Pedro Diniz Rebouc¸as, Danieli Moura Brasil, Francisco Haiter Neto, Ricardo D.Coletta, Renato Assis Machado, Regina Maria Puppin-Rontani, Francisco Humberto Nociti, Kamila Rosamilia Kantovitz, Computational Analysis for GNAQ Mutations: New insights on the molecular etiology of Sturge-Weber Syndrome, Journal of Molecular Graphics and Modellinghttp://dx.doi.org/10.1016/j.jmgm.2017.07.011 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Martins et al. Type of article: Original Research Article Computational Analysis for GNAQ Mutations: New insights on the molecular etiology of Sturge-Weber Syndrome. Luciane Martinsa*, Priscila Alves Giovanib*, Pedro Diniz Rebouçasb, Danieli Moura Brasilc, Francisco Haiter Netoc, Ricardo D. Colettac, Renato Assis Machadoc, Regina Maria PuppinRontanib, Francisco Humberto Nociti Jr.a and Kamila Rosamilia Kantovitzb,d * These authors contributed equally to this work a

Department of Prosthodontics and Periodontics, Division of Periodontics, Piracicaba Dental School, University of Campinas - UNICAMP, Piracicaba, SP, Brazil. b Department of Pediatric Dentistry, Piracicaba Dental School, University of Campinas UNICAMP, Piracicaba, SP, Brazil. c Department of Oral Diagnosis, Piracicaba Dental School, University of Campinas UNICAMP, Piracicaba, SP, Brazil. d Department of Dental Materials, São Leopoldo Mandic School of Dentistry and Research Center, Campinas, SP, Brazil. Corresponding author: Dr. Kamila Rosamilia Kantovitz Department of Dental Materials São Leopoldo Mandic - School of Dentistry and Research Center Campinas, SP, Brazil. Telephone/Fax: +55 19 35183600 E-mail address: [email protected] Graphical abstract

1

Martins et al.

Highlights 

The role of GNAQ mutations in the molecular etiology of Sturge-Weber Syndrome.



Sturge-Weber Syndrome bearing a somatic mosaic mutation (c.548G>A; p.R183Q) in GNAQ.



p.R183Q and p.Q309L mutations differently affect the protein structure and function.



p.R183Q and p.Q309L mutations lead to over-activation of different signaling pathways.



Activation of different signaling cascades by GNAQ mutants result in distinct phenotypes.

ABSTRACT

Somatic activating mutations in the GNAQ have been recently associated with several congenital genetic disorders and tumors; however, the molecular mechanism/etiology that leads to GNAQ somatic mosaic mutation are unknown. Here, we reported a case of SturgeWeber Syndrome (SWS) manifesting cutaneous vascular malformations (hemifacial Portwine stain), cerebral and ocular vascular abnormalities (including epilepsy and glaucoma) and harboring a c.548G>A (p.R183Q) somatic mosaic mutation in GNAQ. Computational modeling studies were performed to assistant with the comprehension of the functional impact of p.R183Q and p.Q209L mutations in GNAQ, which encodes a G protein subunit alpha q (Gαq). The p.R183Q mutation was predicted to abolish hydrogen bonds between R183 residue and GDP molecule, destabilizing the inactive GDP-bound conformation of the Gαq mutants. Furthermore, replacement of R183 by Q183 residue was predicted to promote conformation changes in protein surface features affecting the switch I region, a key region 2

Martins et al. that undergoes conformational changes triggered by receptor binding during signal transduction. In addition, replacement of Q209 by L209 residue was predicted to affect the molecular interaction between Gq and G subunit, impairing formation of the inactive heterotrimeric complex. These findings, in association with PPI network analysis, indicate that p.R183Q and p.Q209L mutations result in the over-activation of different downstream effectors, which in turn will determine the distinct cell responses and phenotype. These findings bring new insights on molecular etiology of vascular malformations associated to SWS and on different mechanisms underlying hyperactivation of downstream pathways to Gq.

Keywords: GNAQ mutations; G protein signaling; genetic disorders; homology modeling; protein-protein interaction networks.

INTRODUCTION Sturge-Weber Syndrome (SWS; MIM#185300) is a vascular neurocutaneous disorder characterized by facial/capillary port-wine stains, leptomeningeal vascular malformation, and ocular abnormalities, which include choroidal vascular anomalies and glaucoma [1, 2]. Despite being rare, SWS is the most frequent disease among the neurocutaneous syndromes and occurs with an estimated frequency of 1:20,000 to 1:50,000 live births [2]. Progressive course of SWS in early childhood is marked by extremely variable clinical manifestations

which

include

seizures,

epilepsy,

stroke-like

episodes,

headaches,

neurological and cognitive deterioration, hemiparesis, glaucoma and visual field defects [3]. Facial port-wine stain (PWS; MIM#163000), a common congenital vascular lesion caused by progressive ectasia of vascular plexus of the dermis affecting the upper parts of the face, is considered a risk factor for SWS and is detected in 87–90% of the SWS cases [4, 5]. Specific facial patterns indicating an increased risk for SWS in children with upper facial PWS were reported by Dutkiewicz et al. (2015) in a prospective study and included specific localization 3

Martins et al. and distribution pattern of PWS involving the midline crossing, nasal area, temporal area, and scalp [5]. In addition, Dutkiewicz et al. (2015) suggest that the facial distribution of PWS occurs due to genetic mosaicism and is not associated with the ophthalmic division of trigeminal nerve territory as originally supposed [5]. More recently, the molecular etiology of SWS started to be unrevealed, and a specific somatic mosaic activating mutation in the guanine nucleotide-binding protein alpha-q gene (GNAQ; MIM# 600998) has been reported to be associated with both, SWS and nonsyndromic PWS [6, 7, 8, 9]. In 2013, for the first time, a somatic non-synonymous singlenucleotide variant (c.548G→A, p.R183Q) in GNAQ gene, suggested to disrupt vascular development, was detected in 88% of pathologic tissue samples from SWS (brain and skin) and in 92% (skin) from non-syndromic PWS [6]. Although these recent studies have improved our understanding of this syndrome, first described in 1879, many aspects remain unclear, including, for example, the impact of such somatic mosaic mutation on the structure and function of the Gαq protein. Computational methods for predicting 3D protein models have been increasingly used to determine the mechanisms underlying disease, as well as in the pharmaceutical industry [10]. Protein structure studies and homology modeling have shown that specific structural properties, such as stability and residue burial, can be used to assist in recognizing and distinguishing disease-causing mutations from neutral variants [11, 12]. Furthermore, recent studies have demonstrated the value of computational studies of predicting 3D protein models for the development of new personalized treatment strategies and drug discovery [10, 11, 12, 13]. In the current study, we report a clinical case of SWS in a 9-year-old Caucasian boy, including its dermatologic (facial PWS), neurologic, ophthalmologic, and intra-oral findings. We also identified the p.R183Q somatic activating mutation in the GNAQ associated with SWS affected tissues and performed a computational study of predicting 3D protein model to determine the structural impact of the p.R183Q and p.Q209L mutations on the Gq protein

4

Martins et al. structure. The findings reported here will assist in elucidating the different mechanisms underlying hyperactivation of downstream pathways to Gq, which lead to congenital vascular anomalies and tumors.

