A functional study of disease-causing GNB1 mutations
Iulia Pirvulescu
Supervisor: Dr. Terence E. Hébert Department of Pharmacology and Therapeutics McGill University, Montréal June 2019
A thesis submitted to McGill University in partial fulfillment of the requirements of the degree of MASTER OF SCIENCE
© Iulia Pirvulescu 2019 Table of Contents
Abstract (English) ...... 1
Résumé (français) ...... 3
List of Abbreviations ...... 5
List of Tables and Figures...... 7
Acknowledgements ...... 8
1 ─ Introduction ...... 9
1.1 GPCRs...... 9 1.1.1 Pharmacological relevance ...... 9 1.1.2 Structure ...... 9 1.1.3 Heterotrimeric G protein activation ...... 10 1.2 Heterotrimeric G proteins ...... 11 1.2.1 Canonical functions of G ...... 12 1.2.1.1 Intracellular calcium release ...... 13 1.2.2 Noncanonical functions of G ...... 14
1.2.2.1 G1 in the nucleus ...... 15
1.3 Gβ1 mutations ...... 15 1.3.1 Genetic perspective ...... 17 1.3.2 Clinical phenotypes ...... 19 1.3.3 GNB1 Syndrome ...... 20 1.3.4 Cancer ...... 21 1.3.5 Pathways affected that have been studied ...... 22 1.4 Thesis objectives and rationale ...... 23
2 ─ Materials and Methods ...... 25
Reagents and Antibodies...... 25 Mutagenesis and cloning...... 26 Cell Culture and Transfection ...... 28 Immunofluorescence ...... 29 Cell Lysis and Protein sample preparation ...... 30 Western blotting ...... 30 Aequorin Assay ...... 31 Co-Immunoprecipitation ...... 32 Data Analysis ...... 33
3 ─ Results ...... 34
3.1 Creating siRNA-resistant constructs expressing Gβ1 ...... 34 3.2 Verifying the expression of the constructs in HEK 293 cells ...... 36 3.3 Verifying the resistance to knockdown by RNA interference ...... 38
3.4 Knockdown of the endogenous WT-Gβ1 can be rescued by overexpressing its siGβ1- resistant counterpart, in the aequorin assay ...... 41
3.5 Gβ1 mutations are categorized as causing gains or losses of function in the M3 mAChR pathway ...... 43
3.6 Gβ1 interaction with Gq is compromised by some of the mutations ...... 47
3.7 Gβ1 mutations impair interaction with RNA polymerase II ...... 50 3.8 Co-expression of a mutated and a WT allele has limited effects on protein complexes formed by the mutant ...... 53
4 ─ Discussion ...... 59
4.1 siGβ1-resistance as a model ...... 59
4.2 Mapping functional regions on the Gβ1 gene ...... 60 4.3 Factors affecting the severity of the disease ...... 66 4.4 Calcium signaling and disease ...... 68 4.5 Heterotrimer formation and cancer ...... 69 4.6 Transcriptional regulation ...... 71
5 ─ Concluding remarks ...... 73
References ...... 75
Abstract (English)
G protein-coupled receptors (GPCRs) represent the largest class of membrane receptors in eukaryotes. Activation of GPCRs by extracellular signals leads to conformational changes that activate the associated G protein heterotrimer, composed of the G and G subunits. Mutations in the G1 subunit have been implicated with a number of different cancers and neurodevelopmental disorders. We focused on a set of ten germline and somatic de novo G1 point mutations studying their effects in vitro, with a view toward functionally classifying them.
Our objectives were to map functional regions, and connect functional outcomes to clinical phenotypes. We hypothesized that disease-causing G1 mutations confer gains or losses of function that impact their interactions with partners and their effects on signalling pathways. We generated flag-tagged, siRNA-resistant versions of wildtype (WT) and mutated G subunits, to study them in a background of reduced endogenous G1 subunit expression.
Our first functional investigation was on intracellular calcium release in response to M3- mAChR stimulation, because calcium signaling has been linked to both cancer and neurological disorders. Previous work in the lab has shown that knockdown of the G1 subunit leads to a significant increase in intracellular calcium release in response to carbachol treatment.
Expression of the siRNA-resistant WT-G1 rescued the increase in calcium release caused by
WT-G1 knockdown. We were able to classify G1 as D76G and I80T resulted in a loss of function, whereas K57E, K78E and K89E exhibited a dominant negative effect, causing changes in baseline calcium signalling.
Next, we assessed whether interactions with Gq/11 and RNA polymerase II (RNAPII) are affected by mutations in G1. We used co-immunoprecipitation to identify which mutations
1 physically interact with Gq/11, the principal G subunit implicated in PLC activation. Only G1 mutants I269T, D76G and A11V maintained a strong interaction with Gq/11. This suggests that
G1 is involved in the PLC signaling pathway independently of a Gq/11 interaction, which supports previous work which has shown that G1 modulates calcium release by regulating the expression of G4. In fact, G plays an important role in transcription, occupying over 700 promoters and interacting with RNAPII. We used co-immunoprecipitation to verify if the G1 mutations were able to interact with RNAPII. We found that all of them were, however, none of the showed the same increase in the interaction seen with WT-G1 in response to M3 mAChR stimulation. In contrast, mutations D76G and K57E had a reduced interaction under carbachol treatment.
In conclusion, we investigated several interacting partners and signaling pathways downstream of G1, to classify G1 mutations as causing gains or losses of function. Our work helped map functional regions along the gene, and draw some links between the functional outcomes and clinical phenotypes caused by the mutations.
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Résumé (français)
Les récepteurs couplés aux protéines G (RCPGs) représentent la plus grande classe de récepteurs membranaires chez les eucaryotes. L'activation des RCPGs par des signaux extracellulaires conduit à des changements conformationnels qui activent l'hétérotrimère des protéines G associées, composé des sous-unités G et G. Des mutations de la sous-unité G1 ont été impliquées dans un certain nombre de cancers et des troubles du développement neurologique. Nous nous sommes concentrés sur un ensemble de dix mutations ponctuelles germinales et somatiques de novo G1, dans le but d’étudier leurs effets in vitro, en vue de leur classification fonctionnelle. Nos objectifs étaient de cartographier les régions fonctionnelles et de relier les résultats fonctionnels aux phénotypes cliniques. Nous avons émis l'hypothèse que les mutations G1 causant des maladies confèrent des gains ou des pertes de fonction qui ont une incidence sur leurs interactions avec les partenaires et leurs effets sur les voies de signalisation.
Nous avons généré des versions de type naturel (WT) et de sous-unités G1 mutées, marquées par flag et résistantes au siRNA, afin de les étudier dans un contexte d'expression de sous-unité
G1 endogène réduite.
Notre première étude fonctionnelle portait sur la libération de calcium intracellulaire en réponse à la stimulation M3-mAChR, car la signalisation du calcium a été démontrée liée au développement des cancers et des troubles neurologiques. Des travaux antérieurs dans notre laboratoire ont montré que l'inactivation de la sous-unité G1 entraîne une augmentation significative de la libération de calcium intracellulaire en réponse au traitement avec le carbachol. Cet effet a été renversé par la surexpression du Gβ1-WT résistant au siRNA. Nous avons pu classer G1 dans les catégories D76G et I80T entraînant une perte de fonction, alors
3 que K57E, K78E et K89E présentaient un effet négatif dominant, provoquant des changements dans la libération basale de calcium.
Ensuite, nous avons évalué l’incidence des mutations de G1 sur les interactions avec
Gq/11 et l'ARN polymérase II (ARNPII). Nous avons utilisé la co-immunoprécipitation pour identifier les mutations qui interagissent physiquement avec Gq/11, la principale sous-unité G impliquée dans l'activation de la phospholipase C (PLC). Seuls les mutants G1, I269T, D76G et
A11V ont maintenu une interaction forte avec Gq/11. Cela suggère que G1 est impliqués dans la voie de signalisation de la PLC indépendamment de Gq/11, ce qui concorde avec des travaux précédents qui ont montré que G1 module la libération de calcium en régulant l'expression de
G4. En effet, G joue un rôle important dans la transcription, occupant plus de 700 promoteurs et interagissant avec l’ARNPII. Nous avons utilisé la co-immunoprécipitation pour vérifier si les mutations G1 étaient capables d'interagir avec ARNPII. Nous avons constaté qu’elles l’étaient toutes, cependant, elles ne présentaient pas la même augmentation d'interaction observée avec
WT-G1 en réponse à la stimulation de M3 mAChR. En revanche, les mutations D76G et K57E montraient une interaction réduite sous traitement au carbachol.
En conclusion, nous avons étudié plusieurs partenaires en interaction et voies de signalisation en aval de G1, afin de classer les mutations de G1 entraînant des gains ou des pertes de fonction. Grace à cette étude, nous avons pu cartographier les régions fonctionnelles le long du gène et établir des liens entre les résultats fonctionnels et les phénotypes cliniques causés par les mutations.
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List of Abbreviations
BSA Bovine serum albumin cAMP Cyclic adenosine monophosphate
BRET Bioluminescence resonance energy transfer
CMV Cytomegalovirus
DAG Diacylglycerol
DMEM Dulbecco’s Modified Eagle Medium 1X
DMSO Dimethyl sulfoxide
EDTA Ethylene diamine tetraacetic acid
EGTA Ethylene glycol bis (2-aminoethyl) tetraacetic acid
ER Endoplasmic reticulum
FBS Fetal bovine serum
GDP Guanosine diphosphate
GNB1 Guanine nucleotide-binding protein subunit beta-1
GPCR G protein-coupled receptors
GTP Guanosine triphosphate
HRP Horseradish peroxidase
IP3 Inositol 1,4,5-triphosphate
K2HPO4 Potassium phosphate
Kir3 Inwardly rectifying potassium channel 3
M3 mAChR M3 muscarinic acetylcholine receptor
MAPK Mitogen-activated protein kinase
5 mRNA Messenger RNA
Na2HPO4 Sodium phosphate
NaCl Sodium chloride
NP-40 Nonidet P-40
PBS Phosphate-buffered saline
PFA Paraformaldehyde
PI3K Phosphoinositide 3 kinase
PLC Phospholipase C
PVDF Polyvinylidene difluoride
RNAPII RNA polymerase II
RT Room temperature
SDS Sodium dodecyl sulfate siGβ1 Human GNB1 siGenome siRNA
Tris Tris (hydroxymethyl) aminomethane
WT Wildtype
ΔΔG Change in Gibbs Free Energy
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List of Tables and Figures
Figure 1. Schematic representation of the aequorin assay in the context of M3-mAChR activation ...... 14 Figure 2. Identified disease-causing GNB1 mutations to date ...... 17 Table 1. Primers used for mutagenesis and cloning ...... 28
Figure 3. Design and incorporation of the siG1-resistant sequence ...... 35
Figure 4. siG1-resistant mutants are expressed in 293-Aeq cells ...... 37
Figure 5. siGβ1-resistant sequence confers protection from siRNA-mediated knockdown ..... 40
Figure 6. Overexpression of the siGβ1-resistant WT-Gβ1 rescues the M3-mAChR-mediated increase in calcium release caused by Gβ1 knockdown ...... 42 Table 2. Categorization of mutations based on predicted effect on calcium release in response to M3-mAChR activation ...... 45
Figure 7. Gβ1 mutations are categorized based on their role in the M3-mAChR pathway ...... 47
Figure 8. The interaction between Gβ1 and Gq is disrupted by some of the mutations ...... 49
Figure 9. The interaction between Gβ1 and RNA polymerase II is disrupted by some of the mutations ...... 52
Figure 10. Knockdown of the endogenous Gβ1 doesn’t affect the state of the interaction between Gq and the WT-Gβ1 or the mutations I269T and K78E ...... 55
Figure 11. Knockdown of the endogenous Gβ1 dulls the state of the interaction between RNA polymerase II and the WT-Gβ1 or the mutations I269T and K78E ...... 57
Figure 12. Illustration of the functional outcomes of our Gβ1 mutations in terms of their localization on the gene...... 63
Table 3. Predicted G protein stability in response to Gβ1 mutations...... 65
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Acknowledgements
My biggest and most sincere thank you goes to my supervisor, Dr. Terry Hébert. I feel more than honored that he believed in me and gave me the opportunity to pursue this project. His unwavering support since the beginning has motivated me and helped me get through the best and through the slowest days. As well, his passion for educating and making the world a better place have inspired me and helped me set my own goals for the future. In a similar light, I also wish to acknowledge the community of parents of children with GNB1 mutations, for their dedication, which has motivated me and made me feel like my work mattered.
