Identifying Novel Protein Interactors of the Glucagon Superfamily of Receptors

Gregory Gaisano

A thesis submitted in conformity with the requirements for the degree of Masters of Science Graduate Department of Physiology University of Toronto

Gregory Gaisano

Masters of Science

Department of Physiology University of Toronto

2009

Abstract

G-protein coupled receptors (GPCRs) have been shown to act as part of GPCR

associated protein complexes (GAPCs) which are required to appropriately transduce

downstream signaling pathways leading to specific cellular actions. I hypothesize that

there are distinct molecular effectors that couple to the glucagon superfamily of B-class

GPCRs (glucagon, GLP-1, GLP-2, GIP receptors) to effect the myriad of reported

actions in numerous target cells including regulation of insulin secretion, intestinal

growth and appetite suppression. GLP-1R, GIPR, GLP-2R and GCGR were screened

using a newly developed membrane-based split-ubiquitin yeast two-hybrid (MYTH)

system to reveal 181 novel candidate protein interactors associated with signal

transduction, transport, metabolism and cell survival. Each candidate was validated

using yeast two-hybrid prey retransformation tests and by co-purification to confirm

coupling to each receptors. The present work is the first demonstration of a split-

ubiquitin interaction screen using in situ membrane expressed GPCRs of the secretin-

like B class.

Acknowledgements

I would like to express my sincere thanks to my supervisor Dr. Michael Wheeler who provided endless support on multiple levels throughout the project. His guidance on the scientific and personal levels has helped me tremendously throughout the development of this thesis.

I would also like to express my heartfelt thanks to Dr. Feihan Dai for all her teachings, encouragements, and caring discussions. Her mentorship has been central to my understanding of the molecular biology field.

My deep appreciation goes to Victoria Wong and Saranya Kittanakom for training me to use the membrane-based yeast-two hybrid system and for providing their expertise on all the biochemical aspects of this project. I would also like to thank my student, Kamyar Giglou, for his kind help in all my assays.

A sincere thank you for Dr. Igor Stagljar and Dr. Anthony Gramolini and their respective laboratory staff for their guidance in yeast two-hybrid and large-scale proteomic screening techniques.

Finally, I would like to express my deepest thanks to God, my family, girlfriend and friends whose endless support have made everything possible.

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TABLE OF CONTENTS

ABSTRACT OF THESIS…………………………………………………………….………....ii

ACKNOWLEDGEMENTS…………………………………………………………………….. iii

TABLE OF CONTENTS………………………………………………..………………………iv

LIST OF TABLES………………………………………………………………….……..…….ix

LIST OF FIGURES……………….…………………………………………………………… x

LIST OF ABBREVIATIONS………………………………………………………….………. xi

CHAPTER 1: GENERAL INTRODUCTION……………………...………………………..... 1

1.1 G Protein-Coupled Receptors (GPCR)……………………………………...…..1

1.1.1 Structure……………………..………………………………………… .1 1.1.2 G-proteins…………………………………………………………… ….2 1.1.3 Interactomes………………………………………………………… ….3

1.2 Class-B GPCRs…………………………………………………………………...…5

1.3 Glucagon Superfamily of Receptors…………………………………………… 6

1.4 Glucagon-Like Peptide 1 and GLP-1R………………………………...………...6

1.4.1 Expression……………………………………………………………… 6 1.4.2 Structure………………………………………………………………… 7 1.4.3 Function ……………...………………………………………………… 7 1.4.4 Signaling……………………………….……………………………….. 9 1.4.5 Regulation……………………………………………………………. 10

1.5 Glucose-Dependent Insulinotropic Polypeptide and GIPR…………………11

1.5.1 Expression………………………………………………………………11 1.5.2 Structure………………………………………………………………...11 1.5.3 Function ……………………………...…………………………………12 1.5.4 Signaling …………………………..……………………………………13 1.5.5 Regulation………………………..…………….……………………….13

1.6 Glucagon-Like Peptide 2 and GLP-2R………………………………..………..14

1.6.1 Expression……………………………………………………………...14 1.6.2 Structure……………………………………………………………...... 14 1.6.3 Function ………………………………………………………………..14 1.6.4 Signaling ……………………………………………………………….16

1.6.5 Regulation ………………………………………………………..…... 16

1.7 Glucagon and GCGR…………………………………………………………...... 16

1.7.1 Expression……………………………………………………………..16 1.7.2 Structure……………………………..………………………………...17 1.7.3 Function …………………………...……………..……………………17 1.7.4 Signaling ……………………………………………………………… 19 1.7.5 Regulation…………………………………………………………….. 19

RATIONALE AND HYPOTHESIS OF THESIS………………………………………... 20

OBJECTIVES ………………………………………...……………………………….. …..21

CHAPTER 2: ESTABLISHMENT OF MYTH METHOD TO STUDY B-CLASS GPCR……. 22

2.1 Rationale…………………………………………………………………………… 22

2.2 Hypothesis……………………………………………………………………...…. 22

2.3 Introduction…………………………………………………………………..…… 22

2.3.1 Molecular Proteomic Screening Tools………………………..….. 22 2.3.2 Yeast Two-Hybrid Screening………………………………………. 23 2.3.3 Spilt Ubiquitin Membrane-based Yeast Two-Hybrid System….. 23 2.3.4 Variation of YTH systems ………………………………………… 25 2.3.5 Alternative Proteomic Screening Tools…………………………… 25

2.4 Method and Materials……………………………………………………………. 27

2.4.1 Reagents……………………………………………………………… 27 2.4.2 Cell Culture…………………………………………………………… 27 2.4.3 Polymerase Chain Reaction (PCR) and Gel Extraction…………. 27 2.4.4 Yeast Bait Construction …………………….………………………. 27 2.4.5 Immunofluorescence ………………………….…………………….. 28 2.4.6 NubG/NubI Test…………………………………………………...... 29 2.4.7 Receptor Cloning…………………………………………………….. 29 2.4.8 Intracellular cAMP Measurement………………………………….. 29 2.4.9 Statistics………………………………………………………………. 30

2.5 Results……………………………………………………………………………….30

2.5.1 Generating Receptor “Bait” Constructs……………………………. 30 2.5.2 Cub-TF Fused Receptors are Localized to Yeast Plasma Membrane…………………………………………………………….. 31 2.5.3 Cub-TF Fused Receptors are Compatible with MYTH system…. 31 2.5.4 Cloned Receptors can be Expressed in Mammalian Cells……… 32

2.5.5 Cloned Receptors are Functional in Mammalian Cells…………. 32

2.6 Summary of Findings……………………………………………………………. 35

2.7 Discussion………………………………………………………………………….36

2.7.1 MYTH Receptor Compatibility……………………………………… 36 2.7.2 GCGR Subcloning…………………………………………………… 36 2.7.3 IF Resolution…………………………………………………………. 37

CHAPTER 3: IDENTIFICATION OF NOVEL INTERACTORS OF RECEPTORS...... 38

3.1 Rationale…………………………………………………………………………… 38

3.2 Hypothesis………………………………………………………………………….38

3.3 Introduction…………………………………………………………………….…..38

3.3.1 Glucagon Receptor Superfamily – Known Interactors…………… 38 3.3.2 Limitation of MTYH System…………………………………………. 39 3.3.2.1 Absence of Receptor Activation…………………….. 39 3.3.2.2 False Negatives………………………………………. 39

3.4 Method and Materials……………………………………………………………. 40

3.4.1 Reagents ………………………………………………………..……. 40 3.4.2 cDNA Synthesis and RT-PCR……………………………………… 40 3.4.3 Large-scale Library Screen…………………………………………. 41 3.4.4 Prey Isolation…………………………………………………………. 41 3.4.5 BLAST Analysis……………………………………………………… 42

3.5 Results……………………………………………………………………………… 42

3.5.1 RT-PCR: GLP-1R is Expressed in Human Fetal Brain cDNA….. 42 3.5.2 GLP-1R Large Scale Library Screen………………………………. 43 3.5.3 GIPR Large Scale Library Screen………………………………….. 45 3.5.4 GLP-2R Large Scale Library Screen……………………………..... 47 3.5.5 GCGR Large Scale Library Screen………………………………… 50

3.6 Summary of Findings…………………………………………………………… 52

3.7 Discussion………………………………………………………………………… 53

3.7.1 Human Fetal Brain Expression……………………………..………. 53 3.7.2 Selection of Yeast Colonies………………………………………… 54 3.7.3 Low Number of Interactors Screened……………………………… 54 3.7.4 List of Putative Interactors…………………………………………... 54

CHAPTER 4: VALIDATION OF NOVEL INTERACTORS………………………………. 56

4.1 Rationale…………………………………………………………………………… 56

4.2 Hypothesis……………………………………………………………………….... 56

4.3 Introduction……………………………………………………………………….. 56

4.3.1 False Positives in YTH screens……………….……………………. 56 4.3.2 Alternative Validation Tests…………………………………………. 57

4.4 Method and Materials………………………………………………………….....57

4.4.1 Reagents……………………………………………………………… 57 4.4.2 Cell Culture…………………………………………………………… 57 4.4.3 In Silico Analysis…………………………………..…………………. 57 4.4.4 Prey Retransformation Test …………………..……………………. 58 4.4.5 Interactor Cloning……………………………………………………. 58 4.4.6 Co-purification…………………………………………………………58 4.4.7 Immunoblotting ………………………………………………………. 59

4.5 Results………………………………………………………………………………59

4.5.1 Validation by Prey Retransformation Tests…………………..…… 59 4.5.2 In Silico analysis of Validated Receptor Interactors……………… 64 4.5.3 Validation by Co-purification……………………………...... 64

4.6 Summary of Findings……………………………………………………………. 66

4.7 Discussion………………………………………………………………………….66

4.7.1 Screening out False Positives……………………………………….66 4.7.2 Co-purification…………………………………………...... 66 4.7.3 Potential Relevance of Validated Interactors …………………….. 67 4.7.3.1 APH1A…………………………………………………. 67 4.7.3.2 APLP1…………………………………………………..68 4.7.3.3 CD81…………………………………………………… 70 4.7.3.4 GABBR2…………………………………….……….....70 4.7.3.5 GPR37………………………………….……………… 71 4.7.3.6 HPN…………………………….……………………….72 4.7.3.7 STMN1………………………………………………….72

CHAPTER 5: GENERAL DISCUSSION……………………………….……………...... 73

5.1 Summary of Findings……………………………………………………………. 73

5.2 MYTH system……………………………………………………………………… 73

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5.3 B-class GPCR Interactomes……………………………………………………. 74

5.4 Pharmacological Relevance……………………………………………………. 75

5.5 Function of Novel Interactors - Preliminary Data…………………………... 76

5.6 Future Directions…………………………………………………………………. 77

5.7 Conclusion………………………………………………………………………… 79

REFERENCE LIST…………………………………………………………………………… 80

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LIST OF TABLES

Table 1. Summary of GLP-1 actions………………………………………...... 9 Table 2. Summary of GIP actions. ………………………………………………………….. 13 Table 3. Summary of GLP-2 actions………………………………………………………….16 Table 4. Summary of glucagon actions……………………………………………………… 19 Table 5. Summary of GLP-1R-Cub-TF screens of human fetal brain NubG-X cDNA library……………………………………………………………………………..43 Table 6. Summary of GLP-1R-Cub-TF screens of human kidney NubG-X library……... 44 Table 7. Summary of identified interactors (unvalidated) from GLP-1R-Cub-TF screens of both human fetal brain and human kidney NubG-X cDNA libraries…… 44 Table 8. Summary of GIPR-Cub-TF screens of human fetal brain NubG-X library…….. 45 Table 9. Summary of identified interactors (unvalidated) from GIPR-Cub-TF screens of human fetal brain NubG-X cDNA library……………………………………...45 Table 10. Summary of GLP-2R-Cub-TF screens of human fetal brain NubG-X cDNA library. …………………………………………………………………………... 48 Table 11. Summary of identified interactors (unvalidated) from GLP-2R-Cub-TF screens of human fetal brain NubG-X cDNA library………………………………..... 49 Table 12. Summary of GCGR-Cub-TF screens of human fetal brain NubG-X library…… 50 Table 13. Summary of identified interactors (unvalidated) from GCGR-Cub-TF screens of human fetal brain NubG-X cDNA library…………………………………….. 51 Table 14. Summary of GLP-1R-Cub-TF putative interactors which tested positive in prey retransformation tests………………………………………………………….. 60 Table 15. Summary of GIPR-Cub-TF putative interactors which tested positive in prey retransformation tests………………………………………………………….. 61 Table 16. Summary of GLP-2R-Cub-TF putative interactors which tested positive in prey retransformation tests………………………………………………………….. 62 Table 17. Summary of GCGR-Cub-TF putative interactors which tested positive in prey retransformation tests………………………………………………………….. 63