RESULTS Medical and dental analysis: The proband is the second son of healthy parents (mother, 31 years old; father, 38 years old), with a healthy brother (11 years old) with no history of infantile SWS, hemangioma or PWS. Physical examination revealed a hemifacial PWS on the right side, involving upper quarter, cheek, upper-lip and extending over the right side of the nose (Figure 1A). In addition, there was a medical history of episodic epileptic seizures since the age of 8 months, which has been controlled by prescribed drugs, including Valproate, Valproic Acid, Phenobarbital, and more recently Oxcarbazepine. It was also reported a history of multiple migraine episodes associated with unilateral congenital glaucoma, which was reduced in number, intensity, and duration after glaucoma surgery. No additional relevant medical events were reported. MRI analysis evidenced a brain asymmetry (due to right hemispheric brain atrophy), leptomeningeal angiomatous malformation (including

right-sided

hemispheric

leptomeningeal

enhancement

or

asymmetric

leptomeningeal enhancement), vascular anomalies enlarged and enhancing right-sided choroid plexus (Supplementary figure 1). Intraoral exam evidenced mixed dentition without caries lesion, and a poor oral hygiene resulting in a moderate level of gingival inflammation on the right quadrant (Figure 1B). Erythematous reddish pink patches were observed in the gingiva of the maxilla and mandible, the floor of the mouth, lips, cheeks, hard palate and ipsilaterally to the PWS (Figure 1B and 1C). These lesions showed blanching when the pressure was applied (Figure 1D). Macroglossia was not observed. Dental abnormalities included loss of enamel and dentin without visible signs of exposed pulp tissue in both upper central incisors (Figure 1B). Panoramic and cone-beam computed tomography (CBCT) and intraoral radiographs 5

Martins et al. revealed an accelerated rate of tooth exfoliation and eruption on the right side (Figure 1E, F, and G), probably due to increased blood supply in the affected region. Genetic findings: A somatic mosaic mutation was found in the GNAQ gene associated with SWS (Supplementary figure 2). Control (saliva) and affected gingival tissues samples were obtained and sequencing of the GNAQ gene identified a heterozygous transition of the G nucleotide at 548-nt position for an A (c.548G>A), leading to the change of Arginine (Arg, R) for Glutamine (Gln, Q) in the 183 protein position (p.R183Q). The affected tissues presented a genetic mosaicism pattern to mutation p.R183Q, with a percentage of mutant alleles of 6.55%, compared to the native sequence from saliva.

p.R183Q somatic mutation in GNAQ affects the stability of inactive GDP-bound Gq form: In the current study, in silico search for specific functional units and domain indicated that the Gαq protein consisted of two domains: a GTP-binding domain (which is homologous to Ras-like small GTPases, and included switch regions I and II and a helical insertion domain (inserted into the GTP-binding domain before switch region I); and P-loop containing nucleoside triphosphate hydrolase (P-loop NTPase), which is involved in the catalyzing of GTP hydrolysis (Figure 2A). Tridimensional model analysis showed that the R183 residue is located in the coil structure into the core of hydrophobic cleft between two inter-domain linkers connecting the GTPase and helical domains of the Gαq (Figure 2 B). Conformational changes in protein surface features (in the hydrophobic cleft region), affecting the switch I region, were evidenced after the alignment of mutant (Q183) and native (R183) 3D models (Figure 2C, 2D, and 2E). Furthermore, the p.R183Q mutation was predicted to affect directly the molecular interactions between Gq subunit and GDP molecule (Figure 2F and 2G). The R183 residue was predicted to form two hydrogen bonds with GDP molecule, which were abolished when R183 native residue was replaced by Q183 mutant residue in the Gq protein structural model (Figure 2F and 2G).

6

Martins et al. To elucidate the molecular aspects involved in different mechanisms of hyperactivation of downstream pathways to Gq, we additionally performed the computational studies of predicting 3D protein models for p.Q209L, other somatic mutation in GNAQ, recently associated with rare vascular tumor (congenital hemangioma), and which is commonly observed in primary intraocular malignant tumor (uveal melanoma). Our computational analysis of molecular interactions for native and mutant G-protein models showed that the replacement of Q209 by L209 mutant residue affected the hydrogen bonds between  and  subunits. The Q209 native residue form hydrogen bonds with S211 and G207 from  subunit and with Y145 residue from  subunit, while L209 mutant residue preserved hydrogen bonds established with S211, but abolished the hydrogen bonds established with G207 residue from  subunit and with Y145 residue from  subunit (Figure 3A and B).

Different signaling cascades are activated by Gq and/or G subunits. In order to validate the hypothesizes that p.R183Q and p.Q209L would differentially affect signal transduction cascades and attempt to determinate which biological processes are involved in the activation of each subunit, we used a robust computational analysis of protein interacting with either Gq or G subunits [Cytoscape platform was used to retrieve the BioGRID PPI database and built a merged PPI network for Gq (encoded by GNAQ) and G subunits (encoded by GNB1, 2, 3 and 4)]. Based on the merged network, it was selected both, common Gq- and Gs-interacting proteins or exclusive Gq- and Gs-interacting proteins for further GO enrichment analysis (biological process) using the Cytoscape plugin BiNGO and Homo Sapiens as the organism/annotation, to identify the main over-represented GO categories in each network. To identify signal transduction cascade exclusively for Gq or G, all over-represented GO categories in both, GNAQ and GNBs networks, were detached. Different biological processes (GO categories differentially over-represented) in each one of GNAQ or GNBs PPI networks are listed in Table 1. Here, Gq-interacting 7

Martins et al. proteins (RGS2, RGS4, RGS5, RGS7, RGS16 and RGS18), which belongs to the GO category of negative regulation of signal transduction (GO ID: 9968 and 23057) were exclusively over-represented in GNAQ network (Figure 4). In addition, regulation of ARF protein signal transduction was also a GO term exclusively over-represented in the GNAQ network (Table 1). A number of GO terms were exclusively over-represented in the GNB1 network, and are listed in Table 1. Data analysis also showed that no GO term overrepresented was exclusive in GNB3 network. Exclusive over-represented GO terms in the GNB2 network included regulation of cell proliferation and negative regulation of molecular function (Table 1).