I also want to thank my advisor, Dr. Paul Clarke and the members of my committee, Dr. Jean-François Trempe and Dr. Jason Tanny. They have helped me see my project from a new angle, and their feedback and support have greatly improved my work and my thesis. A special thank you to the Department of Pharmacology, and in particular Dr. Bernard Robaire and Ms. Tina Tremblay, as well as Dr. Paul Clarke for their support throughout the many adventures of my Master’s degree!
The members of the Hébert lab have made every day feel full of promise, which has made it a wonderful work environment. They have been encouraging, entertaining and they have given me invaluable feedback. I am truly grateful to have gotten to know them and to have worked alongside them all. They have helped me develop my critical thinking and have made me a better scientist. It goes without saying that their kindness and friendship have made my time at the lab amazing.
I wish to thank and give special acknowledgements to Dr. Rory Sleno for creating the siRNA-resistant primers, to Darlaine Pétrin and Xinwen Zhu for creating the flag-tagged mutated
G1 constructs, to Dr. Clarke for helping me find the best way to statistically analyze the aequorin assay data, and to Dr. Nourhen Mnasri for helping me write the French résumé. Thank you also to Sindy Zheng for teaching me how to perform the aequorin assay and to Celia Bouazza for teaching and helping me troubleshoot my co-immunoprecipitations. Finally, thank you again to Dr. Hébert for editing my thesis.
Lastly, I couldn’t have done this without the support from my parents, my best friends, and my husband Michael. I want to share this achievement with you.
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1 ─ Introduction
1.1 GPCRs
1.1.1 Pharmacological relevance
Chemical signaling is at the root of biological functions at all levels, from within a single cell to an entire organism. Cells, tissues and organs interact and carry out their functions by communicating with each other, as well as carry signals within their compartments. Cells are able to receive extracellular signals via their membrane receptors, channels and transporters. The concept of receptors originated in the early 20th century, and has become an important concept in pharmacology in general (Rang 2006).
G protein-coupled receptors (GPCRs) represent the largest class of signaling receptors in eukaryotes. They are among the most studied and the most extensively modelled receptors and, in fact, GPCRs compose approximately 35% of drug targets (Sriram and Insel 2018; Rang 2006).
A deep knowledge of the diverse functions of these receptors, across organs and cell types, is critical in understanding human physiology and the pathology of countless disorders.
1.1.2 Structure
GPCRs detect the extracellular binding of a ligand, and can activate signaling cascades intracellularly, through the use of a transducer, the G protein. Over 1000 different GPCRs have been identified in humans and they are divided into 6 families and 64 subfamilies, based on their pharmacological properties. The ligands of GPCRs range in variety from hormones, small peptides, full proteins, amines, neurotransmitters, ions, odorants and photons.
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The core structure of GPCRs can be divided into three parts. On the extracellular side are found three extracellular loops and the N terminal domain, which modulate ligand access and binding. Second are 7 transmembrane domains, typical of GPCRs, which form the structural core and transmit information to the intracellular region via conformational changes. Finally, on the intracellular side there are three intracellular loops, one intracellular helix and the C terminus.
This is the region which interacts with the G protein and cytosolic signaling proteins
(Venkatakrishnan et al. 2013).
1.1.3 Heterotrimeric G protein activation
The G protein transduces signals received extracellularly by the GPCRs into intracellular signals carried out by second messengers. The G protein is composed of the alpha (G), beta
(G) and gamma (G) subunits, where the latter two form a stable dimer named G. There is an array of isoforms of each subunit; there are 18 different G subunits, 5 different G subunits and
12 different G subunits (Syrovatkina et al. 2016). This allows a great number of possible heterotrimeric combinations, which allows the G protein to mediate the diversity of signaling pathways found downstream of GPCR activation. GPCRs regulate their effector functions by signalling through the specific G subunits they are coupled to. The G subunits are divided into four subclasses based on sequence homology and function (Syrovatkina et al. 2016). Briefly, Gs activates adenylyl cyclase to produce cyclic adenosine monophosphate (cAMP). Conversely, Gi inhibits production of cAMP from ATP. Gq activates phospholipase C (PLC), which leads to the release of calcium ions from the endoplasmic reticulum. Finally, G12, the most recently characterized member, is found to activate Rho GTPases. (Birnbaumer 2007)
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As per the common mechanism of activation of heterotrimeric G proteins, upon extracellular binding of an agonist, the GPCR undergoes conformational changes which trigger the replacement of guanosine diphosphate (GDP) for guanosine triphosphate (GTP) in the G subunit. This, in turns, causes full or partial dissociation of the G protein subunit G from G.
Then, both the GTP-bound G and G can signal through downstream cascades and interact with effector proteins, cellular enzymes generating second messengers at the membrane, and throughout the cell (Galés et al. 2006). Eventually, and under certain circumstances with the aid of GTPase-activating proteins like RGS proteins, the G subunit will hydrolyze the attached
GTP to GDP, allowing it to re-associate with G ready for another cycle of activation of the
GPCR (Sprang, Chen, and Du 2007).
1.2 Heterotrimeric G proteins
Heterotrimeric G proteins signal through a wide range of downstream effectors, including adenylyl cyclase, ion channels, phospholipase C isoforms and protein and lipid kinases. Of the three subunits that form the heterotrimeric G protein, G has, for a long time, been the most extensively studied. The other two, G and G form the obligate dimers termed G which has also been associated with many canonical functions at the cell surface. More recently, G has also been found to have diverse noncanonical effectors in several subcellular locations, most notably in the nucleus (Khan et al. 2013).
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1.2.1 Canonical functions of G
When the G protein is inactive, the G dimer can act as a negative regulator of G. This was considered to be the primary role of G for some time. However, it has since been found to regulate many effectors at the cell surface, and I will briefly discuss the most important ones. In particular, the first direct G effector identified was Kir3, a cardiac muscarinic-gated inwardly rectifying potassium channel. G binding sites have been identified at both the N- and C- termini of the channel. G binding leads to Kir3 activation causes an outward flux of potassium ions, leading to cell hyperpolarization (Logothetis et al. 1987; He et al. 2002). Another important effector of G are voltage-dependent calcium channels, which open upon cell membrane depolarization and mediate calcium ion influx across the cell membrane. The efficacy of activation or inhibition is linked to the specific G isoform and the calcium channel subunit and isoform (De Waard et al. 2005). G also regulates intracellular calcium release by regulating phospholipase C (PLC), which will be discussed more in depth in the following subsection.
Another canonical G effector, which also interacts with several G subunits, is adenylyl cyclase, the enzyme responsible for catalysis of ATP into cAMP. Once again, G interaction may have either activating or inhibiting effects on adenylyl cyclase activity depending on the specific isoform (Bayewitch et al. 1998). G also interacts with kinases such as phosphoinositide 3 kinase (PI3K) and mitogen-activated protein kinase (MAPK), both of which are capable of initiating further trophic signaling cascades (Kerchner et al. 2004; Rozengurt
1998).
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1.2.1.1 Intracellular calcium release
As previously stated, G subunits are able to activate PLC, which, upon activation, can lead to the cleavage of PIP2 into diacylglycerol (DAG) and inositol 1,4,5-triphosphate (IP3).
DAG activates the kinase PKC, while IP3 diffuses to the endoplasmic reticulum (ER) where it binds the IP3 receptor and leads to intracellular calcium release from calcium stores within the
ER. Different isoforms of G and G were found to have differential effects on the magnitude of
PLC activation (Poon, Chan, and Wong 2009). In fact, work in our lab has identified that G41 is the dimer associated with the M3 muscarinic acetylcholine receptor (M3 mAChR) in HEK 293 cells (Khan et al. 2015). Using the aequorin assay, we also found that knocking down G1 leads to an increase in intracellular calcium release from the ER. The aequorin assay (Figure 1) is a bioluminescent assay which detects calcium ion release through the use of apoaequorin, a calcium-activated photoprotein isolated from the hydrozoan Aequorea victoria. Apoaequorin sequesters coelenterazine until calcium ions are released, at which point the free coelenterazine releases light at a frequency of 469nm, measured on a plate reader (Mithöfer and Mazars 2002).
Studies using this assay have reinforced the role that G1 plays in the regulation of gene expression, which are discussed in the next section.
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Figure 1. Schematic representation of the aequorin assay in the context of M3-
mAChR activation The aequorin assay enables light emission upon the release of
calcium ions from the endoplasmic reticulum.
1.2.2 Noncanonical functions of G
More recently, a number of noncanonical functions have been attributed to the G dimer in distinct subcellular compartments. These include endosomes (cell survival and proliferation through Akt activation), mitochondria (mitochondrial aggregation), the endoplasmic reticulum
(calcium release through IP3 receptors, independently of PLC), the Golgi apparatus
(anterograde protein trafficking) and the cytoskeleton (microtubule stability and cell migration).
Additionally, some of the most important new effectors of G signalling are found in the
14 nucleus, and these include RNA polymerase II, histone deacetylases and transcriptional factors.
(Khan et al. 2013; Khan et al. 2018)
1.2.2.1 G1 in the nucleus
Despite lacking a DNA-binding domain, G1 has been attributed roles in regulating gene expression. The G1 protein is encoded by the guanine nucleotide-binding protein subunit beta-1
(GNB1) gene. It was found on the promoters of over 700 genes, including G4, and it directly interacts with transcription factors such as Fos of the activator protein-1 complex (Khan et al.
2015; Robitaille et al. 2010). Moreover, knockdown of G1, under basal conditions of following stimulation with angiotensin II, lead to the upregulation of dozens of genes involved in the fibrotic response. Aiming to elucidate these mechanisms, recent work in our lab has uncovered
RNA polymerase II (RNAPII) as an unexpected but consequential interactor of G1. This interaction has been detected following activation of the angiotensin type I receptor and the M3 mAChR, in multiple cell types (Khan et al. 2018). The profound involvement of G1 in the regulation of so many genes greatly amplifies the number of signaling pathways and functions that G1 plays throughout the cell.
1.3 Gβ1 mutations
The natural occurrence of mutations in living organisms is the primary mechanism driving evolution. On the flip-side, it can also leads to the development of devastating diseases.
Fortunately for us, our DNA is filled with noncoding regions of no discernible function, meaning
15 that most randomly-localized mutations will not have functional effects. Nonetheless, mutations occur regularly in coding regions of the genome, leading to phenotypes that vary in severity.