LIST OF FIGURES

Figure 1. Phylogenetic Tree of B-class Secretin-like GCPRs…………………………...... 2 Figure 2. Examples GPCR binding proteins (GBPs)…………………………………………. 4 Figure 3. Structure of a B-class GPCR……………………………………………………...... 5 Figure 4. Flowchart for experimental aims for MYTH system PPI cDNA-library screen…21 Figure 5. Split-ubiquitin membrane-based yeast two-hybrid system (MYTH)……………. 24 Figure 6. Generation of bait construct…………………………………………………………31 Figure 7. Receptor immunolocalization to yeast membrane………………………………..31 Figure 8. Receptors pass NubG/NubI Test interaction capability and self-activation…....33 Figure 9. Receptor is expressed at the protein level and activation increases intracellular cyclic AMP accumulation in a dose-dependent manner………………….... 35 Figure 10. GLP-1R gene expression shown in human fetal brain cDNA………………….. 43 Figure 11. Breakdown of identified interactors (unvalidated) from GLP-1R-Cub-TF screens of both human fetal brain and human kidney NubG-X cDNA libraries…... 45 Figure 12. Breakdown of identified interactors (unvalidated) from GIPR-Cub-TF screen of human fetal brain NubG-X cDNA library…………………………….………. 47 Figure 13. Breakdown of identified interactors (unvalidated) from GLP-2R-Cub-TF screen of human fetal brain NubG-X cDNA library……………………………..…… 50 Figure 14. Breakdown of identified interactors (unvalidated) from GCGR-Cub-TF screen of human fetal brain NubG-X cDNA library…………………………………….. 52 Figure 15. Breakdown of the total identified interactors (unvalidated) from all 12 receptor MYTH screens…………………………………………………………………. 53 Figure 16. GLP-1R putative interactor proteins pass prey retransformation test…………. 60 Figure 17. GIPR putative interactor proteins pass prey retransformation test…………….. 61 Figure 18. GLP-2R putative interactor proteins pass prey retransformation test…………. 62 Figure 19. Summary of all putative interactors which tested positive in prey retransformation tests………………………………………………………….. 64 Figure 20. Co-Immunoprecipitation (Co-IP) to validate receptor interactors………………. 65 Figure 21. APLP1, CD81 and STMN1 are co-immunoprecipitated with GLP-1R, GIPR and GLP-2R in HEK293T cells…………………………………………………….. 65 Figure 22. Preliminary study showing no effect of selected interactors on cAMP accumulation……………………………………………………………………. 77

LIST OF ABBREVIATIONS

2+] [Ca i intracellular calcium concentration 3’AT 3-aminotriazole aa amino acid AC adenylate cyclase AD Alzheimer’s disease ADP adenosine diphosphate AP affinity purification APH1A anterior pharynx defective 1 homolog A (C. elegans) APLP1 amyloid beta (A4) precursor-like protein 1 Aβ amyloid beta BRET bioluminescence resonance energy transfer cAMP cyclic adenosine monophophate

Cav voltage-gated calcium channel CD81 CD81 molecule/antigen cDNA complementary DNA co-IP co-immunoprecipitation CICR calcium-induced calcium release CT carboxyl-terminal Cub c-terminal ubiquitin moiety DAG diacylglycerol DAPI 4,6-diamidino-2-phenylindole DPPIV dipeptidyl peptidase 4 ECL extracellular loop ERK extracellular signal-regulated kinase FRET fluorescence resonance energy transfer GABA gamma-aminobutyric acid GABBR2 gamma-aminobutyric acid B receptor, 2 GBP GPCR binding protein GCGR glucagon receptor GDP guanosine diphosphate GIP glucose-dependent insulinotropic peptide GIPR glucose-dependent insulinotropic peptide receptor GLP-1 glucagon-like peptide 1 GLP-1R glucagon-like peptide 1 receptor GLP-2 glucagon-like peptide 2 GLP-2R glucagon-like peptide 2 receptor GLUT glucose transporter GPCR guanine nucleotide-binding protein-coupled receptor GPR37 endothelin receptor type B-like GSIS glucose stimulated insulin secretion GTP guanosine triphosphate HEK human embryonic kidney HPN hepsin xi

HPRD human protein reference database HTP high throughput ICL intracellular loop

IP3 inositol triphosphate

KATP adenosine triphosphate-sensitive potassium

Kv voltage-gated potassium channel MAPK mitogen-activated protein kinase MS mass spectroscopy MYTH membrane-based yeast two-hybrid NT amino-terminal NubG n-terminal ubiquitin moiety w/ glycine at position 13 (mutated) NubI n-terminal ubiquitin moiety w/ isoleucine at position 13 (endogenous) PCR polymerase chain reaction PD Parkinson’s disease Pdx-1 pancreas duodenum homobox 1 PEG polyethylene glycol PI-3K phosphoinositide 3-kinase PKA protein kinase A PKB protein kinase B PLC phospholipase C PPI protein-protein interaction RAMP receptor activity-modifying protein RIA radioimmunoassay RRS ras-recruitment system RT room temperature SGLT sodium-glucose transporter SOS son of sevenless STMN1 stathmin 1/oncoprotein 18 T2DM type 2 diabetes mellitus TAP tandem affinity purification TF transcription factor TM transmembrane UBP ubiquitin-specific protease X-gal bromo-chloro-indolyl-galactopyranoside YTH yeast two-hybrid

Symbol

α alpha β beta p pica μ micro m milli M molar (moles/litre)

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°C degrees Celsius l litre g gram sec second min minute h hour wk week W tryptophan L leucine A adenine H histidine

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CHAPTER 1: GENERAL INTRODUCTION

1.1. GPCR Guanine nucleotide-binding protein-coupled receptors (GPCRs) comprise the largest class of transmembrane (TM) signaling molecules (Vassilatis et al., 2003). GPCRs are activated by diverse endogenous ligands that transduce distinct intracellular signaling cascades involving multiple G-proteins subtypes as well as G-protein independent pathways to regulate a myriad of complex physiological and disease processes. Appropriately, GPCRs compose the targets for at least one-third of all currently approved drugs (Lagerstrom and Schioth, 2008). Despite intensive research effort, little is still known about the precise mechanism of GPCR activation. The two major features of GPCR regulation are: 1) ligand binding to putative membrane surface domains of GPCRs causes its activation; 2) GPCR activation induces dynamic interactions with intracellular binding partners.

1.1.1. Structure GPCRs are commonly categorized into 5 groups based on highly conserved sequence motifs. This implies shared structural features and consequent downstream cell signaling pathways. These families include class-A rhodopsin-like, class-B secretin-like, class-C glutamate-like, Adhesion and Frizzled/Taste2 (Fredriksson et al., 2003) (Figure 1). GPCRs are structurally characterized by seven hydrophobic membrane spanning α-helices of about 25-35 consecutive residues (which form a three-dimensional barrel within the membrane) connected by alternating intracellular (ICL) and extracellular (ECL) loop regions, along with an amino-terminal (NH) extracellular domain and an intracellular carboxyl terminal (CT) extension (Figure 2). Whereas the extracellular NH2-terminus and hydrophobic 7 transmembrane (TM) core of the receptor are involved in ligand binding, intracellular domains, particularly the CT, are important for signal transduction mediated by its binding partners (Rosenbaum et al., 2009). The first and second extracellular loops (ECL1 and ECL2), connected by a disulfide bridge, serve to pack and stabilize the central core (Palczewski et al., 2000). The most conserved residues among GPCRs which determine receptor structure and function lie within TM domains, whereas other domains exhibiting sequence variations confer unique signaling properties to each GPCR. For instance, ICL2 and ICL3 involved in G-protein coupling possess distinct sequences that determine specificity of the particular class of G-proteins that they bind and activate (Rosenbaum et al., 2009).

Figure 1. Phylogenetic Tree of B- class Secretin-like GCPRs. The glucagon superfamily of receptors (in bold) compose the class B1 subclass.

1.1.2. G-Proteins Guanine nucleotide-binding proteins (G-proteins) are a family of GTP hydrolases that play critical roles in coupling the activation of receptors to intracellular responses through various signal transduction pathways (Bourne et al., 1990). Impairment of G-proteins signalling has been associated with various endocrine disorders, cardiovascular defects and certain forms of cancer (Spiegel, 2000; Weinstein et al., 2006). Heterotrimeric “large” G-proteins consist of alpha (α), beta (β) and gamma (γ) subunits (Figure 2), where the Gα subunit contains a guanosine triphosphatase (GTPase) and alpha-helical domain and the latter two compose the beta-gamma (Gβγ) complex. Upon activation of the GPCR following ligand stimulation, conformational changes confers the receptor to act as a guanine nucleotide exchange factor to catalyze the the exchange of guanosine diphosphate (GDP) for guanosine triphosphate (GTP) on the Gα subunit (Bourne et al., 1991). Now in the active GTP-bound state, Gα-GTP and Gβγ dissociate to activate various second messenger cascades and downstream effector proteins, thus making way for the next G-protein to be activated. The two subunits rejoin and return to the inactive GDP-bound state following hydrolysis of the GTP to GDP by the Gα GTPase subunit (Lambert et al., 2008).

There are at least 20 different Gα subunits, which can be divided into four classes, Gαs, Gαi,

Gαq/11 and Gα12/13, each of which mediate distinct downstream effects (Olate and Allende, 1991).

Gαs (which includes olfactory Golf) activates adenylate cyclase to generate the second messenger, cyclic adenosine monophosphate (cAMP) from ATP, which leads to activation of protein kinase A (PKA) (Simonds, 1999). Conversely, Gαi (includes Gi/o and Gz) inhibits adenylate cyclase and the production of cAMP from ATP, but also includes Gt and Ggust which signal through phodiesterase 6 and are important in vision and taste respectively (Didsbury and

Snyderman, 1987; Watts and Neve, 2005). Stimulation of phospholipase C beta (PLCβ) by

Gαq/11 allows the cleavage of phosphatidylinositol 4,5-bisphosphate (PIP2) into second messengers, inositol triphophate (IP3) and diacylglycerol (DAG) which are involved in smooth 2+ muscle contraction and Ca flux (Wilkie et al., 1991). Gα12/13 is involved in regulation of cell migration through cell cytoskeleton remodelling and is part of the Rho family GTPase signaling pathways (Strathmann and Simon, 1991). Finally, in addition to inhibiting the Gα subunit, Gβγ has also been shown to activate various signal transduction pathways including activation of mitogen-activated protein kinases (MAPK), phosphoinositide 3-kinases (PI-3K) and small

GTPases to regulate cellular proliferation (Schwindigner and Rabishaw, 2001). As well, Gβγ also signals through phospholipase C (Wing et al., 2001) and directly regulate both G-protein coupled inward rectifying potassium channels (Lei et al., 2000) and L-type calcium channels (Ivanina et al., 2000). The small GTPases exist in a monomeric form and are homologous to the Gα subunit, capable of switching between the active GTP-bound and inactive GDP-bound states. These members of the Ras GTPase family have been shown to regulate cellular growth, differentiation and motility (Exton, 1998; Macara et al., 1996). Finally, Oka et al (2009) recently reported a fifth class of Gα subunits called Gv which is well conserved in across vertebrate family members.