Q209 residue is an important site to Gq-RGS interaction Because, computational PPI network analysis for Gq indicated that negative regulation of signal transduction and positive regulation of ARF signaling are important biological processes for Gq-mediated signaling cascade, we evaluated which residues may potentially be involved in the Gq-RGS interaction. Molecular interaction analysis for native and mutant Gq protein models showed that Q209, T187 and I189 residues from Gq are involved in Gq-RGS interaction. The replacement of Q209 by L209 mutant residue in the Gq abolished the hydrogen bonds between Q209 residue and the N149 or N122 residue from RGS2 and RGS8, respectively (Figure 5).

DISCUSSION In the current study, we report a case of a 9-year old boy with classical clinical features of SWS, including facial PWS, leptomeningeal angiomas, glaucoma, and epilepsy. According to the Roch Scale for neurocutaneous syndromes [14], the current case was classified as type I. MRI exam additionally detected cerebral atrophy and vascular abnormalities in this patient. The literature indicates that the extent of brain involvement and the age of seizure onset are

8

Martins et al. predictive of neurological outcome and epilepsy severity. In addition, the presence of epilepsy and frequency of seizures have been correlated with greater risk for a variety of intellectual, behavioral, and mood concerns [15]. Similarly to previous reports on SWS [2, 16, 17, 18, 19], in the current study, oral manifestation consisted of angiomatous lesions (erythematous reddish pink patches) in the gingiva of the maxilla and mandible, the floor of the mouth, lips, cheeks and hard palate, and gingival inflammation with increased bleeding scores. Craniofacial alterations were also detected and included malocclusion and facial asymmetry. Such phenotypes often require major procedures to improve face aesthetic and malocclusion [1], demanding knowledge of the syndrome-associated clinical features and treatment modalities [17]. SWS presents variable clinical aspects and an effective treatment must be individually determined according to its clinical status. In addition to conception/development of experimental models to study the SWS, which will assist us to expand our knowledge on the gene function [15], computational analysis predicting the potential impact of GNAQ mutations might significantly improve our understanding of the etiology of SWS-associated vascular malformations contributing, therefore, to the identification of potential new therapeutic targets (which directly modulate G proteins) and the development of new and effective treatments strategies to deal with SWS. In the current study, the genetic diagnosis showed the presence of a somatic mosaic mutation in GNAQ gene (c.548G>A; p.R183Q) in DNA samples from the affected gingival tissues (erythematous reddish pink patches ipsilaterally to the PWS) compared to DNA from saliva (control). In the literature, the p.R183Q somatic mutation in the GNAQ has been associated with both SWS and non-syndromic PWS [6, 7, 8, 9] and more recently was also identified in phakomatosis pigmentovascularis [20]. On the other hand, p.Q209L somatic mutation in GNAQ are commonly observed in primary intraocular malignant tumor (uveal

9

Martins et al. melanoma) [21, 22], and more recently correlated with congenital hemangioma, a rare vascular tumor [23]. In vitro studies have shown that both p.R183Q and p.Q209L somatic mutations in GNAQ gene have a gain-of-function effect that results in hyperactivation of downstream signaling pathways [6, 21]. Such effect is supposed to result of a Gαq with impaired autohydrolysis (hydrolysis of  subunit bound GTP to GDP) and impaired inactivation [6]. In fact, substitution of cysteine at the R183 position was shown to result in reduced hydrolysis of GTP to GDP, a key step required for G-protein inactivation [24, 25]. On the other hand, the inactivation of G protein-activated signaling pathways was shown to be dependent on re-association of heterotrimeric G protein subunits and their binding to the receptor, which occurs as a result of intrinsic GTPase activity of G subunit [15, 26, 27].

The GNAQ gene, mapped to 9q21, encodes to the human Guanine nucleotide-binding protein G(q) subunit alpha (Gαq; P50148). The Gαq protein is part of the heterotrimeric GTPbinding proteins (G proteins), composed of three subunits: alpha, beta, and gamma, which transmit extracellular stimuli via G-protein-coupled receptors (GPCRs) to intracellular signaling cascades [15, 28, 29]. A scheme showing the regulatory cycle of activation and inactivation of heterotrimeric G proteins by GPCR is presented in figure 6. The response to specific external stimuli triggered by GPCR is determined by a specific combination of subunits in heterotrimeric G, which in turn determinates the downstream effector specificity and activation of the specific downstream target [30]. Studies have suggested that both, GTP-Gαq subunit and Gβγ dimer, are able to propagate the intracellular signals (separately and sometimes converging) through their interaction with different downstream effectors (such as ion channels, adenylyl cyclase, phosphodiesterases, phospholipase C, and guanine-nucleotide exchange factors (GEF) for the GTPase RhoA) [reviewed by 28, 31]. Furthermore, the signal mediated by Gq may also be modulated by regulators of G-proteins signaling (RGS) proteins that act accelerating the intrinsic GTPase activity (GTP hydrolysis) of the Gα subunit [31]. 10

Martins et al. G subunits display a conserved protein fold composed of the helical domain and GTPase domain, which is responsible for hydrolysis of GTP to GDP and to provide a binding surface for the G dimer, effectors, and GPCRs [29]. The GTPase domain contains three flexible loops, named switches I, II and II, where differences between molecular conformation of GDP-bound Gq and GTP-bound Gq were previously identified [reviewed by 29]. In the present study, the p.R183Q activating mutation in GNAQ was predicted to promote conformational changes affecting the switch I region and destabilizing the inactive GDPbound Gq conformation, whereas the p.Q209L activating mutation was predicted to affect the molecular interaction between Gq and  subunits, thus impairing the re-association and stability of inactive G-protein heterotrimeric complex. Together, these findings suggest that the distinct impact produced by p.R183Q and p.Q209L mutations on the Gq protein structure will differently affect signal intensity and/or result in over-activation of downstream effectors, which in turn will account for the distinct cell responses. Recent studies have shown that p.Q209L mutations lead to hyperactivation of MAPK and Hippo-YAP signaling pathway [6, 21, 32]. However, the p.R183Q mutation was shown to present only a modest effect in the downstream activation of extracellular signal-regulated kinase (ERK) when compared with the activation induced by p.Q209L mutation [6]. In addition, p.Q209L has been demonstrated to strongly activate other downstream effectors, such p38 and Jun N-terminal kinase (JNK), whereas p.R183Q did not [6]. In the current investigation, computational analysis of 3D models for p.R183Q and p.Q209L mutations showed that p.R183Q mutation results in destabilization of the inactive GDPbound form of Gq through the abolishment of hydrogen bond between R183 residue and GDP molecule and conformal changes in surface features of switch I region, while the p.Q209L mutation was predicted to abolish hydrogen bonds between G and G, and potentially reducing the stability of heterotrimeric G proteins complex (Figure 2 and 3). Therefore, the computational analysis used here indicates that the molecular mechanisms for