Small scale mutations affect few nucleotides or even, in the case of point-mutations, a single nucleotide. Point-mutations can be caused by insertions, deletions or substitutions. Unless they are silent, they can have severe impacts on protein sequences by causing frame-shifts or leading to nonsynonymous substitutions, meaning that the original codon will be replaced by a codon that codes for a different amino acid, modifying the amino acid sequence and, in turn, affecting the folding of the protein into the three-dimensional structure it needs to carry out its function
(Hamdan et al. 2014).
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1.3.1 Genetic perspective
Figure 2. Identified disease-causing GNB1 mutations to date
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Two views of the molecular representation of the G protein heterotrimer composed of
Gi1 (gold), G1 (green) and G2 (silver) subunits, based on a crystal structure (PDB 1GP2) (Wall et al. 1995). Corresponding sites of cancer-causing mutations are colored in red, in blue are indicated mutations associated with the GNB1 Syndrome, and the mutations designated in black are found in patients with either disease. Compilation of mutations from publications (Yoda et al. 2015; Petrovski et al. 2016; Brett et al. 2017; Zimmermannova et al. 2017; Lohmann et al. 2017; Hemati et al. 2018; Szczaluba et al. 2018) and unpublished communications from affected families.
Mutations occurring in GNB1, the gene coding for the G1 subunit of the G protein, have recently been described. In Figure 2, we have mapped every known disease-causing GNB1 mutation, illustrating their locations along G1, near sites of interaction with the G and G subunits. About 60 different point mutations have been identified, affecting 36 residues (Yoda et al. 2015; Petrovski et al. 2016; Brett et al. 2017; Zimmermannova et al. 2017; Lohmann et al.
2017; Hemati et al. 2018; Szczaluba et al. 2018). Somatic mutations have been found in cancer patients, whereas germline mutations are associated with a neurodevelopmental disorder named the GNB1 Syndrome. As seen in Figure 2, most mutations found around the G-interacting sites are cancer-causing, and most germline mutations are found around the G-interacting sites. A few mutations are explicitly found to be inherited in an autosomal dominant manner, some had an undeterminable mode of inheritance, and most mutations occurred de novo (Lohmann et al.
2017).
It is interesting to note that there are other instances of cancer-causing mutations in key components of pathways which are also known to be responsible for developmental disorders.
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Examples include BRAF and genes associated with the PI3K-Akt-mTOR pathway (Forbes et al.
2014; Petrovski et al. 2016).
1.3.2 Clinical phenotypes
The GNB1 mutations exhibit very different effects depending on the time at which the mutation occurred. The most important consequences are cancer and neurodevelopmental disorders, as will be discussed further in this section. Interestingly, a 13-year old male patient with a mutation in G77A, was diagnosed with both GNB1 Syndrome as well as acute lymphoblastic leukemia, the latter of which has been successfully responsive to chemotherapy
(Brett et al. 2017).
A series of co-morbidities have been associated with GNB1 mutations. The first attempt at associating GNB1 mutations with diseases relates to the G1 subunit’s function in rod transducin, a G protein that responds to activated opsin and mediates an intermediary step in phototransduction. So far, two groups have hypothesized that disrupted G1 function could be associated with retinal degeneration in humans, and diseases such as retinitis pigmentosa
(Mylvaganam et al. 2006; Perkins et al. 2019). Another rare disorder that appears more common among patients with G1 mutations is cutaneous mastocytosis, which may be explained by disrupted GPCR signaling in mast cells. It could also be an incidental finding, although cutaneous mastocytosis was diagnosed in 11% of patients with germline mutations, compared to an approximately 0.01% prevalence in the general population (Hemati et al. 2018; Szczaluba et al. 2018). Some other co-morbidities that have been detected at an unusual frequency in patients
19 with G1 mutations are cleft palate and genitourinary anomalies in men (Hemati et al. 2018;
Brett et al. 2017).
1.3.3 GNB1 Syndrome
It is widely documented that about three mutations occur each time a normal human stem cell divides (Tomasetti, Li, and Vogelstein 2017). Additionally, men transmit a higher rate of mutations to their offspring than women do. One group found that the age of the father was the dominant factor in determining the number of a child’s de novo mutations. The average mutation rate is about 1.2 x10-8 for fathers aged 29.7 years, and the rate goes up about two mutations per year (Kong et al. 2012).
Germline de novo point mutations in the GNB1 gene has been associated with a new neurodevelopmental disorder named the GNB1 Syndrome. It is a rare disease, with just over 80 known cases, first identified in 2016. All the patients exhibit global developmental delay, a diagnosis which indicated lower than average intellectual functioning, and a delayed achievement of physical milestones. The second most common symptom, affecting approximately 78% of patients is hypotonia. The most severe and life-threatening condition, affecting over 50% of patients, is the development of seizures, including generalized, focal, mixed and infantile spasms. Some other common symptoms include ophthalmological anomalies
(70%), nonverbal patients (60%), abnormal vision (58%), inability to walk independently (48%), growth delays (46%), speech delays (40%), autism (18%), dystonia (17%), and cardiovascular defects (11%) (Brett et al. 2017; Hemati et al. 2018; Lohmann et al. 2017; Petrovski et al. 2016;
Steinrucke et al. 2016; Szczaluba et al. 2018).
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1.3.4 Cancer
Three types of mutations that have been associated with cancer initiation: inherited, replicative, and induced by environmental factors. Of them, mutations resulting from DNA replication errors are the most common types of driver gene mutations in women with cancer
(Tomasetti, Li, and Vogelstein 2017).
GNB1 mutations have been identified in close to 100 cancer patients
(https://cancer.sanger.ac.uk/cosmic/gene/analysis?ln=GNB1). Analyses of publicly available databases and reports across tumor types revealed that G1 mutations occur in approximately
0.5-2% of cases of myelodysplastic syndrome or secondary acute myeloid leukemia.
Interestingly, some mutations clustered on the basis of lineage. For instance, all K57E mutations were found in myeloid neoplasms, and half of I80 mutations were found in B cell neoplasms. In any case, leukemia and lymphoma are the most common types of cancer resulting from G1 mutations (Yoda et al. 2015).
The difficulty lies in determining if these are cancer-causing mutations, or whether they occurred coincidentally. So far, this question has been investigated by overexpressing these mutated genes in models that are easier to study, both in vivo and in vitro, and examining the effect onto pathways linked to cancer. One group has found that certain patient-derived G1 mutations in Cdkn2a-deficient mouse bone marrow followed by transplantation resulted in myeloid or B cell malignancies. They also determined that co-expression of G1 mutants with certain oncogenic kinase alternations results in kinase inhibitor resistance (Yoda et al. 2015).
This reinforces the fact that studying these mutations can provide the patients with useful insight into disease mechanisms and help identify druggable targets.
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1.3.5 Pathways affected that have been studied
The G1 mutations that we are studying only started being described in the past few years, yet, some work has been done to identify which pathways are affected. Several groups have investigated, using bioluminescence resonance energy transfer (BRET) assays or co- immunoprecipitation, whether G1 mutants lose the interaction with G, which would compromise the integrity and function of the heterotrimer. Interestingly, several mutations have been found to interfere with this interaction. Residues K57, I80, K89, A92 were experimentally found to be involved in the G-G1 interaction. Alternatively, of those tested, only residues G64 and A106 were found to weaken the interaction with G. Residues R52 and D118, although not interfering with heterotrimer formation, were found to cause deficits in G protein activation following GPCR stimulation (Lohmann et al. 2017; Yoda et al. 2015).
One group has also investigated the activity of pathways downstream of GPCR stimulation, through gene-expression profiling and gene-set enrichment analysis. They found that
G1 mutations can activate canonical signaling downstream of G protein activation. In particular,
TF-1 cells expressing the G1 mutation K89E caused an enrichment in the signatures of Akt- mTOR-FOXO3, Ras-MAPK and PLC. They also found increased phosphorylation of a PI3K substrate, MAPK signaling proteins and mTOR substrates in cells expressing the G1 mutations
K57E/T, I80N/T and K89E (Yoda et al. 2015). Such studies provide useful insights into the pathology and mechanism of action of the mutations.
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1.4 Thesis objectives and rationale
There is insuficient information available to explain why mutations in certain G1 residues cause severe diseases such as cancer and the GNB1 Syndrome. The objectives of my project were to map functional regions across the G1 subunit, as well as draw links between the functional outcome of the mutations and the clinical phenotypes exhibited by the patients.
Studying these mutations would provide very useful information to the patients, their doctors, and to fellow researchers working on the GNB1 gene and associated diseases. A better understanding of the disease mechanisms will lead to a better understanding of patient symptoms and of the diverse functions of G1. So far, many patients are incorrectly diagnosed with other syndromes, such as autism, and thus are being inappropriately cared for. It is also important for their doctors to be aware of the increased risk of malignancy of some of these mutations. As other groups have shown, mutations in different residues causes effects seen on different downstream pathways as well as interference with known interactors. This reinforces a need for personalized medicine, to have treatments tailored to each patient based on their genetic profile.
Identifying specific druggable targets would facilitate the process for the more severe diseases such as cancer and the prevalence of seizures. In fact, some mutations were found to cause resistance to tyrosine kinase inhibitors, whereas others were susceptible to small molecule inhibitors of the PI3K and mTOR pathways.
To work towards our objectives, we hypothesized that disease-causing G1 mutations confer gains and losses of function that impact their interactions with partners and their effects on signalling pathways. We selected ten mutations to focus on: A11V, K57E, D76G, K78E, I80T,
K89E, A92T, M101V, D118G and I269T. We chose them because they are spread throughout
23 the gene, although most of them are found on and around exon 6, suspected to contain the residues with the most important functions (Brett et al. 2017; Petrovski et al. 2016).
Our first step was to create a model in which we could functionally assess the G1 mutants.
We built pcDNA vectors containing flag-tagged, siRNA-resistant copies of WT and mutated
G1. We used these constructs to test whether the mutants are able to rescue the increase in intracellullar calcium release upon carbachol stimulation of the M3 mAChR , when knocking down the endogenous G1. We also studied the interaction of G1 and Gq/11, to determine whether the mutants might interfere with the formation of the heterotrimer. Finally, we initiated an investigation on the ability of the G1 mutants to carry out the WT role in the regulation of gene expression, by determining if the mutants are able to interact with RNAPII.
24
2 ─ Materials and Methods
Reagents and Antibodies
Reagents were obtained from the following sources: high glucose Dulbecco’s Modified
Eagle Medium 1X (DMEM), phenol-free DMEM, fetal bovine serum (FBS), penicillin/streptomycin and sodium dodecyl sulfate (SDS) were from Wisent (St-Bruno, QC).
The antibiotic G418 sulfate (G418), bovine serum albumin (BSA), Tris (hydroxymethyl) aminomethane (Tris), glycine, ethylene diamine tetraacetic acid (EDTA), ethylene glycol bis (2- aminoethyl) tetraacetic acid (EGTA) and skim milk powder were obtained from BioShop Canada
(Burlington, ON). Blasticidin, zeocin, Lipofectamine 2000, anti--tubulin (used 1:4000 for western blotting) and anti-mouse antibody conjugated with Alexa-488 (used 1:500 for immunofluorescence) came from Invitrogen (Carlsbad, CA). From Sigma (St-Louis, MO) were obtained the following reagents: carbachol, anti-flag M2 antibody (used 1:4000 for western blotting and 1:500 for immunofluorescence), anti-rabbit conjugated with horseradish peroxidase
(HRP) (used 1:20000 for western blotting), anti-mouse conjugated with HRP (used 1:20000 for western blotting), flag M2 magnetic beads, 3X flag peptide, 2-mercaptoethanol, dimethyl sulfoxide (DMSO) potassium phosphate (K2HPO4), Nonidet P-40 (NP-40), sodium deoxycholate, Tween-20, the Hoechst nuclear stain (used 1:10000 for immunofluorescence), protease inhibitor cocktail and paraformaldehyde (PFA). Sodium chloride (NaCl), glycerol, sodium phosphate (Na2HPO4), methanol and 96-well optical-bottom plates came from Fisher
Scientific (Hampton, NH). The Bio-Rad protein assay dye reagent concentrate and polyvinylidene difluoride (PVDF) membranes were from Bio-Rad (Hercules, CA). The ECL
Select western blotting detection reagent came from GE Healthcare (Chicago, IL).