1.1.3. Interactomes Insights derived from the Human Genome Project revealed that there were fewer protein- coding regions than anticipated (Lader et al., 2001; Venter et al., 2001), and this led to the realization that the higher order complexity of the human genome is not simply dictated by the finite number of proteins, but rather by combinatorial permutations of protein interactions. The previous dogma portrayed the simplistic concept of the GPCR as a single monomeric protein which upon ligand activation interacts only with heterotrimeric G-proteins that catalyze guanine nucleotide exchange (GTP to GDP), has become obsolete. Activated GPCRs have been shown to be more versatile in interacting with a larger variety of accessory proteins known in the literature as GPCR interacting proteins (GIPs) (Figure 2); however to avoid confusion with the peptide hormone GIP, they will be referred to as GPCR binding proteins (GBPs). GBPs have been reported to regulate GPCR targeting, subcellular trafficking and intracellular signaling (Bockaert et al., 2004) (Figure 2). They are TM and cytosolic proteins that bind intracellular domains of GPCRs to form large functional multiprotein networks called “proteomes” or GPCR- associated protein complexes (GAPCs) (Daulat et al., 2009). These GAPCs serve to modulate a number of GPCR activities, including targeting to native cellular compartments, recycling between compartments, cross-linking to cytoskeleton, assembly with other membrane proteins

4 and consequent allosteric activation and the fine tuning of downstream signaling events. Of note, some TM GBPs are themselves GPCRs that form homo- or heterodimers like GABAB receptors (Jones et al., 1998; White et al., 1998). Other TM GBPs are ion channels, ionotropic receptors and single TM proteins. Soluble cytosolic GBPs like scaffolding proteins arrestins, tamalin and cAMP-dependent kinase-anchoring proteins (AKAP), serving as “molecular facilitators” to physically link GPCRs and GBPs into GAPCs by anchoring to their CT tails, while others can change selectivity of a receptor for a specific agonist (RAMP) (McLatchie et al., 1998) or G-protein (calcyon) (Lezcano et al., 2000) or modulate downstream signalling pathways (GIPC, NHERF) (Hu et al., 2003; Mahon et al., 2002). More than 50 cytosolic GBPs have been identified and they include accessory ion channels subunits, protein kinases, small G proteins, cytoskeletal proteins and adhesion molecules. Among them, PDZ domain-containing proteins like SSTRIP, PICK-1 and SAP97 are the most abundant (Bockaert et al., 2004; Maurice et al., 2008). It is evident from these studies that signaling specificity of a GPCR is dependent not only on the nature of the heterotrimeric G proteins to which it is coupled but also on the nature of the GBPs to which it binds.

Figure 2. Examples of GPCR binding proteins (GBPs). G-proteins are signaling proteins which include large heterotrimeric G-proteins with α and βγ subunits as well as the small GTPases such as Rho and ADP-ribosylation factor (ARF). Adapter proteins, such as Nck and Grb2 which bind at their SHC domain, mediate specific protein-protein interactions (PPI) that drive the formation of protein complexes. Scaffolding proteins, such β-arrestins and Homer proteins, facilitate GAPC formation by anchoring multiple proteins to one cellular area and regulating signal transduction pathways. Protein tyrosine phosphatases (PTP), like SHP-2, are signaling molecules that regulate a variety of cellular processes including cell growth, differentiation, mitotic cycle, and oncogenic transformation. PDZ-domain containing GBPs are the most abundant, one of which is Na+/H+ exchanger regulator factor (NHERF) which is required for receptor recycling to the plasma membrane.

1.2. Class B GPCRs Class B GPCRs regulate many endocrine and neuroendocrine functions and are endogenously stimulated by their respective peptide hormones. These receptors have a unique set of signature motifs and a lack of homology with other GPCR classes, like the ASP-Arg-Try (DRY) motif and prolines conserved among class-A receptors (Lagerstrom and Schioth, 2008). They contain signature sequences within ICL1 which may be important in protein folding and in the surface expression of the receptor. Most characteristic of the class-B receptors is its long NT extracellular tail region of 100-200 amino acids with six highly conserved cysteine residues which comprise 3 disulfide bonds that are critical for ligand binding (Grauschopf et al., 2000; Lisenbee et al., 2005). Grace et al. (2004) demonstrated the key role played by these bonds and two antiparallel β-sheet regions to establish a stable base for peptide ligand binding. Similarly, the CT tail contains six highly conserved cysteine residues that form three conserved intracellular domain disulfide bonds critical for establishing functional receptor conformation (Asmann et al., 2000) (Figure 3). All of the class-B receptor ligands are moderately long peptides in excess of 25 residues that have diffuse pharmacophoric domains. In addition to the prototype member, the secretin receptor, class-B GPCRs include many members of medical importance such as the calcitonin, corticotropin-releasing factor (CRF), growth hormone- releasing hormone (GHRH), parathyroid hormone (PTH), pituitary AC-activating peptide (PACAP), and vasoactive intestinal polypeptide receptors (VIPR) (Dong et al. 2008; Grace et al. 2007) (Figure 1). The current ligand-receptor binding model is a two-step mechanism whereby the ligand C-terminus interacts with the receptor extracellular N-terminal (NT) domain which at least in part dictates both ligand affinity and specificity and is believed to lead to conformational changes that exposes the endogenous ligand (Dong et al., 2003; López de Maturana et al., 2003). This is followed by interaction of ligand N-terminus with the receptor 7TM core domains (TM helices and connecting loops) to trigger intracellular signal transduction (Dong et al., 2004; Wittelsberger et al., 2006).

Figure 3. Structure of a B-class GPCR. The long amino-terminal and carboxyl-terminal tails contain 6 highly conserved cysteine (orange) residues which comprise 3 disulfide bonds (black lines) that are critical for ligand binding.

1.3. Glucagon Superfamily of Receptors A subclass of the class-B GPCRs includes the glucagon superfamily of receptors which are all named after their specific peptide hormone: glucagon and the glucagon-like peptides, GLP-1 and GLP-2, which are all encoded on the proglucagon gene (Irwin 2001), and glucose- dependent insulinotropic peptide (GIP) (Mayo et al. 2003) (Figure 1). These hormones target receptors which are expressed in a broad variety of cell types that comprise the gastroentero- pancreatic-brain axis, mediate diverse and profoundly important physiologic actions on brain satiety centers, pancreatic islet hormone secretion, islet cell proliferation and apoptosis, gastrointestinal motility, mucosal growth and nutrient absorption and assimilation (Brubaker and Drucker, 2002; Drucker, 2007). Perturbation in the release of these hormones or their receptor signaling dysfunction contribute to corresponding disease processes including the dysregulation of central and peripheral target cells that collectively underlie the abnormal glucose homeostasis in obesity and type 2 Diabetes Mellitus (T2DM) (Drucker, 2007). Below I describe each member of the B-class glucagon subfamily of receptors in the order by which I screened them with the yeast two-hybrid system as outlined in chapter 3. Each receptor’s cellular actions are summarized in tables 1-4 where any function that was lost as a result of receptor knockout or induced by a dose concentration of less than 1 nM was considered physiological.

1.4. Glucagon-Like Peptide 1 and GLP-1R

1.4.1. Expression GLP-1, along with GLP-2, oxyntomodulin and glicentin, are transcribed from the proglucagon gene and released from proglucagon by post-translational processing by prohormone convertase-1 from specialized intestinal enteroendocrine called L-cells (Mojsov et al., 1986). The circulating bioactive forms of GLP-1, GLP-1(7-36) and GLP-1(7-37), are generated from GLP-1(1-37) and are both equipotent (Orskov et al., 1994). Due to an alanine at position 2, GLP-1 is rapidly degraded within minutes by DPPIV to GLP-1 (9-36) amide or GLP-1 (9-37). Plasma levels of GLP-1 are low in the fasted state, in the range of 5–10 pmol/L, and elevate rapidly 3- to 5-fold within minutes of food intake, reaching 15–50 pmol/L, well before direct contact with L cells, thus implicating the potential role of neural and endocrine mechanisms in GLP-1 secretion (Drucker 2006). Exendin-4 is a 53% homologous lizard peptide full GLP-1 agonist and the truncated peptide exendin 9–39 is a potent antagonist of the receptor (Goke et al., 1993). All the actions of GLP-1 are believe to be mediated through the only discovered GLP-1 receptor (GLP-1R), however there is suggestive evidence of a distinct GLP-1(9-36) receptor in the heart (Ban K et al., 2008; Nikoloaidis et al., 2005b). GLP-1R expression has

7 been shown in pancreatic islet α and β cells, kidney, lung, heart, stomach, gastrointestinal tract and multiple regions of the peripheral and central nervous system (Wei and Mojsov, 1995; Bullock et al., 1996).

1.4.2. Structure The GLP-1R is a 463 amino acid (aa) long heptahelical class-B G-protein coupled receptor (Drucker et al., 1987; Goke and Conlon, 1988; Thorens 1992) encoded from its gene that has been mapped to chromosome 6p21.1 (Stoffel et al., 1993). The receptor is characterized by a large hydrophilic, extracellular domain and seven hydrophobic TM domains that are linked by hydrophilic intracellular and extracellular loops (Thorens and Widmann, 1996). Both the NT domain and TM domains 1 to 3 are critical for proper ligand binding (Wilmen et al., 1997; Xiao et al., 2000), while G protein interaction domains are contained within the ICL3 (Hallbrink et al., 2001; Salapatek et al., 1999; Takhar et al., 1996). Bazarsuren et al. (2002) identified 3 pairs of cysteine residues in the NT which form disulfide bridges, while Widman et al. (1997) identified 3 pairs of serine residues in the CT which represent phosphorylation sites important in agonist- induced desensitization, internalization and heterologous desensitization of the GLP-1R. Ligand binding studies suggest that GLP-1 NT binds ECL1 and the EC end of TM helix 2 of the GLP-1R following initial interaction of the GLP-1 CT with the GLP-1R NT (Al-Sabah and Donnelly, 2003; López de Maturana et al., 2004). The crystal structure of the GLP-1R extracellular domain was recently reported and revealed that the GLP-1R antagonist Exendin- 4(9-39) is an amphipathic α-helix forming both hydrophobic and hydrophilic interactions with GLP-1R NT (Runge et al., 2008).

1.4.3. Function GLP-1, secreted primarily from the distal gut in response to carbohydrates and fat in the intestinal lumen, stimulates insulin secretion in a glucose-dependent manner from pancreatic beta cells (Kreymann et al., 1987) and suppresses glucagon secretion from pancreatic α-cells (Creutzfeldt et al., 1996; Orskov et al., 1988). The inhibition of glucagon secretion may be mediated directly through GLP-1R expressed on α-cells or indirectly through insulin or somatostatin secretion from beta cells and delta cells containing GLP-1Rs (Drucker 1998). GLP-1 has also been shown to further increase insulin secretion by upregulating proinsulin gene transcription and biosynthesis (Drucker, 1987; Fehmann and Habener, 1992; Fehmann et al.,1995) as well as enhancing expression of glucose-sensing genes including pancreas duodenum homobox 1 (Pdx-1), glucokinase and glucose transporter 2 (GLUT2) (Zhou et al., 2002).

GLP-1R agonists also promote beta cell survival by enhancing beta-cell proliferation and neogenesis (Edvell and Lindstrom, 1999; Kim et al., 2003; Stoffers et al., 2000; Xu et al., 1999) and protecting β-cells from ER stress (Yusta et al., 2006) and apoptosis (Buteau et al., 2004; Farilla et al., 2003; Li et al., 2003). Additionally, a recent study showed that GLP-1 agonist, exendin-4 protects cholangiocytes from apoptosis (Marzioni et al., 2009) and dopaminergic neurons against degeneration (Harkavyi et al., 2008; Li et al., 2009) both in vitro and in vivo. GLP-1 also acts on the brain to regulate appetite both centrally and peripherally through vagal afferent nerves which project to localized hypothalamic nuclei (Vrang et al., 2003; Wettergren et al., 1997). GLP-1 inhibits gastric emptying and acid secretion (Schirra et al., 1997; Schmidtler et al., 1994) and decreases food intake (Szayna et al., 2000; Turton et al., 1996; Young et al., 1999). A number of novel GLP-1 actions have recently been reported. GLP-1 was found to maintain or enhance sweet taste sensitivity (Shin et al., 2008). Intravenous infusion of GLP-1 could act on the neuronal tyrosine hydroxylase gene transcription of the sympathetic nervous system which enhanced sympathetic outflow, causing increased heart rate and blood pressure (Barragan et al., 1999; Yamamoto et al., 2002; Poornima et al., 2008). Finally, GLP-1 exhibits some cardioprotective actions, where it was observed to improve myocardial function and cardiac output in experimental models of cardiac injury and heart failure (Bose et al., 2005; Nikolaidis et al. 2004a,b). Interestingly, GLP-1R knockout mice are viable and present only mild fasting hyperglycemia and mild glucose intolerance (Scrocchi et al., 1996). Abnormalities are also seen in AC and β- cell signaling (Flamez et al., 1999), neuroendocrine response (MacLusky et al., 1999), islet size and topography (Ling et al., 2001) and in sensitivity to β-cell and neuronal injury (During et al., 2003; Li et al., 2003). However, feeding behaviour, body weight (Scrocchi et al., 1996), glucagon secretion and glucose utilization are all normal. Finally, mice lacking the GLP-1R receptor had a reduced resting heart rate and elevated left ventricular (LV) end-diastolic pressure which progressed to increased LV thickness and impaired LV contractility and diastolic function following insulin administration (Gros et al., 2003).