11

Martins et al. hyperactivation of downstream pathways by Gq, associated with the p.Q183R mutation, is supposed to involve a reduced GDP/GTP exchange (due to impaired intrinsic GTPase activity) and destabilization of the inactive GDP-bound conformation, an earlier step but that also affects the re-association of heterotrimeric G proteins subunits and inactive state of G proteins, whereas the molecular mechanism in consequence of p.Q209L mutation, was supposed to result in a reduced capacity of re-association of the  and  subunits and reduced stability of inactive heterotrimeric G proteins complex. Previous studies in PWS have shown that the pathophysiology underlying congenital vascular anomalies could be, at least in part, explained for cell-type specific distributions of the p.R183Q GNAQ mutation, since that endothelial cells are enriched for GNAQ mutations [33, 34]. In addition to cell type affected by GNAQ somatic mutation and stage of fetal development at which the mutation occurs [6], our results suggest that different molecular mechanisms may be also involved in the constitutive activation of G-protein signaling pathway for p.R183Q and p.Q209L mutants, resulting in distinct phenotypes. To validate this hypothesis we performed PPI network analysis to identify downstream effectors/regulators interacting exclusively with either Gq or  subunits. Different biological processes were over-represented in GNAQ and GNBs PPI networks (Table 1). The biological processes differentially over-represented in GNAQ PPI network as compared to GNB1, 2, 3 and 4 PPI networks were: negative regulation of signal transduction (represented by RGS2, RGS4, RGS5, RGS7, RGS16 and RGS18 proteins) and regulation of ARF protein signal transduction (represented by several Guanine nucleotide-exchange factors (GEF) for ADPribosylation factors (ARFs), including IQSEC1 (also known as ARF-GEP100), CYTH1 (also known as SEC7), CYTH2 (also known as ARNO and PSCD2), CYTH3 (also known as ARNO3 and PSCD3) and PSD). In addition, we also showed that the Q209 is an important residue for Gq-RGS molecular interaction. The replacement of Q209 by L209 results in loss of hydrogen bond between the Q209 residue of Gq and N149 or N122 from RGS2 and RGS8, respectively. These results 12

Martins et al. suggest that the intrinsic GTPase activity (GTP hydrolysis) of the Gq p.Q209L mutants may not be properly regulated by RGSs, resulting in impaired inactivation of Gq-mediated signaling cascade. In line with ours PPI interaction analysis, previous studies in HEK293T cells have shown that activated Gαq forms a molecular complex with various ARF-GEFs, leading to the activation of ARF6 [35, 36, 37]. ARFs are Ras-related small GTPases which display a wellcharacterized role in the regulation of vesicular trafficking. More recently, ARFs GTPases (ARF-1 and ARF-6) have been reported to also function as signal transducers, mediating the activation of MAPK pathway by G-protein-coupled GPCR and regulating cell proliferation [37, 38]. Curiously, a recent study has also reported that ARF6 acts as an immediate downstream effector of Gq-GEP100 complex, activating multiple downstream signaling pathways (including PLC/PKC, Rho/Rac, and YAP and -catenin signaling) and playing a central role in Gq-mediated cell proliferation [37]. In vivo and in vitro blockage of ARF6 has been shown to lead to a reduced Gq(p.Q209L)-dependent signaling and cell proliferation. In addition, this study showed that Gq mutant forms a molecular complex with ARF-GEP100, with consequent activation of ARF6, and redistribution of cell-surface GNAQ to cytoplasmic vesicles. Knockdown of ARF6 or ARF-GEP100 or chemical inhibition of ARF6 induces Gq relocalization from the cytoplasm to the plasma membrane with a concomitant decrease in signaling of all Gq-mediated pathways [37]. Thus, the mechanism by which ARF6 controls all of the currently known pathways mediated by Gq activating mutations was supposed to involve the trafficking of Gq subunit between intracellular compartments and redistribution of cell-surface Gq to cytoplasmic vesicles, where the Gq signaling is supposed to occur [37]. In addition, in animal models of vascular eye disease, blocking ARF6 activation, with SecinH3,

has

been

reported

to

inhibit

pathologic

angiogenesis

and

endothelial

hyperpermeability [39]. Although, ours computational results corroborate with this recent studies, showing that ARF is an important effector in the Gq-GTP signal transduction, and pointing out ARF6 and ARF-GEFs as potential therapeutic target for diseases treatment 13

Martins et al. caused by somatic mutation in GNAQ, the effect of the p.R183Q activating mutation in the Gq-GEF complex formation and ARF6-mediated signaling pathways remain to be validated by in vitro or in vivo studies. Computational analysis suggest that the weak effect of Gq p.R183Q somatic mutation in MAPK signal transduction compared to p.Q209L [6], may be explained by distinct impact of each mutation on Gq protein structure leading to distinct modulation of signal intensity due the failure in mechanism of regulation of GTPase intrinsic activity, with consequent overactivation of downstream effectors for Gq subunit and G dimer. In figure 6B and 6C, we proposed a mechanism for native and pathogenic Gq signaling, which was based on our computational analysis and guided by the evidences from the literature. The formation of inactive Gq-G complex, with consequent inactivation of G-mediated signaling is dependent of inactivation of Gq, re-localization of Gq-GDP from the cytoplasm to the plasma membrane and its efficient association with G dimer. Thus, the G-mediated signaling pathways are directly affected by dysregulated Gq signaling. However, we suggest that the signal intensity mediated by activation of G may be additionally affected in p.Q209L, since this residue appears to be important to Gq-G interaction.