Coelenterazine h came from Nanolight Technology (Pinetop, AZ), anti-RNA polymerase II
25 clone CTD4H8 (targeting the RPB1 subunit of the RNA polymerase II) (used 1:2000 for western blotting) came from Milipore (Burlington, MA), anti-Gq/11 (used 1:2000 for western blotting) came from Santa Cruz (Dallas, TX), human GNB1 siGenome siRNA (siGβ1) was from
Dharmacon (Lafayette, CO), the BLUelf prestained protein ladder was from FroggaBio (North
York, ON), and potassium chloride (KCl) came from BioBasic Canada (Markham, ON).
Forward and reverse primers were ordered from Integrated DNA Technologies (Coralville, IA).
Pfu DNA polymerase was from Agilent Technologies (Santa Clara, CA). The restriction enzyme
DpnI was obtained from New England Biolabs (Ipswich, MA).
Mutagenesis and cloning
Gβ1 mutations and the siG1-resistant sequences were incorporated into a pcDNA3.1(+) vector expressing flag-Gβ1 by QuikChange PCR, as previously described with minor modifications (Ebili et al. 2017). Briefly, the PCR reactions were set up in a final volume of 50 ul, containing 20 ng template, 1 μM primer pair (sequences listed in Table 1), 200 μM dNTPs, 3 units of Pfu DNA polymerase, 1X PCR Buffer and 3% DMSO. The PCR cycles were initiated at
95°C for 5 minutes, followed by 18 amplification cycles. Each amplification cycle consisted of
95°C for 30 seconds and 55°C for 1 minute. The PCR cycles were finished with an annealing step at 72°C for 4 minutes and an elongation step at 72°C for 10 minutes. The PCR products were treated with the restriction enzyme DpnI at 37°C for 2 hours to digest the methylated DNA of the template. The incorporations were confirmed by sequencing.
26
The siGβ1-resistance primer pair was designed by Dr. Rory Sleno, and the Gβ1 mutant constructs were designed and created by Ms. Darlaine Pétrin and Ms. Xinwen Zhu, using the primer pairs in Table 1.
5’- GGAAAGCATGTGCAGATGCCACGTTGAGTCAAATTACA Forward AACAACATCGACCC -3’ siG1- Resistance 5’- GGGTCGATGTTGTTTGTAATTTGACTCAACGTGGCATCT Reverse GCACATGCTTTCC -3’
Forward 5’- CTCCCATGACAACACCATCTGCGGGATCAC -3’ Mutation I 269 T Reverse 5’- GTGATCCCGCAGATGGTGTTGTCATGGGAG -3’
Forward 5’- CCTGCGGTGGCCTGGGTAACATTTGCTCCATTTAC -3’ Mutation D 118 G Reverse 5’- GTAAATGGAGCAAATGTTACCCAGGCCACCGCAGG -3’
Forward 5’- CGCTCCTCCTGGGTCGTGACCTGTGCATATGC -3’ Mutation M 101 V Reverse 5’- GCATATGCACAGGTCACGACCCAGGAGGAGCG -3’
Forward 5’- CCACCAACAAGGTCCACACCATCCCTCTGCGCTCC -3’ Mutation A 92 T Reverse 5’- GGAGCGCAGAGGGATGGTGTGGACCTTGTTGGTGG -3’
Forward 5’- GCTACACCACCAACGAGGTCCACGCCATC -3’ Mutation K 89 E Reverse 5’- GATGGCGTGGACCTCGTTGGTGGTGTAGC -3’
Forward 5’- GCAGGATGGTAAACTTACCATCTGGGACAGCTAC -3’ Mutation I 80 T Reverse 5’- GTAGCTGTCCCAGATGGTAAGTTTACCATCCTGC -3’
Forward 5’- GCCTCGCAGGATGGTGAACTTATCATCTGGG -3’ Mutation K 78 E Reverse 5’- CCCAGATGATAAGTTCACCATCCTGCGAGGC -3’
27
Forward 5’- CGTCAGTGCCTCGCAGGGTGGTAAACTTATCATC -3’ Mutation D 76 G Reverse 5’- GATGATAAGTTTACCACCCTGCGAGGCACTGACG -3’
Forward 5’- CGGGGGCACCTGGCCGAGATCTACGCCATGCAC -3’ Mutation K 57 E Reverse 5’- GTGCATGGCGTAGATCTCGGCCAGGTGCCCCCG -3’
Forward 5’- CCAGTTACGGCAGGAGGTCGAGCAACTTAAGAACC -3’ Mutation A 11 V Reverse 5’- GGTTCTTAAGTTGCTCGACCTCCTGCCGTAACTGG -3’
Table 1. Primers used for mutagenesis and cloning
Cell Culture and Transfection
Flp-In T-Rex-HEK 293 cells stably expressing apoaequorin (293-Aeq) were cultured in
DMEM supplemented with 5% (v/v) FBS, 1% (v/v) penicillin/streptomycin, 15 μg/ml blasticidin, 10 μg/ml zeocin and 700 μg/ml G418. This previously-characterized cell line was a generous gift from Jonathan Javitch (Han et al. 2009). In preparation for transfection, 293-Aeq cells were plated and allowed to attach at least 24 hours, until 30% confluent. Transient transfection of DNA and/or siRNA proceeded using Lipofectamine 2000 (1 μg:2 μL ratio of
DNA:Lipofectamine 2000; 6.25 nM:1 μL siRNA:Lipofectamine 2000, according to manufacturer’s protocol) in pure DMEM. The transfection media was removed 5 hours later and replaced with the cells’ regular media, with 5% FBS and the antibiotics specified above. The cells were left for 48 hours to allow expression when transiently transfected with only DNA.
When transiently transfected with siRNA, the cells were left for 72 hours. The DNA constructs used were the WT and mutated Gβ1, and the negative control was the empty vector pcDNA. As
28 for siRNA, we used human siGβ1 to knock down the subunit, and the non-targeting human siCtl as a negative control.
Immunofluorescence
Transient transfection of 1 μg flag-tagged, siGβ1-resistant WT and mutated DNA constructs was performed on 293-Aeq cells in 6-well plates. The next day, 15 000 cells were replated, in triplicate, in polyornithine-coated 96-well optical-bottom plates, to allow imaging on the microscope. The cells were allowed to attach for another 24 hours if only transfected with
DNA, or for another 48 hours if also transfected with siRNA. Fixation of the cells proceeded with 2% PFA for 10 minutes, followed by permeabilization with cold methanol for 10 minutes.
The cells were then washed three times with phosphate-buffered saline (PBS) (137 mM NaCl,
2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4, adjusted to pH 7.4). The cells were then blocked for 1 hour in PBS with 1% BSA. Staining was performed for 1 hour at room temperature
(RT) with anti-Flag M2 followed by three washes with the blocking buffer. The secondary antibody Alexa 488-conjugated anti-mouse was added for 1 hour at RT, at which point the plates started being covered in aluminum foil to protect them from light. The nuclear staining followed as a 5 minute incubation with the Hoechst dye. After three washes with PBS, the plates were stored in the dark, at 4°C, until ready to image. Imaging was performed using the Operetta High
Content Imaging system with a 20 WD objective (Perkin Elmer). Signal from Alexa 488 was excited with a 475/15 filter and emission was captured with a 525/25 filter. Signal from the
Hoechst nuclear stain was excited with a 380/20 filter and emission was captured with a 445/35 filter.
29
Cell Lysis and Protein sample preparation
Cell lysis was performed 48-72 hours following transfection. Cells were washed twice with cold PBS on ice, and resuspended in 100 μl RIPA lysis buffer (1% NP-40, 50 mM Tris-HCl ph 7.4, 150 mM NaCl, 1 mM EDTA, 1mM EGTA, 0.1% SDS, 0.5% sodium deoxycholate, 1X protease inhibitor cocktail) per approximately a million cells. Samples were frozen and, thawed on ice, then lysed by 10 second bursts using the Misonix Sonicator 3000 at 4°C. Lysates were centrifuged for 20 minutes at 12 000 rpm, and the supernatant was collected. The Bradford assay was used to quantify the protein in each lysate. Briefly, the protein assay reagent is added to each sample and the luminescence output is detected using a plate reader. Cell lysates are plotted against a standard curve created with serially diluted BSA to estimate protein concentration. To prepare samples for western blotting, 50 μg of protein was mixed with 4X sample buffer (62.5 mM Tris-HCl pH 8.0, 16.3% glycerol, 2% SDS, 5% 2-mercaptoethanol, 0.025% bromophenol blue) in a 1:4 ratio. The samples were heated for 15 minutes at 65°C, and were ready for western blotting.
Western blotting
Prepared protein samples, along a protein ladder, were loaded on 10% acrylamide gels for detection of proteins smaller than 100 kDa, and on 6% acrylamide gels for detection of RNA polymerase II. Gels were run for 150 minutes at 100 volts. Following the run, the proteins were transferred from the gel onto PVDF membranes previously activated by a 1 minute soak in methanol. The transfer was ran at 100 volts for 70 minutes. Following the transfer, the membranes were briefly washed with TBST (25 mM Tris, 150 mM NaCl, 0.1% Tween, pH adjusted to 7.6) and then blocked for 1 hour at RT in TBST with 5% skim milk. The membranes
30 were incubated with the appropriate primary antibody in TBST with 5% milk, overnight, rotating at 4°C. The next day, the membranes were washed three times for 10 minutes with TBST, and incubated in the appropriate HRP-conjugated secondary antibody in TBST with 5% milk, for 1 hour at RT. The membranes were washed again three times for 10 minutes with TBST. Imaging was done using the ECL detection reagent and the Amersham Imager 600 (GE Healthcare).
Densitometric analysis was performed using the ImageJ software. Measurements for each sample were standardized to their loading control.
Aequorin Assay
Intracellular calcium release was measured using the aequorin assay, a luminescence based biosensor (Han et al. 2009). 293-Aeq cells were transiently transfected with 0.5 μg DNA constructs, pcDNA or siGβ1-resistant WT and mutated Gβ1 subunits, and 50 nM siRNA, either siGβ1 or siCtl, in 12-well plates. 72 hours later, the cells were washed twice with PBS and resuspended in phenol-free DMEM with 0.1% BSA. Samples were then incubated with 5 μM coelenterazine h for 3 hours, rotating at RT, wrapped in aluminum foil to protect samples from light. Opaque-bottom 96-well plates were loaded with 50 μl of the incubated cells, followed by automated injection of 50 μl of 2X concentrations of carbachol, to reach the desired final concentrations of the drug. Calcium release was immediately measured in terms of luminescence output using the Bio-Tek Synergy 2 Multi-Mode Microplate Reader. Data was normalized to the luminescence output of cells transfected with control conditions, treated with the highest concentration of carbachol tested. At the end of data collection, upon observation of the raw values, we noticed that for the highest dose of carbachol tested, 10 mM, the luminescence output consistently dropped compared to the second highest dose, 1 mM. This suggested that receptor
31 desensitisation occurs around those doses, thus we pooled the two highest values when analyzing the data. Statistical analysis consisted of t-tests with Bonferroni correction on the highest doses of the conditions being compared.