Physiological Action Reference(s)

↑ insulin secretion Kreymann et al. (1987). Lancet 2:1300-4.

↑ proinsulin biosynthesis Drucker et al. (1987). Proc Natl Acad Sci USA 84:3434–38.

↑ glucose sensing genes Zhou et al. (2002). J Cell Physiol 192:304-14.

↑ β-cell proliferation Edvell and Lindstrom. (1999). Endocrinology 140:778–83.

↓ β-cell apoptosis Farilla et al. (2003). Endocrinology 144: 5149-58.

↓ glucagon secretion Orskov et al. (1988). Endocrinology 123: 2009–13.

↓ GI secretion and motility Wettergren et al. (1993). Dig Dis Sci 38: 665–73.

↓ food intake Turton et al. (1996). Nature 379:69-72.

Pharmacological Action Reference(s)

↑ cardiac function Gros et al. (2003). Endocrinology 144: 2242–52.

Li et al. (2009). Proc Natl Acad Sci U S A 106:1285-90. ↑ protection of other cell types Marzioni et al. (2009). Gut 58:990-7.

Table 1. Summary of GLP-1 actions.

1.4.4. Signaling

While the GLP-1R has been shown to activate Gαs, Gαi, and Gαo (Hallbrink et al., 2001) via ICL3, in islet β-cells, it predominantly acts on Gαs which couples and activates AC, causing increased 2+ cAMP accumulation and [Ca ]i, which collectively effect insulin secretion in the presence of glucose (Drucker et al., 1987; Goke et al., 1989). cAMP acts on two major substrates, PKA and cAMP-regulated guanine nucleotide exchange factor II (cAMP-GEF II), a major PKA- independent pathway, which then act on distinct as well as synergistic downstream cellular targets and signaling, effecting a host of cellular actions. For example, these PKA and cAMP cellular receptors work synergistically to close ATP-sensitive potassium (KATP) channels causing membrane depolarization culminating in opening of voltage-gated calcium channels (Cav) (Macdonald and Wheeler, 2003). This results in an increase in intracellular calcium 2+ concentration ([Ca ]i) which stimulates mitochondrial ATP production, which further promotes membrane depolarization ATP-mediated closure of KATP channels. The increased levels of cAMP, intracellular calcium and ATP trigger exocytosis of insulin granules (Holst and Gromada, 2004). Furthermore, Macdonald et al. (2002b, 2003) showed that GLP-1 prolongs the + excitatory effect on GSIS by inhibiting repolarizing voltage-gated K currents (Kv) through a PKA- and PI-3K/protein kinase B (PKB) (Akt)-dependent pathways. As well, GLP-1-dependent stimulation of calcium induced calcium release (CICR) from intracellular stores occurs via IP3 and ryanodine-sensitive pathway (Holz et al., 1999), and in a cAMP-dependent, PKA- independent manner through small G proteins distinct from Gαs (Kang et al., 2001; Kashima et al., 2001). GLP-1 also activates ERK1/2 and PLC in some cell types to further stimulate calcium influx and increase cytosolic free calcium (Montrose-Rafizadeh et al., 1999; Wheeler et al.,

1993). Finally, GLP-1-mediated closure of KATP channels, and the differential effect of adenosine diphophate (ADP) levels on KATP channel closure may provide a cellular mechanism for the glucose-sensitivity of GLP-1 action in β-cells (Light et al., 2002). GLP-1 stimulates insulin gene transcription and biosynthesis through cAMP/PKA-dependent 2+ and –independent signaling pathways to increase [Ca ]i (Drucker et al., 1987; Fehmann and Habener, 1992), nuclear factor of activated T (NFAT) cells (Lawrence et al., 2002) and Pdx-1 (Wang et al., 1999) expression. GLP-1R activates expression of immediate early gene encoding transcription factors that regulate islet cell proliferation and differentiation through transactivation of the epidermal growth factor receptor (EGFR), which leads to increases in PI- 3K and activation of Akt- PKB (Buteau et al., 2003). The mechanism whereby GLP-1R induces β-cell replication includes IRS-2 signaling (Park et al., 2006), activation of cAMP/PKA, PI-3K, and MAPK signaling pathways, and up-regulation of cell cycle regulator cyclin D1 (Friedrichsen et al., 2006). The cytoprotective effects of GLP-1R is mediated through activation cAMP/PKA and phosphorylation of cAMP response element binding protein (CREB) which leads to activation of IRS-2 and induction of the Akt-PKB growth and survival pathway (Jhala et al., 2003; Wang and Brubaker, 2002) and upregulation of the important cellular regulator of apoptosis, nuclear factor-κB (NKκB) (Buteau et al., 2004).

1.4.5. Regulation Several studies have shown that prolonged exposure to native GLP-1 or the GLP-1R agonist, exendin-4 leads to rapid desensitization and internalization of the GLP-1R (Fehmann and Habener, 1991; Baggio et al, 2004). This process is strictly dependent on phosphorylation of three serine residues within the CT tail of GLP-1R, however, the putative protein kinases remain undefined (Widmann et al., 1997). Patients taking exendin-4 for 30 weeks continue to see improvement in their HbA1c levels and postprandial glycemia excursion, suggesting that prolonged administration of GLP-1 agonist does not cause any noticeable receptor densensitization in vivo (Buse et al., 2004). As well, GLP-1R expression has been shown to be downregulated by both glucose and dexamethasone (Abrahamsen and Nishimura, 1995). GLP-1R has been shown to localize in lipid rafts (including a direct interaction of GLP-1R and caveolin-1) which was proved to be necessary for receptor subcellular localization, trafficking and signaling activity (Syme et al., 2006). Additionally, Sonoda, et al. (2008) later demonstrated that the physical association between GLP-1R and the scaffolding proteins β-arrestin-1,2, a protein involved in GPCR agonist-induced desensitization and endocytosis, is required to stimulate cAMP production and insulin secretion in INS-1 β-cell line. Finally, Mahon and Shimada (2005) demonstrated calcium-dependent calmodulin interaction with the cytoplasmic tails of a subset of class-B GPCRs, including GLP-1R.

1.5. Glucose-dependent Insulinotropic Peptide and GIPR

1.5.1. Expression GIP is a 42-aa peptide hormone processed from a 153-aa proGIP precursor via prohormone convertase 1/3 posttranslational processing. It is secreted from enteroendocrine K cells of the proximal small bowel and from specialized neurons in the brain. Full length bioactive GIP (1- 42) is rapidly cleaved within minutes to bioactive GIP (3-42) by DPPIV. Fasting levels of GIP range from 12 to 92 pM, and are elevated 10- to 20-fold within minutes of ingestion of absorbable carbohydrates, amino acids or lipids to 35 – 235 pM (Jorde et al., 1983). Whereas GLP-1 exerts many of its effects indirectly by paracrine actions, GIP seems to exert direct endocrine actions on distant target cells possessing GIPRs. The GIPR is expressed in pancreatic β-cells, stomach, small intestine, adipose tissue, adrenal cortex, pituitary, heart, testis, endothelial cells, bone, trachea, spleen, thymus, lung, kidney, thyroid, and several regions in the CNS (McIntosh et al., 2009).

1.5.2 Structure The human GIPR is a 455-aa long heterotrimeric GPCR which is encoded on a gene located on chromosomal 19q13.3 (Gremlich et al., 1995; Usdin et al., 1993; Yamada et al., 1995). Alternative mRNA splicing results in GIPR variants of varying lengths, but the precise tissue distribution and functional relevance of these splice variants remain to be further elucidated (Gremlich et al, 1995; Volz et al., 1995). Sequences extending to residue 222 within TM domain 3 are critical for ligand binding and G protein activation (Gelling et al., 1997). More specifically, bioactive domains at residues 1-14 and 19-30 of NT activate cAMP formation (Hinke et al., 2001), while serines 426-427 (Wheeler et al., 1999) and serine 406 – cysteine 411 (Tseng and Zhang, 1998b) of the CT are involved in receptor desensitization and internalization, respectively. A minimum receptor length of 405-aa seems to be necessary for proper transport and insertion into the membrane. The CT is the major site for AC coupling and modulating binding affinity (Tseng and Zhang, 1998a; Wheeler et al., 1999). A threonine substitution for proline at residue 340 within TM domain 6 resulted in a constitutively active receptor GIPR that generates cAMP production (Tseng and Lin, 1997). Amiranoff et al. (1985) showed that the NT domain of GIPR contains consensus sequences for N-glycosylation, indicating the latter to be required for GIPR cell surface expression (Lynn, 2003). The recently resolved crystal structure of the GIPR extracellular domain revealed that the CT region assumes an α-helical conformation when it binds by hydrophobic interactions to a surface groove of the receptor,

12 whereas the GIPR NT region remains free to interact with other parts of the receptor (Parthier et al., 2007).

1.5.3 Function GIP was first discovered for its ability to inhibit gastric acid secretion (Brown and Pederson, 1969; Brown et al., 1970, 1982) and hence its original name gastric inhibitory peptide. However, GIP is most well known for its incretin action (Dupre et al., 1973), which like GLP-1, includes stimulation of insulin gene transcription and proinsulin biosynthesis (Schäfer and Schatz, 1979) as well as proliferative (Trumper et al., 2001) and anti-apoptotic action in β-cells (Ehses et al., 2003; Kim et al., 2005; Trumper et al., 2002) and CNS (Buhren et al., 2009; Nyberg et al., 2005). Additionally, GIP-mediated increases in glucose uptake involve both trafficking of sodium-dependent glucose transporter 1 (SGLT1) into the intestinal epithelial cell brush-border membrane (Cheeseman, 1997) and GLUT2-dependent transport in the basolateral membrane (Cheeseman and O’Neill, 1998; Cheeseman and Tsang, 1996). GIP plays a role in adipocyte biology as shown in studies involving K cell ablation, GIPR antagonist treatment and GIPR deletion (mice), all of which conferred protection from high-fat diet induced obesity (Althage et al., 2008; Miyawaki et al., 2002; Yip and Wolfe, 2000). Furthermore, GIP seems to promote adipokine secretion of plasma resistin, LPL activity and triglyceride storage (Hansortia et al., 2007; Kim et al. 2007a,b). Finally, GIP also seems to have an anabolic effect in bone, promoting new bone formation (Bollag et al., 2001), while GIPR (-/-) mice showed enhanced bone turnover and reduced parameters in bone formation (Xie et al. 2005). While no major cardiovascular effects of GIP have been reported, GIP nonetheless plays a role in regulation of splanchnic (Kogire et al., 1988,1992) and islet blood flow (Svensson et al., 1997).

Physiological Action Reference(s)

↑ insulin secretion Dupre et al. (1973). J Clin Endocrinol Metab 37:826-8.

↑ proinsulin biosynthesis Schäfer & Schatz. (1979). Acta Endocrinol 91:493-500.

↑ β-cell proliferation Trümper et al. (2001). Mol Endocrinol 15:1559-70

↓ β-cell apoptosis Trümper et al. (2002). J Endocrinol 174:233-46

↑ glucose uptake Cheeseman &Tsang. (1996). Am J Physiol 271:G477–82.

regulates fat metabolism Yip & Wolfe. (2000). Life Sci 66:91-103

regulate HFD-induced obesity Miyawaki et al. (2002). Nat Med 8:738-42.

Pharmacological Action Reference(s)

↓ gastric acid secretion Brown. (1969). Can J Physiol Pharmacol 47:113–114.

↑ bone formation Bollag et al. (2001). Mol Cell Endocrinol 177(1-2):35-41.

Kogire et al. (1988). Gastroenterology 95:1636–1640. ↑ blood flow Svensson et al. (1997). Peptides 18:1055–9.

Table 2. Summary of GIP actions.