A number of biological processes were exclusively over-represented in GNB1 PPI network, including regulation of catalytic activity, regulation and activation of phospholipase C activity and adenylate cyclase activity, negative regulation of ion transmembrane transporter activity, negative regulation of calcium ion transport via voltage-gated calcium channel activity, desensitization of G-protein coupled receptor protein signaling pathway. Previous in vitro studies have shown that the p.Q209L mutation leads to increased cell proliferation rates and inhibited apoptosis [21]. Interestingly, the findings of the current study, revealed that effectors exclusively interacting with G2 subunits were involved with the regulation of cell proliferation, and therefore, assist us to expand our knowledge on the potential oncogenic

14

Martins et al. effect of the p.Q209L somatic mutation (the most common mutation associated with tumors, such as melanoma uveal and hemangioma congenital). Here, PPI network analysis assisted us to identify signaling pathways and potential differentially regulated biological processes by Gαq subunit or Gβ dimer associated with GPCR and bring new insights on potential mechanisms involved in signal intensity and propagation by Gq p.R183Q or p.Q209L mutants, leading to distinct cell responses and phenotypes. This knowledge may contribute to the identification of potential new therapeutic targets and in the development of new and effective personalized therapeutic strategies for SWS. METHODS Subject and clinical analysis: A 9-year-old Caucasian boy with an unilateral facial PWS lesion was referred to the University of Campinas - Piracicaba Dental School with the main complaint of comprised aesthetics due to a tooth fracture (upper central incisor). Clinical signs of leptomeningeal vascular malformation, as well as other clinical signs indirectly associated with SWS, such as cerebral atrophy or calcification, enlargement of pericerebral space, enlargement of choroid plexus, abnormalities in venous drainage, among other specific unilateral abnormalities, were systematically assessed. Intraoral examination included dental and periodontal evaluation, plaque and gingival bleeding scores and intraoral photography. In addition, periapical, occlusal, and panoramic radiographs were taken to determine his dental-alveolar status, whereas magnetic resonance imaging (MRI) was used to assist with the identification of potential brain alterations.

Identification of GNAQ somatic mosaic mutation: Direct DNA sequencing of PCR products was performed using the BigDye Terminator v3.1 Cycle Sequencing Kit and migrated on capillary 3500 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA). The GNAQ gene was amplified by polymerase chain reaction (PCR) using primers designed to amplify the covering mutation region (Exon 4, forward 5’- ATTGTGTCTTCCCTCCTCTA 15

Martins et al. 3’ and reverse 5’-GGTTTCATGGACTCAGTTAC-3’) [6]. Allele frequencies in saliva sample (reference) and gingival lesion were calculated on the basis of the area of the resulting peaks, using a tool for DNA variant analysis (Mutation Surveyor® software; SoftGenetics).

Tridimensional (3D) Gαq models and molecular interaction analysis: Native and mutant (p.R183Q and p.Q209L) 3D models were built for the Gαq protein based on previously determined crystal structure of heterotrimeric G protein Gq-G (PDB: 3AH8.1.A) [13] or RGS2 in complex with Gq (R183C)(PDB: 4EKC) [40] or RGS8 in complex with IF4activated Gq (PDB: 5DO9) [41] using the SWISS-MODEL software [42]. The native and mutant models were aligned, visualized, and analyzed using the PyMOL (PyMOL Molecular Graphics System, Version 1.7.4, Schrödinger, LLC). Gq internal contacts and molecular interaction between the Gq and G subunits were analyzed using the PdbViewer modeling tool [43].

In silico analysis of GNAQ and GNBs Protein-protein Interaction (PPI) Networks First, we performed a search for proteins interacting with Gq in BioGRID (General Repository for Interaction Datasets) website (http://www.thebiogrid.org/index.php) to identify which Gs are found to interact with Gq. Then, the interactions for Gq (GNAQ network) and G1, G2, G3 and G4 (GNB1, GNB2, GNB3, and GNB4 networks) were retrieved from protein-protein interaction (PPI) databases of BioGRID and imported into the Cytoscape 3.3.0 software. A merged PPI network for GNAQ and GNBs was assembled and visualized as an interactive graphical network using the Cytoscape 3.3.0. Non-human proteins were deleted of GNAQ and GNBs PPI networks and duplicated edges were removed. Proteins exclusively interacting with Gq or G1, G2, G3 and G4 were evidenced after generating statistics network. Next, the degree filter for GNAQ node or GNBs nodes was applied separately. First neighbors for each GNAQ or GNBs were selected separately and Gene Ontology (GO) enrichment analysis and statistically over-represented GO categories in each 16

Martins et al. one of biological networks were assessed using a Cytoscape plugin BiNGO (Biological Networks Gene Ontology tool; [44]). Over-represented GO terms were determined for proteins exclusively present in GNAQ or GNBs biological networks, as well for proteins mutually overlapping in GNAQ and GNBs networks. In the current investigation, it was established a significance level of 0.001 for BiNGO analysis. Then, the p-values for overrepresented GO biological process terms in each one biological network (GNAQ or GNB1, GNB2, GNB3, GNB4 or GNBs merged) were assessed, and significantly enriched categories were considered for comparison.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE The study protocol was approved by the Piracicaba Dental School - University of Campinas Institutional Review Board (IRB# 1721679), and a written informed consent to participate in the study was obtained from guardians of the child enrolled in this study, in compliance with the World Medical Association Declaration of Helsinki, Ethical Principles for Medical Research Involving Human Subjects. A written informed consent for publication of their clinical details and clinical images was obtained from the guardians of the child enrolled in this study.

COMPETING FINANCIAL INTERESTS The authors declare that they have no conflict of interest.

ACKNOWLEDGMENTS This research was supported by National Council for Scientific and Technological Development

[CNPq,

grant # 304680/2014-1

(FHNJ)]

and

by

Coordination for

the Improvement of Higher Education Personnel [CAPES, grant # 33003033008P8 (LM)].