Co-Immunoprecipitation
Transient transfection of 10 μg flag-tagged, siGβ1-resistant WT and mutated Gβ1 DNA constructs and, and if dictated, 50 nM siGβ1 or siCtl, was performed in duplicate, in 10-cm dishes. 48-72 hours post-transfection, the cells were starved for 6 hours in pure DMEM. One dish from each transfection condition was then treated with 1mM Carbachol for 45 minutes, following which all cells were lysed in 500 μl RIPA lysis buffer, as per the protocol above.
Following quantification with the Bradford assay, 50 μg of each sample was set aside as the total lysate sample, and kept at -20°C until ready to use. Flag M2 magnetic beads were washed three times with RIPA lysis buffer, before being incubated with 700 μg of cell lysates overnight, rocking at 4°C. The next morning, once the beads had ample time to bind protein complexes expressing flag-tagged Gβ1, the beads were washed three times with RIPA lysis buffer, and incubated with elution buffer (150 ng/μL 3X flag peptide in TBS) for 3 hours, rocking at 4°C.
The supernatant collected constitutes the immunoprecipitated fraction. Both the immunoprecipitated and total lysate samples were prepared for western blotting as described above, and ran by western blot. Statistical analysis was done by t-test, comparing the untreated and carbachol-treated densitometric quantifications.
32
Data Analysis
All data were graphed and statistically analyzed using GraphPad Prism.
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3 ─ Results
3.1 Creating siRNA-resistant constructs expressing Gβ1
To be able to functionally assess the mutants, we needed to create a way to study them in cells, in the absence of the endogenous Gβ1 subunit. RNA interference constituted the most practical method for eliminating the endogenous WT-Gβ1. This method for sequence-specific gene silencing works by introducing cells to siRNA, which are small-interfering, double- stranded RNA sequences. These siRNA are designed to target specific messenger RNA (mRNA) molecules, which they bind to and promote the degradation of their targets (Fischer 2015; Fire et al. 1998).
The segment of the Gβ1 sequence that the siRNA can recognize is common between the
WT and the mutated Gβ1 subunits. To ensure that the siRNA targeting Gβ1 (siGβ1) only knocks down the endogenous WT subunit of the cells, and not the subunits that we are overexpressing, we mutated the siGβ1-targeting sequence. Nucleotide substitutions were made at one or two sites per codon, taking advantage of synonymous codons, to preserve the amino acid sequence.
(Figure 3A)
The siGβ1-resistant sequence was incorporated into a pcDNA3.1(+) vector containing the flag-tagged WT-Gβ1 gene. (Figure 3C). The insertion was performed by QuikChange PCR. The non-mutated template was then eliminated through DpnI digestion of methylated sites. The incorporation of each mutation into the same WT-Gβ1 vector was performed using a similar protocol. To confirm the incorporation of the siGβ1-resistant sequence into the WT and mutated
Gβ1 constructs, the samples were sent for sequencing. The sequence alignment illustrates that the resistant sequence was correctly incorporated into each construct. (Figure 3B)
34
Figure 3. Design and incorporation of the siG1-resistant sequence
A. The nucleotide sequence of the siG1-binding region was mutated at one or two sites per codon. The substitutions were made towards synonymous codons, to ensure the preservation of the amino acid sequence. As such, the protein structure remains undisturbed but the siRNA cannot recognize the sequence, protecting the constructs from knockdown.
B. Sequence alignment showing the incorporation of the designed siG1-resistant sequence
into the WT and mutated G1 constructs. The first row shows the original G1 sequence.
The second row is its siG1-resistant form, where the mutated nucleotides appear in blue. The same mutations appear in the following rows, corresponding to the sequences of the 10 mutants that we studied.
C. Map of the pcDNA3.1(+) vector expressing flag-tagged WT-G1 and the siG1-resistant sequence. The cytomegalovirus (CMV) and T7 promoters are used for transient
transfection expression. The G1 mutation constructs were also incorporated into a
pcDNA3.1(+) vector expressing flag-tagged WT-G1, and the siG1-resistant sequence were subsequentially built in.
35
3.2 Verifying the expression of the constructs in HEK 293 cells
Once we incorporated the siGβ1-resistant sequence into our constructs, and had compiled an array of the regular and siGβ1-resistant versions of the WT and each mutant, we had to confirm that these new subunits are able to get translated, folded and expressed correctly upon transient transfection into our cells.
First, the expression of the constructs was tested by western blot. We used HEK 293 cells stably expressing apoaequorin (293-Aeq), transfected with each siGβ1-resistant mutant. Flag- tagged Gβ1 expression was compared by blotting for -tubulin, a control housekeeping gene.
(Figure 4A) Despite occasional fluctuations between experiments, only mutants M101V and
A11V exhibited consistently lower relative protein expression. (Figures 4A, 5A and 5B)
G subunits have been attributed functions throughout the cell, from the membrane, to the nucleus and within the cytosol at various organelles (Khan et al. 2013). Although western blotting can tell us if a protein is being expressed, it doesn’t confirm whether it gets localized correctly. By immunofluorescence, detecting the flag tag, we can see that the siGβ1-resistant WT and mutated proteins are found at the cell membrane, throughout the cytoplasm, as well as in the nucleus of cells. The latter is detected by the co-localization with the Hoechst nuclear stain. We can also see that each construct had comparable transfection efficiency. (Figure 4B)
We also tried visualizing the localization of Gβ1 by immunofluorescence under knockdown of the endogenous Gβ1, as well as under carbachol stimulation of the M3 mAChR. In every case, the constructs were expressed in the same pattern as under basal conditions (data not shown).
36
Figure 4. siG1-resistant mutants are expressed in 293-Aeq cells
A. 293-Aeq cells were transiently transfected with siGβ1-resistant forms of the WT and
mutated Gβ1 subunit. 48 hours following transfection, the cells were lysed and samples were prepared for western blotting. 40 μg of protein were loaded and the membranes
were blotted for flag, to detect the flag-tagged Gβ1 subunits (~37 kDa), as well as - tubulin as a control (~55 kDa). This shows one representative western blot with each mutant. Similar transfection protocols were used for every experiment further on.
37
B. 293-Aeq cells were transiently transfected with siGβ1-resistant forms of the WT and
mutated Gβ1 subunit, as well as with the empty vector pcDNA. 24 hours following transfection, the cells were harvested and replated in polyornithine-coated 96-well optical-bottom plates, and allowed to attach for another 24h. Cells were then washed, fixed in 2% PFA and permeabilized with methanol. The cells were then blocked for an hour with 1% BSA, incubated with anti-flag primary antibody for an hour, then again with the secondary antibody Alexa 488-conjugated anti-mouse for an hour, and finally with the nuclear stain Hoechst for 5 minutes. The Operetta High Content Imaging system was used to capture these images. The merging of the stained images allows to visualize
the distribution of the WT and mutated Gβ1 subunits throughout cell membrane, cytosol and nuclei.
3.3 Verifying the resistance to knockdown by RNA interference
Having shown that the siGβ1-resistant WT and mutant Gβ1 constructs are expressed correctly at the protein level, we needed to confirm that the mutated siGβ1-binding sequence indeed conferred protection from knockdown. We assessed the levels of WT and mutant Gβ1 by detecting the expression of the flag tag, because we didn’t have access to a good antibody directly targeting Gβ1. However, previous work using the same siGβ1 showed that it efficiently knocks down endogenous levels of Gβ1 as well (Khan et al. 2015).
We first showed that the regular WT and mutated constructs were all completely knocked down by siGβ1. We noted this using western blotting, when comparing the expression of the flag tag to the expression of the -tubulin control, under each condition. (Figure 5A) Following the same transfection protocol, we saw that the siGβ1-resistant constructs of each gene are fully resistant to siGβ1 knockdown. The strength of expression of the flag-tagged protein is similar in the presence of both siGβ1, and the negative control siRNA (siCtl). (Figure 5B)
38
Having concluded that the siGβ1-resistant forms of the WT and mutated Gβ1 proteins were expressed in the right places throughout the cell, and that they conferred protection from siGβ1-mediated knockdown, we could begin using them to compare the function of the mutations to the WT-Gβ1.
39
Figure 5. siGβ1-resistant sequence confers protection from siRNA-mediated knockdown
293-Aeq cells were transiently transfected with siRNA (siGβ1 or its negative control siCtl) as well as, in A with the WT or mutated Gβ1 constructs and in B with each construct’s siGβ1-resistant form. 72 hours following transfection, the cells were lysed and samples were prepared for western blotting. 40 μg of protein were loaded and the membranes were blotted for flag, to detect the flag-tagged Gβ1 subunits (~37 kDa), as well as β-tubulin as a control (~55 kDa). Efficient knockdown of Gβ1 is seen as a faded band when blotted for flag.
40
3.4 Knockdown of the endogenous WT-Gβ1 can be rescued by overexpressing its siGβ1-resistant counterpart, in the aequorin assay
It has been shown that knocking down the endogenous Gβ1 causes an increase in intracellular calcium release, in response to carbachol stimulation of the M3-mAChR (Khan et al. 2015). The aequorin assay allows the quantification of intracellular calcium release by turning it into a bioluminescent signal, in cells stably expressing apoaequorin (293-Aeq). We were able to demonstrate this effect as well, using the same assay. 293-Aeq cells were transiently transfected with the empty vector pcDNA and with either siGβ1 or its negative control siCtl. We detected a statistically significant increase in intracellular calcium release in response to carbachol treatment, under knockdown of the endogenous Gβ1. (p ≤ 0.05) (Figure 6A)
The next step was to reintroduce WT-Gβ1, under knockdown conditions, to verify that the phenotype could be rescued. We transiently transfected the siGβ1-resistant form of the gene into the same 293-Aeq cells. Under siCtl, the calcium release in response to carbachol stimulation was the same for cells transfected with the empty vector or with the overexpressed siGβ1- resistant gene. This confirmed that overexpression of Gβ1 did not interfere with intracellular calcium release. Under siGβ1, we showed that knockdown of Gβ1 could be rescued by introduction of the siGβ1-resistant WT gene, because we did not see the increase in calcium release in response to carbachol treatment. (Figure 6B)
41
Figure 6. Overexpression of the siGβ1-resistant WT-Gβ1 rescues the M3-mAChR-
mediated increase in calcium release caused by Gβ1 knockdown
Calcium release readings were obtained in terms of luminescence emitted. The values were normalized to the highest dose of the negative control. Data is represented as mean ± SEM, of at least 3 independent experiments. Provided p-values are calculated by t-tests with Bonferroni correction on the pooled values of the two highest doses. A. HEK 293 cells stably overexpressing the calcium-sensing biosensor molecule apoaequorin (293-Aeq) were transiently transfected with the empty vector pcDNA and 50
nM of siRNA (where siCtl is a negative control of siGβ1). 72 hours later, the cells were
42
harvested, incubated with 5 μM of coelenterazine h for 3 hours, and then treated with the increasing doses of carbachol.
B. Overexpression of the siGβ1-resistant WT-Gβ1 in the same cells rescues the increase seen in A. 293-Aeq cells were transiently transfected with the empty vector pcDNA or the
siGβ1-resistant WT-Gβ1 construct, as well as with 50 nM of either siCtl or siGβ1. The cells were processed 72 hours following transfection and calcium release was measured, as described in A.