1.5.4 Signaling GIP enhances GSIS by activating AC (Lu et al., 1993) to generate intracellular cAMP production, which acts on PKA-dependent (Ding and Gromada, 1997) and PKA-independent pathways. In the latter, cAMP acts directly on cAMP-GEFII (Holz, 2004; Seino and Shibasaki, 2005) which have direct effects on stimulating the exocytotic machinery among other actions, particularly calcium release pathways (Holst and Gromada, 2004). GIP potentiates membrane 2+ depolarization by inducing PKA-mediated closure of KATP channel leading to increased [Ca ]i levels through opening of Cav, non-selective ion channels and CICR (Lu et al., 1993; Wheeler et al., 1995) from intracellular stores via ryanodine and IP3 receptors (Holz et al., 2006; Kang et al,

2005). GIP further stimulates insulin secretion by activating iPLA2 leading to arachidonic acid 2+ production and increased [Ca ]i (Ehses et al., 2001; Wheeler et al., 1995). GIP has also been 2+ shown to inhibit Kv, thus prolonging β-cell action potential and potentiating the Ca signal, most likely via both PKA- and PI-3K/PKB (Akt)-dependent effect (MacDonald and Wheeler, 2003; MacDonald et al., 2002b, 2003). Also secondary to this rise in cAMP, GIP can stimulate growth-factor dependent pathways including p38 MAPK and ERK1/2 (Ehes et al., 2003; Kubota et al., 1997) and PI-3K/PKB-Akt (Kim et al., 2005; Trumper et al., 2001). GIP also influences β-cells apoptosis by stimulating expression of anti-apoptotic Bcl-2 gene through PKA-mediated dephosphorylation of AMP- activated protein kinase (AMPK), inducing nuclear entry of cAMP-responsive CREB coactivator 2 (TORC2), and phosphorylation of CREB (Kim et al., 2008). GIP can also mediate PKB/Akt activation to effect reduction of Bax levels, and this is by phosphorylation and consequent nuclear exclusion of transcription factor Foxo1 (Kim et al., 2005).

1.5.5 Regulation At normoglycemia, GIPR expression is upregulated in response to a dietary fatty acid load via activation of PPARα, while at hyperglycemia, it is downregulated in response to a glucose load (Lynn et al., 2003) in a manner independent of PKA or PKC (Hinke et al., 2000a). As well, Zhou

14 et al. (2007) recently showed that the downregulation of GIPR action seen under hyperglycaemic conditions is due in part to receptor ubiquination. As well, both G protein- coupled receptor kinase 2 (GRK2), and β-arrestin 1 have been implicated in GIP-mediated desensitization and cAMP accumulation leading to insulin secretion (Tseng and Zhang, 1998, 2000).

1.6 Glucagon-Like Peptide 2 and GLP-2R

1.6.1 Expression GLP-2 is a peptide hormone which is cosecreted with GLP-1 from the intestinal L-cells in response to nutrient ingestion (Brubaker et al., 1997) and degraded by DPPIV (Drucker et al, 1997). GLP-2(1-33) is the product of post-translational processing of proglucagon by prohormone covertase-1/3 (Bell et al., 1983; Mojsov et al., 1986; Monroe et al., 1999). All the effects of GLP-2 are mediated in a primarily endocrine manner through GLP-2Rs expressed tissue-specifically in the endocrine cells, subepithelial myofibroblasts and enteric neurons of the stomach, small and large intestine, selected brain neurons and the lung (Munroe et al., 1999; Yusta et al., 2000).

1.6.2 Structure The GLP-2R is a 553-aa GPCR cloned from the human hypothalamic and intestinal cDNA libraries and transcribed from a gene localized to human chromosome 17p13.3 (Munroe et al., 1999). DeCambra et al. (2000) showed that GLP-2R structure and ligand-receptor interface could be modulated by generating position 2 single amino acid substitutions within the GLP-2R, suggesting that these residues were important in GLP-2R binding and receptor activation. The CT seems to be important for mediating cell surface expression, receptor trafficking and PKA- mediated heterologous receptor desensitization (Estall et al., 2005).

1.6.3 Function Based on evidence from work on intestinal glucagonomas (Gleeson et al., 1971; Stevens et al., 1984), Drucker et al. (1996) discovered the principal roles of GLP-2 are to maintain the growth and absorptive function of intestinal mucosal villus epithelium through stimulation of mucosal growth in the small and large intestine and inhibition of enterocyte and crypt cell apoptosis (Burrin et al., 2000; Tsai et al., 1997). The trophic and pro-absorptive actions of GLP-2 have to suggested widespread clinical applications, particularly the treatment of intestinal diseases such as short bowel syndrome (Jeppesen et al., 2001), small bowel enteritis (Boushey et al., 1999), colitis (Drucker et al., 1999), inflammatory bowel disease (Alavi et al., 2000), as well as

15 promoting intestinal mucosal repair following small bowel surgical or chemical injury (Prasad et al., 2001). GLP-2 has profound effects on enterocyte nutrient transport, upregulating SGLT-1 transport activity and increasing GLUT-2 localization to the basolateral membrane in rat small intestine (Au et al., 2002; Cheeseman, 1997), increasing enteral lipid absorption and chylomicron production (Hsieh et al., 2009), and raising intestinal blood flow (Guan et al., 2003). Furthermore, studies by Benjamin et al. (2000) showed that GLP-2 improves survival and decreases bacterial infection of the intestine by reducing gut permeability through enhancement of intestinal epithelial barrier function. GLP-2 has many extra-intestinal actions including reducing bone resorption and increasing bone mineral density (Haderslev et al., 2002; Henriksen et al., 2003), relaxing intestinal smooth muscle (Amato et al., 2009), inhibiting gastric acid secretion (Wojdemann et al., 1999) and emptying (Bozkurt et al., 2002; Nagell et al., 2004), reducing food intake following ICV administration (Tang-Christensen et al., 2000) and potentially playing a proliferative and anti- apoptotic role in the brain (Lovshin et al., 2004; Velázquez et al., 2003). Finally, unlike the other three hormones, GLP-2 has no effect on glucose homeostasis at physiological concentrations; however, at pharmacological levels, GLP-2 can stimulate glucagon secretion in both fasted and postprandial states (Meier et al., 2006) through activation of GLP-2R expressed on α cells (de Heer et al., 2007).

Physiological Action Reference(s)

↑ intestinal proliferation Drucker el al. (1996). Proc Natl Acad Sci U S A 93:7911-6.

↓ intestinal apoptosis Tsai et al. (1997). Am J Physiol 273:E77-84.

↑ intestinal nutrient absorption Au et al. (2002). Biochem J 367:247-54.

↓ gut permeability Benjamin et al. (2000). Gut 47:112-9.

Bozkurt et al. (2002). Regul Pept 107:129-35. ↓ gastric acid and motility Wøjdemann et al. (1999). J Clin Endocrinol Metab 84:2513-7.

Pharmacological Action Reference(s)

↓ bone resorption Henriksen DB et al. (2003) J Bone Miner Res 18:2180-9.

↓ food intake Tang-Christensen et al. (2000). Nat Med 6:802-7.

↑ neural cell survival Lovshin et al. (2004). Endocrinology 145:3495-506.

↑ glucagon secretion Meier et al. (2006). Gastroenterology 130:44-54.

Amato et al. (2009). Am J Physiol Gastrointest Liver Physiol relaxes gut smooth muscle 296:G678-84.

Table 3. Summary of GLP-2 actions.

1.6.4 Signaling

GLP-2 mainly signals through activation of AC through Gαs subunit to increase intracellular cAMP and activate PKA (Yusta et al., 1999). However, in some cells GLP-2 has been shown to activate ERK1/2 in a Gαi/o-, Gβ/γ-, and Ras-dependent manner to regulate apoptosis (Koehler et al., 2005). Furthermore, Yusta et al. (2000, 2002) shows that the anti-apoptotic effect of GLP-2 is not dependent on cAMP, PKA, PI-3K or PKB-Akt. While the mechanism by which GLP-2 inhibits apoptosis is still unclear, GLP-2 signaling has been shown to block the proapoptotic factors glycogen synthase kinase-3 (GSK3) and Bad while upregulating Bcl-2 expression (Burrin et al., 2005; Yusta et al., 2002). Yusta et al. (1999) also showed GLP-2 to activate additional signaling events including AP-1-dependent signaling, immediate early gene expression, and p70 S6 kinase activity. Finally, the intestinal proliferative effects of GLP-2 are thought to be mediated indirectly primarily through insulin-like growth factor-1 and 2 since the GLP-2R is not expressed in enterocytes (Dubé et al., 2006).

1.6.5 Regulation Like most GPCRs, GLP-2R undergoes desensitization and internalization following acute ligand stimulation which is most likely PKA-mediated (Lovshin et al., 2001). However, prolonged exposure to GLP-2 for over 12 weeks did not cause GLP-2R desensitization in vivo (Tsai et al., 1997). Estall et al. (2004) later showed colocalization with the lipid raft marker caveolin-1 and demonstrated a separate clathrin- and dynamin-independent, lipid raft-dependent pathway for homologous GLP-2R internalization. A year later, Estall et al. (2005) showed that specific amino acids within the CT associate with β-arrestin-2; however, this interaction is not required for homologous receptor desensitization and subsequent resensitization.

1.7 Glucagon and GCGR

1.7.1 Expression Glucagon, a 29-amino acid (Bromer et al., 1956), is produced from the tissue-specific posttranslational processing of proglucagon by prohormone convertase-2 (Furuta et al., 1998; Mojsov et al., 1986). It is secreted mainly from the pancreatic α cells (Baum et al., 1962), but

17 has also been detected in the stomach, intestine and specialized neurons of the brain (Baetens et al., 1976). While it remains unclear how glucagon is degraded and cleared, dipeptidyl peptidase IV (DPPIV) has been shown to cleave glucagon in vitro but not in vivo (Hinke et al., 2000b), and neutralendopeptidase 24.11 has been implicated in regulating porcine glucagon levels (Trebbien et al., 2004). All actions of glucagon are mediated through its one specific receptor, the glucagon receptor (GCGR), which is expressed primarily in the liver and kidney, but low levels are also found in the heart, adipose tissue, spleen, thymus, adrenal glands, ovary, testes, pancreatic islet alpha and beta cells, brain and intestinal smooth muscle (Svoboda et al., 1994; Dunphy et al., 1998).

1.7.2 Structure The human GCGR is a 477-aa protein with a putative 27-aa signal peptide that is presumably cleaved between A27 and Q28 to yield a mature 450-aa receptor, consisting of a 121-aa extracellular amino-terminal domain, a 404-aa seven-helical core, and a 73-aa intracellular CT domain. The receptor is encoded on a gene localized to chromosome 17, 17q25 (Lok et al., 1994; MacNeil et al., 1994; Menzel et al., 1994). Structure-function studies have shown that all 7 TM helices, which contain four N-linked glycosylation sites, are required for proper folding and processing of the receptor (Iyengar and Herberg, 1984; Unson et al. 1995). The NT extracellular portion, particularly the ECL1, is important for both glucagon binding and receptor activation

(Unson et al. 2002). The ICL2 seems to be necessary for coupling to Gαs while ICL2 and ICL3 are required for proper glucagon receptor signaling (Cypress et al. 1999). The CT tail seems to be involved in mechanisms regulating the functional level and activity of the receptor, as well as containing the serine residue phosphorylation sites required for receptor internalization (Heurich et al., 1996).