17

Martins et al. REFERENCES [1] A. K. Greene, S. F. Taber, K. L. Ball, B. L. Padwa, J. B. Mulliken, Sturge-Weber syndrome: soft-tissue and skeletal overgrowth, J. Craniofac. Surg. 20 Suppl 1 (2009) 617-621. [2] S. M. Shaikh, M. Goswami, S. Singh, D. Singh, Sturge-Weber syndrome - A case report, J. Oral Biol. Craniofac. Res. 5 (2015) 53-56. [3] A. Sudarsanam, S. L. Ardern-Holmes, Sturge-Weber syndrome: from the past to the present, Eur. J. Paediatr. Neurol. 18 (2014) 257-266. [4] C. Inan, J. Marcus, Sturge-Weber syndrome: report of an unusual cutaneous distribution, Brain Dev. 21(1999) 68-70. [5] A. S. Dutkiewicz, K. Ezzedine, J. Mazereeuw-Hautier, J-P. Lacour, S. Barbarot, P. Vabres, et al., A prospective study of risk for Sturge-Weber syndrome in children with upper facial port-wine stain, J. Am. Acad. Dermatol. 72 (2015) 473-480. [6] M. D. Shirley, H. Tang, C. J. Gallione, J. D. Baugher, L. P. Frelin, B. Cohen, et al., Sturge-Weber syndrome and port-wine stains caused by somatic mutation in GNAQ, N. Engl. J. Med. 368 (2013) 1971-1979. [7] C. G. Lian, L. M. Sholl, L. R. Zakka, T. M. O, C. Liu, S. Xu, et al., Novel genetic mutations in a sporadic port-wine stain, JAMA Dermatol. 150 (2014)1336-1340. [8] M. Nakashima, M. Miyajima, H. Sugano, Y. Iimura, M. Kato, Y. Tsurusaki, et al., The somatic GNAQ mutation c.548G>A (p.R183Q) is consistently found in Sturge-Weber syndrome, J. Hum. Genet. 59 (2014) 691-693. [9] Y. Uchiyama, M. Nakashima, S. Watanabe, M. Miyajima, M. Taguri, S. Miyatake, et al., Ultra-sensitive droplet digital PCR for detecting a low-prevalence somatic GNAQ mutation in Sturge-Weber syndrome, Sci. Rep. 6 (2016) 22985. [10] T. Schmidt, A. Bergner, T. Schewede, Modelling three-dimensional protein structures for applications in drug design, Drug Discov. Today 19 (2014) 890-897.

18

Martins et al. [11] R. A. Studer, B. H. Dessailly, C. A. Orengo, Residue mutations and their impact on protein structure and function: detecting beneficial and pathogenic changes, Biochem. J. 449 (2013) 581-94. [12] J. Reumers, J. Schymkowitz, F. Rousseau, Using structural bioinformatics to investigate the impact of non-synonymous SNPs and disease mutations: scope and limitations, BMC Bioinformatics 10 (2009) S9. [13] A. Nishimura, K. Kitano, J. Takasaki, M. Taniguchi, K. Mizuno, K. Tago, Structural basis for the specific inhibition of heterotrimeric Gq protein by a small molecule, Proc. Natl. Acad. Sci. U. S. A. 107 (2010) 13666-13671. [14] E. S. Roach, Neurocutaneous syndromes, Pediatr. Clin. North Am. 39 (1992) 591-620. [15] A. M. Comi, M. Sahin, A. Hammill, E. H. Kaplan, C. Juhasz, P. North, et al., Leveraging a Sturge-Weber Gene Discovery: An Agenda for Future Research, Pediatr. Neurol. 58 (2016) 12-24. [16] D. D. Lin, P. Gailloud, E. F. McCarthy, A. M. Comi, Oromaxillofacial osseous abnormality in Sturge-Weber syndrome: case report and review of the literature, AJNR Am. J. Neuroradiol. 27 (2006) 274-277. [17] B. Kalakonda, K. Pradeep, A. Mishra, K. Reddy, T. Muralikrishna, V. Lakshmi, Periodontal management of Sturge-Weber syndrome, Case Rep. Dent. 2013 (2013) 517145. [18] N. Sharma, S. Passi, A. Mehta, Sturge-Weber syndrome: Report of a case and literature review, J. Pediatr. Dent. 2 (2014) 65-69. [19] A. K. Tripathi, V. Kumar, R. Dwivedi, C. S. Saimbi, Sturge-Weber syndrome: oral and extra-oral manifestations, BMJ Case Rep. 2015 (2015) pii:bcr2014207663. [20] A. C. Thomas, Z. Zeng, J.-B. Rivière, R. O’Shaughnessy, L. Al-Olabi, J. St.-Onge, et al., Mosaic Activating Mutations in GNA11 andGNAQ Are Associated with Phakomatosis Pigmentovascularis and Extensive Dermal Melanocytosis, J. Invest. Dermatol. 136 (2016) 770–778.

19

Martins et al. [21] C. D. Van Raamsdonk, V. Bezrookove, G. Green, J. Bauer, L. Gaugler, J. M. O'Brien, Frequent somatic mutations of GNAQ in uveal melanoma and blue naevi, Nature 457 (2009) 599-602. [22] M. J. de Lange, L. Razzaq, M. Versluis, S. Verlinde, M. Dogrusoz, S. Bohringer, et al., Distribution of GNAQ and GNA11 Mutation Signatures in Uveal Melanoma Points to a Light Dependent Mutation Mechanism, PLoS One 10 (2015) e0138002. [23] U. M. Ayturk, J. A. Couto, S. Hann, J. B. Mulliken, K. L. Williams, A. Y. Huang, et al., Somatic Activating Mutations in GNAQ and GNA11 Are Associated with Congenital Hemangioma, Am. J. Hum. Genet. 98 (2016) 789-95. [24] B. R. Conklin, O. Chabre, Y. H. Wong, A. D. Federman, H. R. Bourne, Recombinant Gq alpha. Mutational activation and coupling to receptors and phospholipase C, J. Biol. Chem. 267 (1992) 31-4. [25] D. E. Coleman, E. Lee, M. B. Mixon, M. E. Linder, A. M. Berghuis, A. G. Gilman, et al., Crystallization and preliminary crystallographic studies of Gi alpha 1 and mutants of Gi alpha 1 in the GTP and GDP-bound states, J. Mol. Biol. 238 (1994) 630-4. [26] P. Svoboda, J. Teisinger, J. Novotny, L. Bourová, T. Drmota, L. Hejnová, Biochemistry of transmembrane signaling mediated by trimeric G proteins, Physiol. Res. 53 Suppl 1 (2004) S141-152. [27] E. L. Bodmann, V. Wolters, M. Bunemann, Dynamics of G protein effector interactions and their impact on timing and sensitivity of G protein-mediated signal transduction, Eur. J. Cell Biol. 94 (2015) 415-9. [28] N. Wettschureck, S. Offermams, Mammalian G proteins and their cell type specific functions, Physiol. Rev. 85 (2005) 1159-204. [29] W. M. Oldham, N. Van Eps, A. M. Preininger, W. L. Hubbell, H. E. Hamm, Mapping allosteric connections from the receptor to the nucleotide-binding pocket of heterotrimeric G proteins, Proc. Natl. Acad. Sci. U. S. A. 104 (2007) 7927-32. [30] J. D. Robishaw, C. H. Berlot, Translating G protein subunit diversity into functional specificity, Curr. Opin. Cell Biol. 16 (2004) 206-209. 20