3.5 Gβ1 mutations are categorized as causing gains or losses of function in the M3 mAChR pathway
So far, we have confirmed that knocking down Gβ1 leads to an increase in intracellular calcium release, under stimulation of the M3 mAChR, and we have determined that this phenotype can be rescued by overexpression of the siGβ1-resistant form of the WT gene. This information can be used to predict the effect of each of our mutants on this pathway, based on whether their overexpression can rescue the phenotype or not.
As described in Table 2, the overexpression of a siGβ1-resistant Gβ1 mutation that does not interfere with the M3 mAChR pathway would be able to rescue the calcium increase, similarly to the overexpression of the siGβ1-resistant WT gene. Indeed, mutations I269T,
D118G, M101V, A92T and A11V demonstrate a conserved function, because their intracellular calcium release at the highest doses of carbachol, under both siCtl and siGβ1, is not significantly different from the baseline response of cells transfected with the empty vector pcDNA and siCtl.
(Figure 7A)
Next, we predicted that Gβ1 mutations that cause a loss of function would lead to the same increase in calcium release as under the knockdown of the endogenous Gβ1, because of the
43 inability of the mutation to rescue the phenotype. (Table 2) Under knockdown of the endogenous gene, compared to the baseline response, the Gβ1 mutations I80T and D76G showed significantly higher calcium release in response to carbachol (p ≤ 0.001 and p ≤ 0.05, respectively). (Figure
7B)
The third category of mutations is the ones exhibiting a gain of function, characterized by a dominant-negative effect. These mutations are unable to rescue the phenotype, and they even behave antagonistically to the WT, when co-expressed. This means that the same increase in calcium release in response to carbachol, characteristic of Gβ1 knockdown, will be caused by the dominant-negative mutations, both in the presence and absence of the endogenous WT copy.
(Table 2) We identified three mutations, K89E, K78E and K57E, which satisfy these requirements by causing significant increases in intracellular calcium release in response to carbachol, compared to the baseline response, both under siCtl and siGβ1, (p ≤ 0.05). (Figure 7C)
44
siCtl siG1
pcDNA Normal Increased
siRNA-resistant WT-G1 Normal Rescue
Conserved function Normal Rescue
Loss of function Normal Increased
resistant
-
Mutants Dominant-Negative Increased Increased
siRNA
Table 2. Categorization of mutations based on predicted effect on calcium release in response to M3-mAChR activation
Knockdown of Gβ1 is known to increase intracellular calcium release in response to carbachol stimulation of the M3-mAChR. This effect is detected using the aequorin assay, in 293-Aeq cells transfected with the pcDNA empty vector. Returning a siGβ1- resistant form of WT-Gβ1 rescues the increase in calcium release caused by loss of the endogenous Gβ1. Using this information, we can predict the possible effects of overexpressed siGβ1-resistant mutants in the aequorin assay, with and without knockdown of the endogenous Gβ1, leading to their categorization as whether they conserve the function of the WT protein, lose the function, or cause dominant-negative effects.
45
46
Figure 7. Gβ1 mutations are categorized based on their role in the M3-mAChR pathway
HEK 293 cells stably overexpressing the calcium-sensing biosensor molecule apoaequorin (293-Aeq) were transiently transfected with the empty vector pcDNA or
siGβ1-resistant mutant Gβ1, and 50 nM of siRNA (where siCtl is a negative control of
siGβ1). 72 hours later, the cells were harvested, incubated with 5 μM of coelenterazine h for 3 hours, and then treated with the increasing doses of carbachol to stimulate the M3- mAChR. Calcium release readings were obtained in terms of luminescence emitted. The values were normalized to the highest dose of the negative control. Data is represented as mean ± SEM, of at least 3 independent experiments. Provided p-values are calculated by t-tests with Bonferroni correction on the pooled values of the two highest doses.
A. Overexpression of the Gβ1 mutants I269T, D118G, M101V, A92T and A11V rescued the
increase in intracellular calcium release under Gβ1 knockdown, indicating a conserved pathway.
B. Overexpression of the Gβ1 mutants D76G and I80T were unable to rescue the increase in
intracellular calcium release under Gβ1 knockdown, indicating a loss of function in the M3-mAChR pathway.
C. Overexpression of the Gβ1 mutants K78E, K89E and K57E leads to an increase in intracellular calcium release in response to M3-mAChR stimulation, both under baseline
conditions and under Gβ1 knockdown, indicating a dominant-negative effect.
3.6 Gβ1 interaction with Gq is compromised by some of the mutations
Our mutations of interest are localized throughout the length of the Gβ1 gene. As seen in
Figure 2, some of them are found in proximity to suspected sites of interaction with G and G.
In particular, Gβ1 is known to interact with Gq, the G subunit coupled to the M3 mAChR
(Kruse et al. 2014). To investigate if the gains or losses of function in the calcium pathway downstream of the M3 mAChR correlated with an impaired interaction with Gq, we performed
47 co-immunoprecipitation assays. Briefly, we pulled down protein complexes involving Gβ1, and surveyed them for the presence of Gq.
As expected, we detected a strong interaction between WT-Gβ1 and Gq. The G subunit’s interaction with mutations I269T, D76G and A11V remained robust. The mutations
D118G and M101V showed interactions that were more variable but still detectable, although substantially weakened. The remaining mutations, A92T, K89E, I80T, K78E and K57E, had drastically impaired interactions with Gq, occasionally undetectable. (Representative blot shown in Figure 8A, quantifications in Figure 8B) These five mutations with the most impaired interactions with Gq are found on and near exon 6, which is a portion of the gene relevant to the interaction between G and G (Petrovski et al. 2016).
Interestingly, carbachol-mediated stimulation of the M3 mAChR had no effect on the interaction between G1 and Gq, neither in the case of the WT or the mutants.
48
Figure 8. The interaction between Gβ1 and Gq is disrupted by some of the mutations
A. 293-Aeq cells were transiently transfected with siGβ1-resistant forms of the WT and
mutated Gβ1 subunit (5 μg), in duplicate. 48 hours following transfection, the cells were
49
starved for 6 hours in serum-free DMEM (-/-), and one well of each construct was treated with 1 mM of carbachol for 45 minutes. Cells were then harvested, lysed and proteins immunoprecipitated (IP) for flag. 50 μg of protein were loaded for the total lysate fraction and 60 μl of eluate were loaded for the immunoprecipitation fraction. The western blot
membranes were blotted for Gq (~45 kDa) as well as flag- Gβ1 (~37 kDa) as a control. The blots shown are representative of at least 3 independent experiments.
B. Densitometric analysis of the amount of Gq pulled down, normalized to the amount of
flag-Gβ1 pulled down, for each Gβ1 construct. The bar graph shows mean ± SEM of at least 3 independent experiments.
3.7 Gβ1 mutations impair interaction with RNA polymerase II
So far, several lines of evidence have attributed roles in the nucleus for G. Most recently, G1 has been found to physically interact with RNAPII, in multiple cell types and in response to diverse signaling pathways (Khan et al. 2018). In fact, G1 has been found localized at the promoter region of over 700 genes (Khan et al. 2015). In consequence, we suspected that an impairment to the G1-RNAPII interaction, and thus to the transcriptional regulation of countless genes, could perhaps constitute a disease-causing mechanism.
First, we validated the interaction between G1 and RNAPII, by co-immunoprecipitation.
This interaction is detected at baseline, and it is further induced two-fold by carbachol-mediated stimulation of the M3 mAChR. (p ≤ 0.05) Looking at the G1 mutants, we are able to detect basal interactions, although ranging in strength from approximately 50% (K89E) to 150%
(K57E) as compared to that of the WT. More interestingly, however, is the fact that none of the
G1 mutations exhibit the same increase in interaction with RNAPII as the WT does. In fact,
RNAPII interaction with most mutants is very stable, with and without stimulation. In two cases,
50 mutations D76G and K57E, we actually see a decrease in the strength of interaction, upon carbachol treatment. (Representative blots in Figure 9A and quantifications in Figure 9B) There was some variability in the detection of the interaction, which can account for some of the larger error bars. For instance, in the case of mutation K57E, the high basal interaction, particularly compared to the treated condition, is seen in all replicates. (Figure 9C)
51
Figure 9. The interaction between Gβ1 and RNA polymerase II is disrupted by some of the mutations
A. 293-Aeq cells were transiently transfected with siGβ1-resistant forms of the WT and
mutated Gβ1 subunit (5 μg), in duplicate. 48 hours following transfection, the cells were starved for 6 hours in serum-free DMEM (-/-), and one well of each construct was treated with 1 mM of carbachol for 45 minutes. Cells were then harvested, lysed and proteins immunoprecipitated (IP) for flag. 50 μg of protein were loaded for the total lysate fraction and 60 μl of eluate were loaded for the immunoprecipitation fraction. The western blot membranes were blotted for the RPB1 subunit of RNAPII (~300 kDa) as well as flag-
52
Gβ1 (~37 kDa) as a control. The blots shown are representative of at least 3 independent experiments. B. Densitometric analysis of the amount of RNAPII pulled down, normalized to the amount
of flag-Gβ1 pulled down, for each Gβ1 construct. The bar graph shows mean ± SEM of at least 3 independent experiments. C. Side-by-side replicates of the RNAPII co-immunoprecipitation done with flag-tagged
Gβ1 K57E mutation, illustrating the extent of the variability in the densitometric analysis.
3.8 Co-expression of a mutated and a WT allele has limited effects on protein complexes formed by the mutant
Several of the patients affected by G1 mutations are explicitly described as carrying autosomal dominant mutations. Considering that these mutations occurred de novo, it is likely that the patients are heterozygous for the mutations. In this context, we can imagine several mechanisms of impact for the mutations. For instance, losses of function can lead to haploinsufficiency, and gains of function that promote dominant-negative behavior of a gene can justify the dominance of the mutated allele over the healthy one. This information leads to some possible distinctions in our interpretation of the experiments with knockdown of the endogenous gene copy.
We chose to focus experiments on two cancer-causing G1 mutations, I269T and K78E, because we associated them with differing functional outcomes throughout our experiments, and because they are positioned on opposite sides of the G1 protein. When studying the intracellular calcium release pathway downstream of M3 mAChR activation, we determined that I269T had a conserved protein function, whereas K78E exhibited dominant negative behavior. (Figures 7A and 7C) Next, we showed that I269T maintained the ability to interact with Gq, much unlike
K78E which had effectively lost this interaction. (Representative blots in Figure 8A, quantified 53 in 8B) We repeated the co-immunoprecipitation experiment to observe the Gq interaction, using the siG1-resistant constructs, but this time under G1 knockdown. We observed that the WT was unaffected by knocking down the endogenous protein. In the case of I269T, we observed a slight increase in the interaction, which could be attributed to an increase in available Gq.
Finally, K78E remained unable to bind G1, even in the absence of the endogenous WT, indicating that there is a complete loss of function, not just a competitive bias in binding. Once again, the Gq interaction appeared to be independent of carbachol treatment. (Representative blot in Figure 10A, quantified in 10B)
When analyzing the RNAPII interactions with the mutants, we were surprised to see that, unlike for the WT-G1, treatment with carbachol did not consistently induce the interaction.
(Representative blots in Figure 9A, quantified in 9B) We suspected that the polymerase was capable of distinguishing between the WT and the mutant, and that it preferentially bound to the
WT, under stimulation. Therefore, we repeated the co-immunoprecipitation, using the siG1- resistant constructs, under G1 knockdown. Without carbachol stimulation, we didn’t notice an effect of knockdown on the baseline interaction between G1 and RNAPII. However, knocking down the endogenous WT-G1 weakened the interaction induced by carbachol stimulation.
(Representative blot in Figure 11A, quantified in 11B) This opens the possibility of an interplay between the WT and mutant alleles. It would be interesting to study this further once we have a better characterization of the protein complex involving G1 and RNAPII.