1.7.3 Function Glucagon release is stimulated by hypoglycemia which depolarizes the α-cell membrane by opening KATP channels (Gromada et al. 2007). Conversely, hyperglycemia leads to closure of

KATP channels, causing membrane hyperpolarization and consequent cessation of glucagon secretion (Shi et al., 1996). Many paracrine factors inhibit glucagon secretion by hyperpolarizing the α cell membrane (Gromada et al. 2007). For example, somatostatin hyperpolarizes α cells through activation of a low conductance K+ channel coupled to inhibitory G-proteins (Ferich et al., 1974; Koerker et al., 1974), whereas, GABA hyperpolarizes the membrane by activating Cl- influx (Wendt et al., 2004; Xu et al., 2006), and GLP-1, insulin and 2+ Zn activate KATP channels (Franklin et al., 2005; Ishihara et al., 2003; Maruyama et al., 1984;

Rorsman et al., 1989). A recent study by Cabrera et al. (2008) demonstrated that glutamate released from α-cells in response to low glucose acts on ionotropic glutamate receptors (iGluRs) expressed on α-cells, which potentiated glucagon secretion. This is intriguing as low glucose alone may be insufficient to stimulate glucagon secretion and would require this positive feedback autocrine action of glutamate to optimize glucagon secretion to maintain normoglycemia (Cabrera et al, 2008). Glucagon itself can also exert autocrine effects on α- cells; however, the physiologic extent and nature (stimulatory or inhibitory) of this autocrine action remain unclear (Ma et al., 2005). Glucagon acts mainly on the liver to release glucose into the circulation, thereby counteracting the action of insulin. Specifically, glucagon’s actions on the liver include glycogenolysis (Sutherland, 1950) and gluconeogenesis from lactate, pyruvate, glycerol and certain amino acids (Claus et al., 1983). As such, it is currently used in clinical practice to counteract hypoglycaemic incidents, particularly in type 1 Diabetic patients (Collier et al., 1987). An increased ratio in the glucagon to insulin ratio in the liver can also promote the release of lipid stored in the liver and other tissues (Steinberg et al., 1959). Glucagon has also been shown to directly stimulate insulin secretion (Samols et al., 1966) through its receptors expressed on pancreatic β-cells (Kawai et al., 1995) but this seems to have no effect physiologically (Moens et al., 2002). As well, at super-physiological levels, glucagon increases heart rate and blood pressure (Farah, 1983) and induces relaxation of intestinal smooth muscle (Taylor et al., 1975). A recent study showed the importance of glucagon and GCGR signaling in promoting hepatocyte survival. Here, glucagon administration increased the survival of hepatocytes Fas ligand induced injury, and conversely, GCGR (-/-) mice were found to be more susceptible to liver injury (Sinclair et al, 2008). Some controversial reports suggest that glucagon promotes lipolysis (Richter et al., 1989) as well as activates the hypothalamic-pituitary-adrenal gland (HPA) axis to release ACTH and cortisol (Arvat et al., 2000). Gelling et al. 2003 generated the GCGR knockout mouse and reported it to have a significant increase in total pancreatic weight, marked islet α cell hyperplasia, extremely large elevations in circulating levels of circulating glucagon and GLP-1, and mild reproductive abnormalities. As well, GCGR signaling in the liver is profoundly affected in these mice, as GCGR -/- hepatocytes exhibit increased susceptibility to apoptotic injury and major defects in lipid oxidation leading to excessive accumulation of lipid in the liver during fasting (Sinclair et al., 2008). Furthermore, multiple defects in islet development were observed in mice lacking the GCGR including loss of control of cell replication (Vuguin et al., 2006).

Physiological Actions Reference(s)

Sutherland. (1950). Recent Prog Horm Res 5:441–459. ↑ blood glucose Claus et al. (1983) Glucagon I pp 315–360, Springer-Verlag.

↑ lipid mobilization Schade et al. (1979). Metabolism 28(8):874-86.

↑ insulin secretion Kawai et al. (1995). Diabetologia 38:274–6.

Pharmacological Actions Reference(s)

↑ cardiac function Farah AE. (1983). Pharmacol Rev 35(3):181-217.

relaxes gut smooth muscle Taylor I et al. (1975). Gut 16(12):973-8.

↑ hepatocye survival Sinclair et al. (2008). Gastroenterology 135(6):2096-106.

↑ HPA hormones Arvat et al. (2000). Pituitary 3(3):169-73.

Table 4. Summary of glucagon actions.

1.7.4 Signaling Most of glucagon’s cellular effects are mediated through glucagon receptor activation of AC via the heterotrimeric G-protein Gαs to produce cAMP, leading to activation of PKA, which results in 2+ increased [Ca ]i. However, glucagon has been shown to induce intracellular calcium release through both Gαs- and Gαi-activated pathways and PLC/IP3 (Wakelam et al., 1986; Hansen et al., 1998). Jiang et al. (2001) showed that the GCGR activates the MAPK pathway in a dose- dependent phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2), an effect 2+ mediated by Gαs-mediated elevation in intracellular [Ca ] via cAMP-dependent PKA activation.

1.7.5 Regulation Like many GPCRs, continual exposure to the glucagon agonist in vitro leads to desensitization and internalization of the receptor (Authier et al., 1992). Krilov et al. (2008) recently demonstrated that exposure to high concentration or prolonged duration of glucagon exposure resulted in GCGR internalization and degradation in lysosomes, while receptor recycling occurs through GTPases Rab4- and Rab11-positive vesicles in a process dependent on actin skeleton, β-arrestin-1, β-arrestin-2 and the carboxyl terminus. In islet cells, receptor expression is upregulated by glucose and agents which reduce cAMP (e.g. somatostatin) (Nishimura et al., 1995) and downregulated by glucocorticoid dexamethasone and agents that increase cAMP (e.g. forkolin, iMBX) (Abrahamsen and Nishimura, 1995). In a study by Burcelin et al. (1998) investigating the metabolic regulators of GCGR expression, he showed that GCGR mRNA

20 increased in any condition where intrahepatic glucose metabolism was active, and decreased when glucose flux was inhibited by any glycolytic inhibitor. GCGR expression is also regulated by thyroid hormone (Morales et al. 1998) and by cold exposure in brown adipose tissue in a tissue-specific manner (Morales et al. 2000). Finally, GCGR has been shown to interact with receptor activity modifying proteins (RAMPs), specifically RAMP2, in transfected fibroblasts (Christopoulos et al., 2002); however, no biological significance of this interaction has been elucidated.

RATIONALE AND HYPOTHESIS OF THESIS

Since we know that most cellular processes are coordinated by specific protein interactions in multi-protein complexes, many studies have focused on characterizing the protein interactomes or “proteomes” of GPCRs to better understand GPCR mechanism of action. The rationale for studying PPI is based on the concept of “guilt by association” whereby if the function of one protein is known, then it’s highly probable that the function of any binding partner is related. To date, there have been several studies on the nature and functions of GBPs and GAPCs which have opened up this new mechanistic paradigm for GPCR function. However, these studies have primarily focused on class- A and C types GPCRs, while considerably less is known about GAPCs of B-class GPCRs. The aforementioned large body of work demonstrates the very large number of cell actions of the glucagon superfamily of receptors. However, remarkably little progress has been reported so far in identifying the intracellular effector proteins that would transduce such a myriad of actions. This has led me to hypothesize that for the glucagon superfamily of receptors to effect such diverse actions, these GPCRs must be coupled to as yet undefined intracellular effector proteins which form putative protein interactome complexes that transduce context-specific downstream signaling pathways leading to specific cell actions. It therefore behooves me, as the underlying rationale of my thesis work, to embark on identifying the novel interactors coupled to the glucagon superfamily of receptors. A major reason for the lack of progress in this area of investigation has been technological limitations of current strategies. To surmount this limitation the development of a novel strategy was required, and that is the membrane-based yeast two-hybrid system (MYTH) (Iyer et al., 2005). Since about 50% of all drug targets are integral membrane proteins, the MYTH system represents a potentially valuable tool for identifying novel therapeutic agents. This work forms the platform from which further work can now be carried out to define how each of these GAPCs would trigger the distinct downstream signaling and specific physiologic and therapeutic

21 cell actions of the glucagon superfamily of hormones. The ensuing insights will be the basis of new therapeutic approaches of GAPC modulation that could confer target cell specificity to hormone drug-GPCR actions (i.e. amplifying islet beta cell insulin secretion and beta cell growth) while reducing untoward side effects emanating from drug actions on other cell types.

OBJECTIVES In my thesis study, I have set out to accomplish three major objectives (Figure 4): 1) to apply the MYTH system to assess B-class secretin-like GPCR PPI and GAPC; 2) to identify novel protein interactors of GLP-1R, GIPR, GLP-2R and GCGR in order to generate a putative interactome (receptome) of the glucagon superfamily of receptors; and 3) to validate some of these novel interactors by yeast prey retransformation and co- purification (co-purification). I have accomplished all three objectives in each of the succeeding three chapters.

Figure 4. Flowchart of experimental aims for MYTH system PPI cDNA-library screen.

CHAPTER 2: ESTABLISHMENT OF MYTH METHOD TO STUDY B-CLASS OF GPCR

2.1 Rationale Despite major advances in proteomic screening methodology, the characterization of membrane-bound protein complexes is still in its infancy. Membrane proteins make up at least one third of all proteins in a given organism. They include receptor tyrosine kinases, G protein– coupled receptors, membrane-bound phosphatases, and transporters, which represent important classes of signaling molecules that perform essential cellular tasks. However, they have proven difficult to study using traditional approaches of protein interaction assays, in part because these protein interactions can be confounded by their hydrophobic nature (Gavin et al., 2002; Iyer et al., 2005). Furthermore, functional analysis of GPCRs and their GAPCs has been plagued by seemingly unsurmountable challenges of low endogenous expression of GPCRs in native cells, poor immunogenicity to raise antibodies, and difficulty in solubilizing these receptors into functionally active forms (Daulat et al., 2008). Here, I have utilized the strategy of a membrane-based yeast two-hybrid system (MYTH) that is superior to previous strategies because it allows us, for the first time, to study protein-protein interaction of full-length GPCRs in situ at the cell membrane.

2.2 Hypothesis The MYTH system can be adapted for B-class GPCR screening in order to identify the novel interacting partners of the glucagon superfamily of receptors.

2.3 Introduction

2.3.1 Molecular Proteomics Screening Tools A number of molecular proteomics screening methods have been developed to very efficiently assess PPIs, with the aim of characterizing entire protein interactomes (or proteomes). This is based on the guiding principle that a protein’s role is based on it’s interaction with other proteins, and the versatility of its function can be derived from identifying its putative interacting partners (Claverie, 2001). Initial biochemical approaches towards investigating PPI, such as co-purification, cross-linking, and copurification by chromatography, involved protocols that were often too harsh to sustain weak and/or transient interactions. To overcome these difficulties, alternative genetic methods had to be developed, one of which was the yeast two- hybrid (YTH) system which is currently the most widely and successfully used proteomic method to study PPI (Fields, 2005). As these assays became more widespread, many were

23 developed into large-scale or high-throughput (HTP) strategies to analyze PPI of the growing number of novel sequence information available, most of which are without assigned function.

2.3.2 Yeast Two-Hybrid Screening The original YTH system is a molecular biology technique developed by Fields and Song (1989) which utilizes the tractability of the eukaryotic transcription factor and yeast, Saccharomyces cerevisiae, the most intensively studied eukaryotic model organisms. The basis of this assay relies upon the activation of a downstream reporter gene(s) by the binding of a transcription factor to an upstream activation sequence (UAS). Classical factor based YTH involves the transcription factor being split into two moieties, the DNA binding domain and the activating domain. The bait protein of interest is fused to the DNA binding domain and the prey potential interacting protein to the activating domain. A physical interaction of any two bait and prey proteins will lead to spontaneous reconstitution of the transcription factor and subsequent transcription of the reporter gene which can be monitored through growth under selective conditions or by colorimetric (β-galactosidase) assay. The bait protein of interest can be screened against either a genomic or complementary DNA (cDNA) prey library derived from an entire organism or specific tissue of interest (Fields, 2005). Various modifications of the YTH system have been described, which include the Son of Sevenless (SOS) recruitment system (Aronheim et al. 1994), Ras-recruitment system (RRS) (Broder et al. 1998), reverse RRS (Hubsman et al. 2001), rUra3-based split-ubiquitin assay (Johnsson and Varshavsky 1994), and a heterotrimeric G protein fusion method (Ehrhard et al. 2000).

2.3.3 Split-Ubiquitin Membrane-based Yeast Two-Hybrid System The split-ubiquitin MYTH is an exciting and novel method of studying PPI recently developed by Dr. Igor Stagljar’s Laboratory at the University of Toronto (Iyer et al., 2005). Unlike the conventional system, this new MYTH system no longer requires the transport of interacting proteins into the nucleus where only subdomains of integral membrane proteins can be assayed since GPCRs targeted to an aqueous nuclear environment may aggregate or misfold (Miller et al., 2005). This strategy is superior to previous strategies because it allows, for the first time, to study PPI of 1) full-length GPCRs (7TM domain, arrangement of intracellular loops and the C-tail, and receptor oligomerization) 2) in situ at the cell membrane. Membrane spanning domains of membrane proteins are of extreme importance in structure-function of those proteins per se and the regulation of their interactions with other membrane and cytosolic proteins. This system centers around ubiquitin, which is a 76-aa cellular marker which serves as tag for cells targeted for degradation. It is recognized by ubiquitin-specific proteases (UBPs) found in

24 the nucleus and cytoplasm of all eukaryotic cells. This YTH system takes advantage of the observation that ubiquitin split into two moieties, an NT ubiquitin (Nub) and a CT ubiquitin (Cub), will spontaneously reconstitute when in close proximity. The Nub is fused to the potential protein interactors (called the “prey”) and the Cub is fused to the protein of interest (called the “bait”), along with an artificial transcription factor (TF) that consists of the bacterial LexA-DNA binding domain and the Herpes simplex VP16 transactivator protein (Figure 5). Both bait and the prey library of proteins are expressed in yeast. Because of their high affinity, the two halves (Cub + NubI) of ubiquitin spontaneously reconstitute and are recognized by the UBPs. Hence, to prevent spontaneous association, an isoleucine (I) to glycine (G) exchange at position 13 of the Nub moiety has been introduced to form NubG (Johnsson and Varshavsky, 1994). Therefore, only upon interaction of the bait and prey proteins will reconstitution of ubiquitin moieties (Cub + NubG) occur, leading to cleavage of the TF by UBP after the C-terminal residue of ubiquitin. The TF is released and travels to the nucleus to activate different reporter genes (HIS3, ADE2, lacZ) which can be monitored by growth on selection plates and by colorimetric assay in the yeast strain Saccharomyces cerevisiae TH4.AP4 3-reporter gene system (Figure 5) (Iyer et al., 2005).