Martins et al. [31] D. P. Siderovski, F. S. Willard, The GAPs, GEFs, and GDIs of heterotrimeric G-protein alpha subunits, J. Biol. Sci. 1 (2005) 51-66. [32] F.-X. Yu, J. Luo, J.-S. Mo, G. Liu, Y. C. Kim, Z. Meng, et al., Mutant Gq/11 promote uveal melanoma tumorigenesis by activating YAP, Cancer Cell 25 (2014) 822-830. [33] W. Tan, D. M. Nadora, L. Gao, G. Wang, M. C. Mihm Jr., J. S. Nelson, The Somatic GNAQ Mutation (R183Q) is Located within the Blood Vessels of Port Wine Stains, J. Am. Acad. Dermatol. 74 (2016) 380–383. [34] J. A. Couto, L. Huang, M. P. Vivero, N. Kamitaki, R. A. Maclellan, J. B. Mulliken, et al., Endothelial Cells from Capillary Malformations are Enriched for Somatic GNAQ Mutations, Plast. Reconstr. Surg. 137 (2016) 77e–82e. [35] P. M. Giguère, M. D. Rochdi, G. Laroche, E. Dupré, M. R. Whorton, R. K. Sunahara, et al., ARF6 activation by Galpha q signaling: Galpha q forms molecular complexes with ARNO and ARF6, Cell Signal. 18 (2006) 1988-1994. [36] G. Laroche, P. M. Giguère, É. Dupré, G. Dupuis, J. L. Parent, The N-terminal coiledcoil domain of the cytohesin/ARNO family of guanine nucleotide exchange factors interacts with Gαq, Mol. Cell Biochem. 306 (2007) 141. [37] J. H. Yoo, D. S. Shi, A. H. Grossmann, L. K. Sorensen, Z. Tong, T. M. Mleynek, et al., ARF6 is an actionable node that orchestrates oncogenic GNAQ signaling in uveal melanoma, Cancer cell 29 (2016) 889-904. [38] F. Zhou, C. Dong, J. E. Davis, W. H. Wu, K. Surrao, G. Wu, The mechanism and function of mitogen-activated protein kinase activation by ARF1, Cell Signal. 27 (2015) 2035–2044. [39] C. A. Jones, N. Nishiya, N. R. London, W. Zhu, L. K. Sorensen, A. C. Chan, et al., Slit2Robo4 signalling promotes vascular stability by blocking Arf6 activity, Nature Cell Biol. 11 (2009) 1325-1331. [40] M. R. Nance, B. Kreutz, V. M. Tesmer, R. Sterne-Marr, T. Kozasa, J. J. G. Tesmer, Structural and Functional Analysis of the Regulator of G Protein Signaling 2-Gq Complex, Structure 21 (2013) 438–448. 21

Martins et al. [41] V. G. Taylor, P. A. Bommarito, J. J. G. Tesmer, Structure of the Regulator of G Protein Signaling 8 (RGS8)-Gq Complex. Molecular basis for G-selectivity, J. Biol. Chem. 291 (2016) 5138–5145. [42] L. Bordoli, F. Kiefer, K. Arnold, P. Benkert, J. Battey, T. Schwede, Protein structure homology modeling using SWISS-MODEL workspace, Nat. Protoc. 4 (2009) 1-13. [43] N. Guex, M. C. Peitsch, SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling, Electrophoresis 18 (1997) 2714-2723. [44] S. Maere, K. Heymans, M. Kuiper, BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks, Bioinformatics 21 (2005) 3448-3449.

22

Martins et al. FIGURE LEGENDS Figure 1 – Clinical features and oral findings in a patient with SWS. A) A 9-year-old boy with unilateral (right side) facial port wine stain and mild upper-lip overgrowth. B) Mild gingival enlargement in the mucosa of the right upper lip, and loss of enamel and dentin without visible signs of exposed pulp tissue. C) Erythematous reddish pink patches were observed in the gingiva of the maxilla and mandible, the floor of the mouth, lips, cheeks, hard palate and ipsilaterally to the PWS. D) Blanching of the lesion under pressure. Bone overgrowth abnormalities evidenced by panoramic, cone-beam computed tomography (CBCT) and intraoral radiographs (E, F, and G, respectively) showing facial asymmetry, malocclusion, accelerated tooth exfoliation and eruption, and alveolar bone loss in the maxilla ipsilaterally to the PWS.

Figure 2 – In silico structure analysis of p.R183Q somatic mosaic mutation. The heterotrimeric G protein is composed of three subunits: α, β, and γ. GNAQ gene, affected by a somatic mosaic mutation p.R183Q in patients with SWS, encodes a guanine nucleotidebinding protein G protein subunit alpha q (Gαq). Schematic figure of functional domains of the Gαq subunit is shown in A. Ribbon representation of heterotrimeric G protein structure is shown in B. C) Superimposed 3D models from native (D) and mutant (E) Gαq subunit, showing conformational changes in molecule surface. The location of R183 and native and Q183 mutant residues (highlighted in yellow) are indicated by an arrow. The R183, E49, T54, G51, S50, A331 and K275 residues, predicted to form a hydrogen bond with GDP molecule, into the core of hydrophobic cleft, are highlighted in green. The images were obtained using PyMol software. Sticks models showing internal contacts for native (F) and mutant (G) Gαq proteins. Internal contacts and molecular interaction analysis for codon 183 was assessed by Swiss-PdbViewer. The residues predicted to form a hydrogen bond with GDP molecule (red stick) were displayed in the F and G figure. The hydrogen bond established between R183 and GDP molecule, which was eliminated when R183 native was replaced by Q183 mutant

23

Martins et al. residue is indicated by an asterisk (A). Carbon (gray), Hydrogen (green), nitrogen (blue), oxygen (red), hydrogen bond (green).

Figure 3 - Internal contacts and molecular interaction analysis for codon 209 of Gq assessed by Swiss-PdbViewer. The hydrogen bond established between Gq (blue and yellow) and G (cyan) subunits in the locus harboring the p.Q209L mutation was displayed in A and B, respectively. The internal contacts and molecular interactions between Gq (blue and yellow) and G (cyan) subunits which were eliminated when Q209 native was replaced by L209 mutant residue are indicated by an asterisk. The lower panel summarizes the interactions between the different subunits.