54
Figure 10. Knockdown of the endogenous Gβ1 doesn’t affect the state of the
interaction between Gq and the WT-Gβ1 or the mutations I269T and K78E
A. 293-Aeq cells were transiently transfected in duplicate with siGβ1-resistant forms of the
WT and mutated Gβ1 subunit (5μg), and siRNA (50 nM). siCtl constitutes the negative
control for siGβ1. 72 hours following transfection, the cells were starved for 6 hours in serum-free DMEM (-/-), and one well of each construct was treated with 1 mM of carbachol for 45 minutes. Cells were then harvested, lysed and proteins immunoprecipitated (IP) for flag. 50 μg of protein were loaded for the total lysate fraction and 60 μl of eluate were loaded for the immunoprecipitation fraction. The western blot
55
membranes were blotted for Gq (~45 kDa) as well as flag- Gβ1 (~37 kDa) as a control. The blots shown are representative of 3 independent experiments.
B. Densitometric analysis of the amount of Gq pulled down, normalized to the amount of
flag-Gβ1 pulled down, for each condition. The bar graph shows mean ± SEM of 3 independent experiments.
56
Figure 11. Knockdown of the endogenous Gβ1 dulls the state of the interaction
between RNA polymerase II and the WT-Gβ1 or the mutations I269T and K78E
A. 293-Aeq cells were transiently transfected in duplicate with siGβ1-resistant forms of the
WT and mutated Gβ1 subunit (5 μg), and siRNA (50 nM). siCtl constitutes the negative
control for siGβ1. 72 hours following transfection, the cells were starved for 6 hours in serum-free DMEM (-/-), and one well of each construct was treated with 1mM of carbachol for 45 minutes. Cells were then harvested, lysed and proteins immunoprecipitated (IP) for flag. 50 μg of protein were loaded for the total lysate fraction and 60 μl of eluate were loaded for the immunoprecipitation fraction. The western blot
57
membranes were blotted for the RPB1 subunit of RNAPII (~300 kDa) as well as flag-
Gβ1 (~37 kDa) as a control. The blots shown are representative of 3 independent experiments. B. Densitometric analysis of the amount of RNAPII pulled down, normalized to the amount
of flag-Gβ1 pulled down, for each condition. The bar graph shows mean ± SEM of 3 independent experiments.
58
4 ─ Discussion
Mutations in the Gβ1 subunit of G proteins have recently started being identified as disease-causing, which has generated interest into their specific functional outcomes. We hypothesized that these mutations would cause gains and losses of function, which we could detect by studying their interactions with known partners of Gβ1, and by investigating effects on known Gβ1-associated signaling pathways. The greater objectives of our study were to map functional regions on the Gβ1 gene, and to shed some light on the disease mechanisms by trying to connect the functional outcomes of the mutations with the patient clinical phenotypes.
4.1 siGβ1-resistance as a model
To study the effect of the mutations, we needed a model in which we could easily replace the endogenous Gβ1 with the mutated forms. We chose to proceed by knocking down the gene using
RNA interference and then transiently transfecting siGβ1-resistant forms of our WT and mutated
Gβ1 constructs. RNA interference was a preferable technique for many reasons. For instance, previous work in our lab, which we have built on, used RNA knockdown screens to investigate which G protein subunits were involved in the M3 mAChR pathway in HEK 293 cells (Khan et al. 2015).
Alternatively, we could have opted to use a Gβ1 knockout cell line through CRISPR/Cas9.
Whereas knockdown only temporarily reduces the expression of a gene of interest, knockouts make the protein inactive in the long term, which allows the cells time to adapt and build compensatory mechanisms (Luttrell et al. 2018). Mechanistic evidence for this hypothesis has recently been demonstrated to include modulation of the transcription of related genes. Briefly,
59 mutations aimed at inactivating a gene can lead to the translation of prematurely terminated mRNA. These can trigger mRNA degradation through a process termed nonsense-mediated
RNA decay. The resulting fragments are then able to bind complementary nucleotide sequences in related genes, initiating their translation (El-Brolosy et al. 2019; Ma et al. 2019). These compensatory mechanisms change the biology of the cells in a way that is yet poorly understood, which at this point would hinder their usefulness as a model in a study such as ours. Using RNA interference to trigger knockdown provided us with a consistent model for testing our different constructs.
4.2 Mapping functional regions on the Gβ1 gene
Over 50 distinct mutations in the Gβ1 subunit have been associated with cancer and/or neurodevelopmental disorders. We focused on a set of ten, which we chose because they were spread throughout the length of the gene, and six of them are concentrated in the stretch of the gene between K57 and A92, which has been shown to be involved in important interactions and signaling pathways (Ford et al. 1998; Yoda et al. 2015; Lohmann et al. 2017). These ten mutations are each associated with cancers and/or neurodevelopmental disorders. (Figure 2)
Throughout our study of these Gβ1 mutations, we compared their functional outcomes to that of WT-Gβ1. We aimed to categorize the mutations as causing gains or losses of function in the signaling pathways and interactions that we hypothesized would guide our understanding of how the mutations cause clinical symptoms in patients. We first studied whether the mutations interfere with M3 mAChR-mediated intracellular calcium release, by determining whether their expression can rescue the phenotype caused by knockdown of the WT. We found that half of our
60 mutants could rescue this function, whereas the other five caused either gains or losses of function. (Figure 7) Next, we studied the known interactions of Gβ1 with Gq and with RNAPII.
We found that most of our mutations interfered with these interactions. (Figures 8 and 9) Our findings support our hypothesis, that disease-causing mutations alter protein function at a molecular level.
61
62
Figure 12. Illustration of the functional outcomes of our Gβ1 mutations in terms of their localization on the gene.
Molecular representation of the G-protein heterotrimer composed of the Gi1 (gold), G1
(green) and G2 (silver), based on a crystal structure (PDB 1GP2) (Wall et al. 1995). Corresponding sites of mutations are identified by spheres, of which the color represents the outcome in each of the following analyses: (A) associated pathology, (B) functional ability to carry out intracellular calcium release stimulated by M3 mAChR activation, (C)
state of the interaction with Gq, and (D) change in the strength of the interaction with RNAPII upon stimulation of the M3 mAChR.
We noted that the mutations situated at the extremities of the gene, A11V, M101V, D118G and I269T, had the least severe functional outcomes in our assays. As predicted, the most severe functional phenotypes were found for K57E, D76G, K78E, I80T, K89E and A92T. This is consistent with previous work having shown that exon 6 (chr1: g.1737912–1737979; GRCh37) of the Gβ1 gene, containing mutations D76G, K78E, I80T and K89E, although only encoding
6.4% of the total protein-coding sequence, harbors the most common mutations leading to both cancer (4 out of the 5 missense substitution locations associated with three or more patients with malignancies) and neurodevelopmental disorders. In fact, 28% of patients with neurodevelopmental disorders and a substitution in the Gβ1 gene had it at the I80 residue
(Petrovski et al. 2016; Brett et al. 2017; Hemati et al. 2018). Additionally, as seen in Figure 2, this region also harbors the mutations with the largest number of different disease-causing substitutions at a single residue. Looking at the location of the mutations, we do notice that this region is located in proximity to the Gq and effector binding surface. That corresponds to the mutations that we identified as losing the interaction with the subunit. (Figure 12C) We also notice several disease-causing mutations occurring near the G binding region. Taken together,
63 this reinforces the fact that defects in the heterotrimer formation would severely impair the G protein function.
Coincidentally, we noticed that the substitutions from lysine to glutamic acid are common, and among the most devastating, leading to gains of function in the intracellular calcium release pathway. (Figure 12B) Our data suggests that the change from a positively-charged to a negatively-charged residue is especially prone to functional consequences. In fact, eight of our ten mutations of interest carry a change in amino acid polarity or charge. The other two mutations, M101V and A11V, maintain the nonpolar/hydrophobic nature of the residue. As a matter of fact, the specific nucleotide and amino acid substitutions could have effects on the protein stability of the mutated Gβ1 subunits. We ran our mutations through a program that estimates and compares the Gibbs free energy of WT-Gβ1 to the mutated forms. As a result, we found that our mutations were associated with a range of predictions. On one hand, two mutations, A92T and A11V are classified as stabilizing, which predicts an increase in the rigidification of the molecule. The other eight mutations were classified as destabilizing, leading to an increase in the flexibility of the molecule. Most notably, I269T and I80T had the strongest values, suggesting the greatest change in vibrational entropy energy between the WT and the mutant (Table 3) (Rodrigues, Pires, and Ascher 2018).
64
Mutation Predicted effect on stability
1 269 T ΔΔG: -1.515 kcal/mol (Destabilizing)
D 118 G ΔΔG: -0.595 kcal/mol (Destabilizing)
M 101 V ΔΔG: -0.123 kcal/mol (Destabilizing)
A 92 T ΔΔG: 0.332 kcal/mol (Stabilizing)
K 89 E ΔΔG:-0.051 kcal/mol (Destabilizing)
I 80 T ΔΔG: -1.270 kcal/mol (Destabilizing)
K 78 E ΔΔG: -0.086 kcal/mol (Destabilizing)
D 76 G ΔΔG:-0.682 kcal/mol (Destabilizing)
K 57 E ΔΔG: -0.027 kcal/mol (Destabilizing)
A 11 V ΔΔG: 0.050 kcal/mol (Stabilizing)
Table 3. Predicted G protein stability in response to Gβ1 mutations.
A Dynamut analysis was used to predict the impact of each mutation on the flexibility
and stability of the G protein. We used a crystal structure (PDB 1GP2) that contains G1
in complex with Gi1 and G2. The program output gives us an estimate change in Gibbs Free Energy (ΔΔG), which is the difference in the protein’s free energy between the WT-
Gβ1 and each mutation. A positive value is considered stabilizing, and would cause a rigidification of the structure, whereas a negative value is considered destabilizing, and would be associated with an increase in flexibility (Rodrigues, Pires, and Ascher 2018; Wall et al. 1995).
Another possible outcome of the mutations would be a change in the expression of the subunits. The translation-selection theory posits that expression level of genes can be influenced
65 by the availability of codons and amino acids, due to the fact that certain major codons and amino acids have a higher availability in the cell than other ones (Varenne et al. 1984; Kudla et al. 2009). However, this remains a controversial theory. One study in particular found that less than 10% of variation of expression levels of genes are explained by the specific amino acid components, and even less so by specific codon composition (Hershberg and Petrov 2008;
Misawa and Kikuno 2011). In any case, by overexpressing our constructs, we overcome the possible limitations of codon and amino acid selection bias that may have an effect on protein expression in vivo. We experimentally confirmed that the expression level and distribution of our constructs throughout the cells is comparable for our WT and mutated Gβ1 subunits. (Figures 4 and 5) In future steps, it would be relevant to test other cell lines, as well as pursue a more detailed investigation of sub-cellular localization of the mutant constructs using markers for different organelles where WT-Gβ1 is found.
4.3 Factors affecting the severity of the disease
Unfortunately, there are many aspects about the patients that affect the severity of their diseases, and that we can’t model in our experiments. Location is obviously a determining factor when it comes to the severity of a mutation. Another very important factor is the timing of the mutation’s occurrence. The de novo Gβ1 mutations that are observed in cancer patients are somatic, as the name implies, they occur in somatic cells and are passed down as the cell divides.