Figure 5. Split-ubiquitin membrane-based yeast two-hybrid system (MYTH). Bait protein of interest is fused to the C-terminal ubiquitin (Cub) and LexA-VP16 transcription factor (TF) to form

the bait construct, while the prey protein is fused to the N-terminal ubiquitin (NubG) to form the prey construct. Bait-prey interaction leads to reconstitution of the ubiquitin and proteolytic cleavage by ubiquitin-specific proteases (UBP), thus releasing the TF which enters the nucleus to activate the reporting genes by binding the LexA operator sites (lexA ops), resulting in HIS3+/ADE2+/lacZ+ (Iyer et al., 2005).

2.3.4 YTH Variant Systems Modified YTH systems have been developed to overcome the limitations of previous technologies or to focus on specific aspects of PPI. cytoYTH parallels the MYTH system by using a split-ubiquitin approach, but focuses on cytosolic proteins of interest that, like transcription factors, have proven difficult to study in the nuclear environment. Here, to ensure only cytosolic PPI occurs, the cytosolic bait is anchored to a resident yeast endoplasmic reticulum integral membrane protein called Ost4p (Mockli et al., 2007). Furthermore, variants of protein fragment complementation including split-TEV and MAPPIT are specialized yeast-based mammalian PPI screening tools. Unlike the MYTH, the tobacco etch virus (TEV) protease is split into two and functionally reconstitutes upon bait-prey interaction leading to cleavage of a recognition sequence that release either a TF to activate reporter gene expression or luciferase which is only active when liberated (Wehr et al., 2006). Finally, mammalian PPI trap (MAPPIT) takes advantage of the Janus kinase/Signal Transducer and Activator of Transcription (JAK/STAT) signaling pathway, where the bait is fused to the ligand-bound JAK and the prey to the STAT3 TF. Bait-prey interaction results in phosphorylation and release of the STAT3 TF to activate the reporter gene (Eyckerman et al., 2001). While these technologies represent promising PPI approaches, few have been evolved into HTP screening methods (Suter et al., 2008b). The major advatages of the YTH method include occurrence in an in vivo normal cellular environment, lack of harsh biochemical lysis or washing step and the capability of sensing weak or transient interactions. Conversely, common limitations include detection of only binary interactions, prevalence of artifactual interations (both false positives and negatives discussed later) and the presence of two artificial fusion tags which may inhibit potential PPI (Auerbach et al., 2003).

2.3.5 Alternative Proteomic Screening Tools Many other biochemical approaches have been developed including affinity precipitation and mass spectroscopy (MS), phage-display system, protein chip technology using tagged gene arrays, protein fragment complementation in mammalian cells, and detection of PPI using fluorescence (FRET) and bioluminescence resonance energy transfer (BRET) approaches (Figeys, 2008; Suter et al., 2008a). However, the genetic YTH method is often preferred over

26 the biochemical assays since positive interactors are easily identified through growth selection, colorimetric or fluorescent phenotype and prey plasmid DNA is readily accessible for sequencing (Suter et al, 2008b). Therefore, of all PPI published in scientific literature, the majority have been reported using the YTH method (Suter et al., 2008b). A well-established mature technology which is comparable to MYTH is affinity purification-mass spectroscropy (AP-MS) which also allows for use of the entire GPCR as the bait for studying PPI. The AP-MS is a biochemical method used to isolate GBPs by binding or forming complexes with affinity-tagged proteins expressed in mammalian cells as baits, thus providing an in vivo normal cellular environment. These GAPC proteins are separated by gel electrophoresis and identified by mass spectroscopy (Gavin et al., 2002; Ho et al., 2002). Since AP-MS captures entire protein complexes, instead of just binary interacting partners, it is capable of detecting interactors that rely on higher order complexes. However, the AP-MS strategy has several potential limitations: 1) the difficulty in distinguishing between specific and nonspecific interactors; 2) the unreliable quantification of changes in the abundance of protein complexes or their components; 3) the precise physical associations of the proteins within the complex are not always reliable; 4) it often is difficult to identify low-abundance interacting proteins, and weak or transient interacting proteins are often lost during the purification steps; and 5) overexpression of bait protein can lead to artifact or false-positive interactions (Auerbach et al., 2003; Stagljar, 2003). Nonetheless, an advantage of AP-MS is the presence of a fused artificial tag with only one binding partner which lessens the chance of interference with PPI. Currently, the most popular AP-MS method is the tandem affinity protein purification (TAP) scheme, which is a two-step affinity chromatography purification of complexes formed in intact cells. This strategy relies on TAP tags consisting of IgG binding domains at a tobacco etch virus (TEV) protease cleavage site and at a calmodulin binding domain site (Puig et al., 2001; Rigaut et al., 1999). This system has been successfully applied to screen the entire yeast proteome, in which all open reading frames (ORF) were tagged (Gavin et al., 2002, 2006; Krogan et al., 2006), as well as to assess PPIs in signaling pathways in Drosophila melanogaster (Veraksa et al., 2005) and in human cells (Bouwmeester et al., 2004; Brajenovic et al., 2004). However, due to low protein yields, application of TAP to study integral membrane proteins, particularly GPCRs, has proven challenging. However, a recent study by Daulat et al. (2007) seems to have surmounted this limitation whereby they were able to purify GAPCs in native conditions, and remarkably, in quantities suitable for MS analysis. The novelty here is a clever TAP configuration adapted to analyze PPI in a mammalian cell line, Human Embryonic Kidney (HEK) 293 cells stably transfected with TAP tagged MT1 and MT2 melatonin receptors.

2.4 Method and Materials

2.4.1 Reagents The yeast strain used for the generation of bait constructs and immunofluoresence imaging was Saccharomyces cerevisiae TH4.AP4 3-reporter gene system. All plasmid amplifications were performed using the in E.coli strain XL-10 Gold prepared using the Inoue method as described in Sambrook and Russell’s Molecular Cloning: A Laboratory Manual (Vol.1 pt. 112-1.115). Human Embroyonic Kidney 293T cells (HEK293T) were used for transient transfection in western blot analysis and cAMP assay experiments.

2.4.2 Cell Culture

HEK293T cells were grown at 37°C in 5% CO2 in DMEM supplemented with 10% fetal bovine serum (Invitrogen) and penicillin-streptomycin (100 units/ml, 100 µg/ml) (Invitrogen).

2.4.3 Polymerase Chain Reaction (PCR) and Gel Extraction PCR reaction mix was generated: 0.05-0.1 μg islet cDNA template, 0.125 μl forward + reverse primer (10μM), 0.5 μl Pfu Turbo DNA polymerase, 2.5 μl 10x Pfu buffer,1 μl DMSO, 0.25 μl dNTP, 19.5 μl RNAse free water. Using the Dual Block DNA Engine Thermal Cycler (MJ Research, Inc., MA, USA), reaction mix sample was heated initially 95°C for 3 min. Sample was then incubated to 95°C for 0.45 s, to 56 – 72°C for 45 s, to 72°C for 1 min 45 s, and then cycled 30 times. Finally, sample was incubated at 72°C for 10 min before being stored at 4°C. All 25 μl of PCR sample were run on a 0.8% agarose pure gel with 0.75 μl ethidium bromide. Appropriate sized bands were excised from the gel and purified using the QIAquick Gel Extraction Kit (Qiagen). Gel extraction was carried out according to the protocol. Final product was eluted in 15 – 30 μl of TE buffer at pH7.5.

2.4.4 Yeast Bait Construction This method was performed as previously described (Iyer et al., 2003). cDNA encoding each receptor was amplified by PCR using Pfu Turbo DNA polymerase (Stratagene, La Jolla, CA) and 60-nucelotide oligonucleoties flanked with 5’ and 3’ ends which were homologous to the appropriate yeast-expression vector insertion site (Dualsystems Biotech, Zurich) which contains a centromeric locus (CEN)/autonomously replicating sequence (ARS) low copy origin of replication (limits one or two copies of plasmid per cells) and driven by a weak Cytochrome-C oxidase (CYC1) promoter, which provides low-levels of heterologous protein expression. This is followed by a yeast Ste2 leader sequence to enhance subcellular targeting to the yeast plasma membrane, a multicloning site (MCS), a CT ubiquitin moiety fused in frame with a LexA-VP16

28 transcription factor tag, CYC terminator, as well as the LEU2 gene for selection in yeast and KanR gene for selection in bacteria (Figure 6). GLP-1R was cloned into the pCCW-ste vector, GLP-2R and GIPR into the pBT3-ste vector. The GCGR was transformed into the pTMBVMFα vector which contained a stronger TEF promoter. Saccharomyces cerevisiae THY.AP4 3- reporter system (HIS3, ADE2, lacZ) yeast cells from a 50-ml overnight culture grown to 0.6 - 0.8

OD546 were harvested at 4000 rpm for 5 min at 4°C, washed in 30 ml of sterile double distilled

H2O, and resuspended in 1 ml of double distilled H2O. An aliquot of 50 μl of competent yeast cells was treated with transformation or TRAFO mixture (240 μl of 50% (w/v) polyethylene glycol (PEG) 4000, 36 μl of 1 M LiOAc, 50μl of 2.0 mg/ml single-stranded DNA, 50 μl of distilled

H20) and added to 1 μg of digested vector and 1 ug of amplified PCR product. The transformation mixture was incubated for 30 min at 30°C and 45 min at 42°C, then pelleted, and resuspended in 100 μl of 0.9% NaCl. At most, 45 μl was plated on synthetic dropout (SD) agar plates devoid of Leu (TF-Cub-Baits). The SD medium was composed of 0.67% yeast nitrogen base without amino acids (Difco), dropout supplement powder (Clontech), 2% glucose, 0.01% adenine hemisulfate at pH 5.6 and 2% select agar for plates. Plasmid DNA was isolated from yeast using the GenElute plasmid miniprep kit (Sigma) and amplified in XL-10 Gold E.coli competent cells. Overnight bacterial cultures were miniprepped and samples were verified by sequencing and protein expression was verified by immunofluorescence and western blotting analysis.

2.4.5 Immunofluorescence

Yeast cells were grown to midlog phase to an OD546 of 0.4 in SD-Leu and fixed for 30 min in 37% formaldehyde at room temperature (RT) for 1 h with rotation. Sample was then washed twice with 1 ml H2O and twice with 1 ml SK solution (1.8mM K2HP04 at pH7.5, 1.7mM KH2PO4 at pH7.5, 3.6mM sorbitol, H2O) and then resuspended in 100-200 μl SK solution. Cells were lysed with zymolyase solution (0.5 mg/mL zymolyase, 1 ul/mL B-mercaptoethanol) and checked using 0.1% SDS. Slides were prepared by adding 10 μl poly-L-lysine to each well for 2 min and then washing 3 times with 20 μl sterile water. Spheroplasted cells were washed twice with 500 μl SK solutions and resuspended in 40 - 200 μl SK solution. 20 μl of cells were added to each poly-L-lysine coated well and incubated for 20 min at RT. Slides were then incubated in -20°C methanol for 6 min and -20°C acetone for 30 min. Blocking was performed with 3% BSA in 1xPBS for 20 min at RT in humidity chamber, followed by 20 μl of rabbit anti-VP16 primary antibody (1/200 dilution) mixed in 1% BSA in 1xPBS for 1 h at RT in humidity chamber. Wells were washed 5 times with 20 μl 1xPBS with 1% BSA and then incubated in 20 μl of goat anti- rabbit FITC secondary antibody (1/500 dilution) mixed in 1% BSA in 1xPBS for 1 h at RT in humidity chamber. Wells were washed 5 times with 20 μl 1xPBS with 1% BSA and then

29 stained for 3 min with 1 ug/ml 4',6-diamidino-2-phenylindole (DAPI). Coverslips were applied and sealed with nail polish and slides were stored at -20°C. Slides were imaged using an inverted fluorescence microscope.