Figure 4 - Molecular interaction analysis in 3D models of native and mutant Gq in complex with RSG2 and RSG8 assessed by Swiss-PdbViewer. The hydrogen bond established between native and mutant Gq (blue) and RSG2 or RGS8 (magenta) in the locus harboring the p.Q209L mutation (highlighted in yellow) were displayed according to indicated in the figure. Q209, T187 and I189 residues from Gq were involved in Gq-RGS molecular interaction. The replacement of Q209 by L209 mutant residue abolished the hydrogen bonds between Gq Q209 residue and the N149 or N122 residue from RGS2 and RGS8, respectively (Figure 4). The abolished molecular interactions are indicated by an asterisk.

Figure 5 - Representation of the GNAQ-GNBs PPI network. PPI network information for GNAQ and GNBs (1, 2, 3 and 4) retrieved from BioGRID database were merged and organized in an Edge-Weighted Spring Embedded Layout. Nodes, representing Gq interactors (1o grade) in GNAQ network are highlighted in yellow. Gq-interacting proteins involved with biological processes which were exclusively over-represented in GNAQ

24

Martins et al. network were indicated in the figure. Biological processes over-represented in GNAQ or GNBs PPI networks are shown in B and C, respectively.

Figure 6 – Schematic representation of the regulatory cycle of activation and inactivation of heterotrimeric G proteins by GPCR. In the inactive state, GDP-Gαq is connected to the Gβγ dimer. The G protein-mediated signaling starts by ligand binding to GPCR, which in turn promote the exchange of bound GDP for GTP on the Gαq subunit. Then, conformational changes of Gq switch regions, allow that the inactive G-protein heterotrimeric complex detaches from the receptor and dissociates in GTP-Gαq and Gβγ dimer. Both, activated GTP-Gαq and Gβγ dimer would transmit the signals through their binding with different downstream effectors (such as adenylyl cyclase, phosphodiesterases, phospholipase C, and ion channels), and which will determine intracellular signaling responses. B) After signal transduction, inactivation of G proteins signaling cascade occurs as a result of intrinsic GTPase activity of Gα subunits, which leads to the conversion of bound GTP into GDP. RGS family molecules act accelerating this process. The formation of inactive G-protein heterotrimeric complex requires inactivation of ARF6, leading to Gq relocalization from the cytoplasm to the plasma membrane, where re-association of Gq and Gβγ subunits and their binding to the receptor is believed to occur. C) The mechanism by which Gq activating mutations (p.R183Q and p.Q209L) differentially controls signal intensity downstream to G-protein effectors may involve conformational changes in Gq molecule surface, affecting its intrinsic GTPase activity, and/or its association with RGS molecules and with the Gβγ dimer. Thus, as a result of the failure/reduction in the Gq inactivation processes, multiple downstream signaling pathways are over-activated, including ARF6mediated pathways (PLC/PKC, Rho/Rac, and YAP and b-catenin signaling) and those activated by Gβγ (Table 1). Figures B and C are based on recent experimental evidences including a figure displayed by Yoo et al. 2016 [37].

25

Martins et al.

26

Martins et al.

27

Martins et al.

28

Martins et al.

29

Martins et al.

30

Martins et al.

31

Martins et al.

Table 1 - GO terms differentially over-represented in GNAQ or GNBs PPI networks. GNAQ

GNB1

GO ID

Description

p-value

32012

Regulation of ARF protein signal transduction negative regulation of signal transduction negative regulation of signal process

1.05E06

cluster freq 5/55 9.0%

6.68E06

7.34E06

9968

23057

GNB2

GO ID

Description

50790

regulation of catalytic 3.36Eactivity * 06

cluster freq 17/75 22.6%

6/55 10.9%

43085

positive regulation of 5.24Ecatalytic activity 06

13/75 17.3%

7212

6/55 10.9%

51927

negative regulation of calcium ion transport via voltagegated calcium channel activity activation of adenylate cyclase activity

7.61E06

3/75 4.0%

42127

1.07E05

5/75 6.6%

44092

positive regulation of adenylate cyclase activity positive regulation of cyclase activity positive regulation of lyate activity adaptation of

1.17E05

5/75 6.6%

1.28E05 1.51E05 1.62E-

5/75 6.6% 5/75 6.6% 3/75

7190

45762

31281 51349 23058

p-value

GO ID

Description

8284

positive 2.20Eregulation of 06 cell proliferation dopamine 3.03Ereceptor 06 signaling pathway * regulation of 5.89Ecell 06 proliferation

negative regulation molecular function

p-value

cluster freq 13/83 15.6%

4/83 4.8%

17/83 20.4%

1.01Eof 05

11/83 13.2%

32

Martins et al.

7213

22401 2029

10863

7202

8624

10518

32413

1503 6468

signaling pathway muscarinic acetylcholine receptor signaling pathway negative adaptation of signaling pathway desensitization of Gprotein coupled receptor protein signaling pathway positive regulation of phospholipase C activity activation of phospholipase C activity induction of apoptosis by extracellular signals positive regulation of phospholipase activity negative regulation of ion transmembrane transporter activity ossification

05 1.62E05

4.0% 3/75 4.0%

1.62E05 1.62E05

3/75 4.0% 3/75 4.0%

1.92E05

5/75 6.6%

1.92E05

5/75 6.6%

2.12E05

6/75 8.0%

2.59E05

5/75 6.6%

2.94E05

3/75 4.0%

3.19E05 protein amino acid 3.28E-

6/75 8.0% 13/75 33

Martins et al.

10517

60193 16310 10517

60193 16310

phophorylation 05 regulation of 3.44Ephospholipase 05 activity positive regulation of 4.20Elipase activity 05 phosphorylation 4.99E05 regulation of 3.44Ephospholipase 05 activity positive regulation of 4.20Elipase activity 05 phosphorylation 4.99E05

17.3% 5/75 6.6% 5/75 6.6% 14/75 18.6% 5/75 6.6% 5/75 6.6% 14/75 18.6%

Over-represented GO term exclusivelly in one of G-protein subunit are highlighted in negrite. Over-represented GO term exclusivelly found in Gβ subunits are highlighted in italic. (*) indicate the over-represented GO terms observed in Gβ4. (*) GO term found to be over-represented in GNB4 subunit. GNB3 no showed no GO term diferentially over-represented compared to subunit encoded by GNAQ.

34