Such mutations are often caused by environmental factors. More relevantly to the topic at hand, the Gβ1 mutations associated with neurodevelopmental diseases occur at the germline stage, meaning that they affect germ cells and can occur throughout zygote development (Foulkes and
Real 2013). Gβ1 is known to play an important developmental role. Studies have associated mice
66 homozygous for a disrupted Gβ1 with lethality at the perinatal stage as well as throughout growth and development. Additionally, embryos homozygous for a mutated Gβ1 exhibit severe neurological symptoms including brain morphology and cellular proliferation. (Petrovski et al.
2016; Okae and Iwakura 2010) However, the number of patients with germline Gβ1 mutations showed that heterozygous mutations also lead to severe neurological symptoms. (Brett et al.
2017; Steinrucke et al. 2016) Although it could not be determined in all cases, the majority of patients were found to express the mutations in an autosomal dominant manner. (Lohmann et al.
2017) Interestingly, one patient with the neurodevelopmental disorder has been described with somatic mosaicism of Gβ1 mutation, leading to a milder phenotype. (Hemati et al. 2018)
The genomic characterization of the patients gave us a particular interest in studying possible dominant-negative effects of the mutations, so that we could determine if the symptoms may be an outcome of the mutated copy disrupting the WT copy, as well as haploinsufficiency, the latter of which is typical of loss-of-function mutations (Veitia 2009). When studying the intracellular calcium release pathway, we found that three mutants, K78E, K89E and K57E, were categorized as dominant-negative. On top of being unable to rescue the loss of the WT subunit, like mutations D76G and I80T which caused loss of function, the gain of function mutations also blocked the activity of the endogenous WT-Gβ1. (Figure 7B and 7C) In the physiological context of heterozygous patients, we can suspect that the loss of function mutations could by the endogenous, WT-Gβ1, as was the case in the aequorin assay. Of course, in our experiments, we relied on the endogenous expression of WT-Gβ1 in HEK 293 cells, to carry out the protein’s function in the M3 mAChR calcium signaling pathway. In humans, it comes down to whether the natural expression of the WT gene is sufficiently high to overcome haploinsufficiency.
67
4.4 Calcium signaling and disease
The GNB1 syndrome, caused by germline de novo Gβ1 mutations, is characterized by neurological symptoms such as global developmental delay and issues such as seizures, hypotonia and dystonia. Calcium is a common second messenger inside cells, and is especially important in excitable cells because it controls vital cellular functions including differentiation, proliferation, growth, membrane excitability and gene transcription (Pchitskaya, Popugaeva, and
Bezprozvanny 2018). Dysregulated calcium signaling has been associated with neurological syndromes, such as epilepsy, by causing hyperexcitability of neurons through mechanisms such as modulation of neuronal activity and calcium-dependent gliotransmission (Steinlein 2014).
Calcium signaling has also been studied extensively in the context of neurodegenerative diseases, by causing synaptic instability, mitochondrial dysfunction and excitotoxicity (Glaser et al. 2018; Pchitskaya, Popugaeva, and Bezprozvanny 2018). Beyond its importance in neuronal function and signaling, calcium regulation also affects skeletal muscle function. Altered calcium influx has been associated with muscle diseases such as hypotonia (Stiber and Rosenberg 2011).
Many Gβ1 residues have been associated with inhibition of calcium channels, and mutations at those sites have been predicted to interfere with signaling (Petrovski et al. 2016) One group performed alanine scans on the conductance of calcium channels, and they identified that residue
I80 can enhance the inhibition of calcium current, whereas residues K78 and M101 lose the ability to inhibit calcium currents (Ford et al. 1998). We investigated the effect of Gβ1 mutations on intracellular calcium signaling downstream of the M3 mAChR activation. Surprisingly, two mutations that caused neurodevelopmental disorders, D118G and A92T, were able to rescue the knockdown of WT-Gβ1. The five mutations that we identified as causing gain or loss of functions in this pathway were all associated with cancer, and only two of them, D76G and I80T,
68 were also found in patients with neurodevelopmental disorders. (Figure 7B, 7C, 12A and 12B).
As a matter of fact, some groups have linked calcium signaling to cancer progression and metastasis, in particular through calcium-mediated promotion of cell migration (Pratt et al.
2018). Having generated some interesting results using biosensors to study the effects of Gβ1 mutations on intracellular calcium release, the next steps would be to investigate the activity of other signaling pathways such as adenylyl cyclase/cAMP and Rho/PKN. The latter would be especially interesting to study in the context of cancer-causing G1 mutations, because Gβγ has been shown to activate a Rho guanine nucleotide exchange factor upregulated in a number of leukemia cell lines and mouse models of leukemia (Ueda et al. 2008).
4.5 Heterotrimer formation and cancer
Close to a hundred cancer patients (cancer.sanger.ac.uk) have been found to express mutations in GNB1, however, in many cases they may not necessarily constitute disease-causing mutations (Harsha et al. 2016). There are several mechanisms through which Gβ1 mutations have been suggested to cause cancer, such as the disruption of residues important for interactions between G and downstream effectors, or even disruption to the protein interface required for heterotrimer formation, which could lead to a constitutively active G (Petrovski et al. 2016).
That being said, one group has tested this hypothesis by culturing cells expressing G1 mutations causing an impaired G interaction, and treating them with pertussis toxin, which blocks Ga signaling, and they found that this did not inhibit cell growth (Yoda et al. 2015). Nonetheless, activating mutations in genes encoding G are found in 4-5% of all human cancers, and constitutively active Gq has been associated with cancers, including nearly 90% of cases of
69 uveal melanoma, the most common eye cancer (Onken et al. 2008; O'hayre et al. 2013). One group suggested that this particular disease mechanism involves the antagonism by Gq of epigenetic silencing (Onken et al. 2018). In the future, it may be interesting to test it Gβ1 mutations enhance tumorigenicity in cancer cells, by doing assays such as wound healing or colony-formation. To narrow down which Gβ1 mutations are capable of promoting cancer through gain-of-function alterations, one group constructed cDNA libraries from individual cancers and transfected them into cytokine-dependent cells. They studied several pathways and interactions that have been linked to cancer promotion, including cytokine-independent growth and increased trophic signaling through Akt-mTOR and MAPK, which they attributed to several
Gβ1 mutations. When looking into heterotrimer formation, they discovered that Gβ1 mutations
K89E, I80T and K57E had reduced binding to G subunits but not to G (Yoda et al. 2015). This is consistent with our findings for mutations with reduced interaction with Gq, and we additionally found that the same went for A92T and K78E. (Figure 8 and 12C) Interestingly, the group found that the state of interaction between the Gβ1 mutants and G was conserved for each G subunit they tested, namely Gi2, Gi3, Gq, G13. This suggests that our results on
Gq may be applicable to other G subunits as well, which opens the door to other G- dependent signaling pathways that may be affected by Gβ1 mutations. The results we obtained in terms of whether our Gβ1 mutants were able to physically interact with Gq were independent of either carbachol stimulation or presence of the endogenous WT-Gβ1. (Figures 8 and 10) Rather, our results support previous findings which stated that Gβ1 regulates the expression of Gβ4, which in turn is part of the G41 heterotrimer coupled to M3 mAChR. The conclusion of this previous work was that knockdown of Gβ1 causes increased intracellular calcium release by
70 increasing the expression of Gβ4 and thus increasing signaling through the muscarinic receptor
(Khan et al. 2015).
4.6 Transcriptional regulation
As such, an important role for Gβ1 has been established in transcription, notably downstream of Gq-coupled GPCRs. More specifically, Gβ1 has been found to localize to the promoters of over 700 genes, as well as bind to RNAPII and transcription factors (Robitaille et al. 2010; Khan et al. 2018; Khan et al. 2013). Impairment in the function and association of transcription elongation factors have been linked with several diseases, including cancers such as acute myeloid leukemia, the latter having has also been associated to Gβ1 mutations (Sharma 2016;
Yoda et al. 2015). We investigated whether Gβ1 mutations lead to changes in the interaction with
RNAPII. In the absence of carbachol stimulation, we found that our ten mutations of interest had maintained the ability to form protein complexes with the polymerase, ranging in strength from approximately 50% (K89E) to 150% (K57E) that of the WT. In the case of the WT-Gβ1, we detected a statistically significant increase in the interaction in response to carbachol treatment.
We didn’t see this increase with any of our mutations. In fact, two mutations, D76G and K57E, showed a decreased interaction with RNAPII in response to carbachol treatment. (Figure 9 and
12D) RNAPII is a very large protein, over 500 kDa, composed of 12 subunits (Kostek et al.
2006). In this context, our results suggest that none of our Gβ1 point-mutations alone are sufficient to completely lose the basal interaction with such a large complex. In addition, during transcription, RNAPII is associated with a number of other proteins and transcription factors.
Perhaps mutations in Gβ1 interfere with the recruitment or destabilize the interaction of other members of the larger RNAPII -Gβ1 complex, particularly upon stimulation GPCR-mediated
71 pathways. This calls for a better understanding of the greater complex formed by the polymerase with Gβ1, and the conditions which mediate its recruitment to promoter sites. All the work described in this thesis has been done using HEK293 cells. It would be very interesting to pursue these studies in other cell lines, where interesting work has been done. For instance, in the context of Gβ1’s role in gene expression, work in our lab using primary cardiac fibroblasts has shown that knockdown of leads to the significant basal upregulation of 19 genes, and to trends for the upregulation of 37 genes following treatment with angiotensin II (Khan et al. 2018).
Investigating how Gβ1 mutations affect the pattern of genes whose transcription is mediated by
Gβ1 would provide extremely useful leads into which signaling pathways might be affected by the mutations, and thus lead to the observed clinical symptoms of the patients.
72
5 ─ Concluding remarks
Aside from their role in regulating the activity of heterotrimeric G proteins, G subunits have been associated with a wide array of distinct signaling pathways throughout the cell. On one hand, canonical functions of the dimer involve cell surface effectors such as ion channels and adenylyl cyclase. More recently, noncanonical effectors of G subunits have been identified at subcellular sites, away from the plasma membrane, such as the mitochondria and the
Golgi apparatus, as well as in the nucleus where G has been found to regulate transcription of numerous genes.
Mutations in Gβ1, a particular subunit of the G protein, have been associated with cancer and with the GNB1 Syndrome, a neurodevelopmental rare disease. Very little is known about how the clinical phenotypes of the patients relate to the functional changes caused by the mutations. Our objective was to attempt to draw such links by studying which specific Gβ1 residues are involved in known protein interactions and by searching for gain and loss of function in established Gβ1 signaling pathways. We hope that our work can provide a better understanding of the diseases, to help support the patients from a medical perspective.
By building a model in which we knock down the endogenous WT-Gβ1 in cells, and then replace it with siGβ1-resistant WT and mutated constructs, we were able to identify which mutations had conserved, loss, or gain of function in the intracellular calcium release downstream of M3 mAChR. Calcium signaling has been linked to both neurological symptoms and cancer metastasis, which made it especially relevant for our disease-causing mutations. It also paves the way to use biosensors for testing other important signaling pathways. Next, we mapped Gβ1 residues involved in the binding to Gq, which gave us a better idea of which
73 mutations impair the formation of the G protein heterotrimer. Constitutively active G has been linked to cancer in many instances, and we identified some mutations that enable this mechanism. We also investigated whether the mutations may impair G subunit effects in modulating gene transcription, by testing whether the mutations impair the interaction of Gβ1 with RNAPII. Our results suggest that the mutations may have a severe impact on gene expression, which strengthens our interest in pursuing it as a disease-causing mechanism.
In conclusion, our work uncovers potential pathways affected by disease-causing Gβ1 mutations, to bring us closer to our goal of better understanding disease mechanisms, and hopefully identify druggable targets.
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