2.4.6 NubG/NubI Test Yeast transformation was performed as previously described for bait construction. THY.AP4 yeast expressing the receptor of interest were cotransformed with 1 μg each of non-interacting Ost1 (resident endoplasmic reticulum protein) and Fur4 (resident plasma membrane protein) NubI (endogenous Nub form) fused positive control plasmids and NubG fused negative control plasmids. Transformed yeast was plated on SD deficient of leucine (for bait) and tryptophan (for prey). 3 days later yeast was replated on interaction selection plates of SD deficient of leucine, tryptophan, adenine and histidine, supplemented with 0, 5, 10, 25, 50 and 100mM concentrations of 3-amino-1,2,4,-triazole (Sigma-Aldrich), a competitive inhibitor of HIS3 gene product, to determine optimal stringency conditions.

2.4.7 Receptor Cloning Each receptor cDNA was subcloned out of the yeast expression vector into a V5-his tagged mammalian expression vector using the Invitrogen pcDNA3.1 directional cloning kit. Cloning was performed according to kit instructions. Briefly, the receptor cDNA was amplified by PCR from the yeast receptor plasmid using oligonucleotides flanked with specific directional sites for the TOPO cloning. The PCR product and TOPO vector was combined in a 1:1 molar ratio into a reaction mix (0.5-4 μl fresh PCR product, 1 μl salt solution, 1 μl TOPO vector, up to 5 μl double distilled H2O) and incubated at 20°C for 5 min. 2 μl of the reaction mix was mixed into 1 vial of One Shot TOP10 competent cells and incubated for 5-30 min on ice and then heat shocked at 42°C for 30 sec. 250 μl of S.O.C. medium (Invitrogen) was added and the culture was incubated at 37°C with shaking (200RPM) for 1 h then plated on LB +Ampicillin (100ug/μl) plates. Plates were incubated overnight for 16-18 h at 37°C. Single colonies were picked into 5 mL LB+Ampicilin (100ug/ul) liquid cultures and incubated overnight for 16-18 h at 37°C. Each culture was miniprepped using the GenElute plasmid miniprep kit (Sigma) and eluted in 50 μl of double distilled H2O and verified by enzymatic digestion and by sequencing.

2.4.8 Intracellular cAMP Measurement HEK293 cells plated in 12-well culture dishes were preincubated in 0.5 ml OPTI-MEM for 30 min. For each well, 0.6 ug of the V5-His-tagged receptor construct and 1.5 ug LipofectAMINE 2000 (Invitrogen) were each added to 150 ul OPTI-MEM and incubated at RT for 5 min, before being added together and incubated for 30 min. Transfection mix was added drop-wise to each well after preincubation media was removed and fresh 0.5 ml OPTI-MEM was added.

Transfected cells were incubated for 4-6 h at 37°C in 5% CO2 and then transfection mix was removed and replaced with 1 ml DMEM supplemented with 10% fetal bovine serum (Invitrogen) and penicillin-streptomycin (100 units/ml, 100 µg/ml) (Invitrogen). Transfection efficiency in HEK293T cells was about 80%. 36-48 h after transfection, cells were incubated in 1 ml Buffer 1 (50mL DMEM, 0.25g BSA) for 30 min and then stimulated in Buffer 2 (50 ml DMEM, 0.25g BSA, 1 uM isobutylmethylxanthine (IBMX) and 10-12 M – 10-6 M concentrations of peptide agonist). Cells were then washed with 1 ml ice-cold phosphate-buffered saline and lysed/extracted with ice-cold 80% ethanol solution. Cells were pelleted at 2500 rpm for 5 min and then 100ul of supernatant was lyophilized using CentriVap system (Labcono, Missouri) and used for intracellular cAMP measurement using a cAMP radioimmunoassay (RIA) kit (Biomedical Technologies Inc.).

2.4.9 Statistics Paired t-tests were performed to determine statistical significance between intracellular cAMP measurements. p values less than 0.05 were considered statistically significant.

2.5 Results

2.5.1 Generating Receptor “Bait” Constructs To generate receptor constructs which were compatible for MYTH screening, each receptor was C-terminally fused with the CT (Cub) domain of yeast ubiquitin and LexA-VP16 transcription factor tag. Human Glucagon, human GLP-1, human GLP-2 and rat GIP receptor cDNA was amplified by PCR with primers flanked with 5’ and 3’ ends homologous to the yeast expression vector insertion site. The amplified cDNA was the correct size, as verified on agarose gel, and PCR product was extracted, purified and cloned into the yeast expression vector by gap repair and in vivo recombination via yeast transformation (Figure 6). The receptor “bait” construct was shown to be the correct size following enzymatic digestion of the vector Pst1 and Hind3 restriction sites and further verified by DNA sequencing using forward and reverse primers designed from internal vector sequences confirming receptor nucleotide identity. Therefore, each receptor was successfully cloned into the following yeast-expression vectors: GLP-1R into the pCCw-ste vector, GLP-2R and GIPR into the pBT3-ste vector and GCGR into the pTMBVα vector.

Figure 6. Generation of bait construct. Receptor cDNA was amplified by PCR from islet cDNA with oligonucleotides flanked with 3’ and 5’ ends homologous to vector cloning site. The PCR product was subcloned into each respective yeast expression vectors by gap repair in the THY.AP4 3-repoorter gene system yeast strain (Iyer et al., 2005).

2.5.2 Cub-TF Fused Receptors are Localized to Yeast Plasma Membrane To ensure that the Cub-TF fused receptors were being efficiently transported to and expressed at the yeast plasma membrane, immunofluoresence was performed. FITC labeled antibody against the VP16 portion of the fused transcription factor was used. As indicated in green, immunofluoresence microscopy show localized green FITC to the yeast plasma membrane indicating that addition of the Cub-TF tag does not prevent the receptor from being expressed and correctly localized to the yeast plasma membrane (Figure 7). Nuclear staining is in blue using DAPI.

Figure 7. Receptor immunolocalization to yeast membrane. Immunofluorescent visualization of subcellular distribution of Cub-TF tagged receptors (GLP-1R, GIPR, GLP-2R, GCGR) expressed in THY.AP4 yeast strain. Fixed and acetone-treated spheroplasts of yeast were processed for fluorescence microscopy using transporter- specific primary and FITC-conjugated secondary antibodies (green) and DAPI stain (blue) of the nuclei.

2.5.3 Cub-TF Fused Receptors are Compatible MYTH System Protein interaction capability within the MYTH system and self-activation of the Cub-TF fused bait constructs were tested with subsequent yeast cotransformation using positive and negative control prey vectors. NubI is the endogenous form of ubiquitin which spontaneously reconstitutes with the Cub regardless of a true protein-protein interaction. Therefore, proteins fused to NubI are positive control prey plasmids and NubG are negative control prey plasmids.

A non-interacting resident endoplasmic reticulum protein (Ost1) and non-interacting resident plasma membrane protein (Fur4) were chosen to ensure interaction with control proteins as the bait protein should be transported through the secretory pathway and expressed at the membrane (Figure 8A-B). Plating of cotransformed bait and prey control plasmids on selection media showed yeast growth with NubI fused proteins and not with NubG fused proteins (Figure 8). While the GLP-2R Cub-TF cotransformation with NubI-Fur4 resulted in no yeast growth, cotransformation with NubI-Fur4 did result in growth. This still qualifies as a positive NubG/NubI test since while the receptor as not interacting in the secretory pathway, it still made it to the membrane. Therefore, each Cub-TF fused receptor plasmid passed the NubG/NubI test for protein interaction capability indicating that they are properly inserted into the membrane and that each receptor is not self-activating. The amount of 3-aminotriazole (3'AT), a competitive inhibitor of the His3 reporter gene, to give the optimal stringency conditions for library screening also was determined by the concentration which could abolish growth with the negative NubG control prey but not with the known positive NubI control prey. The optimal concentration of 3’AT for each receptor was determined to be 10 mM (Figure 8).

2.5.4 Cloned Receptors can be Expressed in Mammalian Cells To ensure that the cloned receptors could be expressed at the protein level, the GLP-1R, GIPR and GLP-2R receptors were subcloned out of the yeast-expression vector and into a pcDNA3.1 mammalian expression vector containing a V5-6xHistidine CT tag. The V5-His tagged receptor plasmids were transiently transfected into HEK293T cells and expression was confirmed by western blot analysis of the cell lysate using an anti-V5 antibody (Figure 9). The presence of the higher molecular weight band may be due to misfolding, aggregation or glycylation of the receptor.

2.5.5 Cloned Receptors are Functional in Mammalian Cells Since class B1 GPCRs are known to activate AC, receptor function can be validated through measurement of intracellular cAMP following receptor activation. HEK293T cells were transiently transfected with each V5-His tagged receptor and stimulated with their respective peptide hormone. Stimulation with a series of different peptide hormone concentrations (10- 12M to 10-8M) showed a dose-dependent cAMP response from both GLP-1R and GLP-2R receptors (p<0.05); however GIPR dose responses were not statistically significant (Figure 9). No significant cAMP response was observed following stimulation of untransfected HEK cells controls. Conversely, a significant cAMP response was observed following stimulation of a GLP-1R-V5-his stably expressing Chinese Hamster Ovarian (CHO) cell line which was used as

33 a positive control for each experiment. Therefore, GLP-1R and GLP-2R can increase cAMP levels in vitro following stimulation by their endogenous peptide hormones, thus indicating that these receptors are functional.

Figure 8. Receptors pass NubG/NubI Test for interaction capability and self-activation. A) NubG fused proteins will only reconstitute with the Cub induce UBP-mediated cleavage and release of TF in the presence of a bait-prey interaction. Therefore non-interacting Ost1 and Fur4 proteins fused to NubG should not result in growth on selection media. B) NubI fused proteins will spontaneously reconstitute with the Cub and induce UBP-mediated cleavage and release of TF in the regardless of any bait-prey interaction. Therefore non-interacting Ost1 and Fur4 proteins fused to NubI should result in growth on selection media. C) Negative control NubG and positive control NubI prey plasmids were transformed into THY.AP4 yeast expressing the GLP-1R-Cub-TF bait protein and then plated on –WLAH growth selection media. The optimal amount of 3’AT concentration was determined by that which could abolish growth with the negative NubG control prey but not with the known positive NubI control prey. –WL plates were used as positive control transformation plates where the presence of a bait (L) and prey (W) plasmid would permit growth on the –WL selection media.

Figure 9. Receptor is expressed at protein level and activation increases intracellular cyclic AMP accumulation in a dose-dependent manner. Human embryonic kidney (HEK) 293T cells were transiently transfected with each V5-His-tagged receptor construct (GLP-1R, GIPR, GLP-2R) and immunoblotted to verify protein expression. Following stimulation of transfected HEK293T cells with 10-12M – 10-8M concentrations of each peptide agonist, intracellular cAMP accumulation was measured using a cAMP RIA kit.

2.6 Summary of Findings Here I have established a system to screen class-B GPCRs PPIs using the MYTH system. The GCGR, GLP-1R, GIPR and GLP-2R have all been fused to the Cub-TF interaction tag via gap repair and in vivo recombination in the THY.AP4 3-reporter gene yeast. Each of the Cub-TF fused receptor plasmids has been sequenced verified and tested for receptor membrane localization and compatibility in the MYTH system. GLP-1R, GIPR and GLP-2R were tested for

36 protein expression and cAMP accumulation following activation within HEK293T cells. I show here that each receptor is properly transported, expressed and interacting at the yeast membrane within the MYTH system and that GLP-1R, GIPR and GLP-2R receptor can be expressed and activated within a mammalian host. Therefore, the MYTH system can be adapted to study B-class GPCRs and these 4 glucagon subclass receptors can be used for large-scale library screening.

2.7 Discussion

2.7.1 MYTH Receptor Compatibility Within the MYTH system, compatibility issues with mammalian receptors are quite common, where at least 50% do not work within the system. Initially with each of the 4 receptors, there was difficultly either with yeast transformation to generate the bait construct or the construct would not pass the NubG/NubI test for receptor compatibility. Therefore, different parameters must be adjusted to overcome compatibility issues, such as adjusting primer sequences or cloning into different yeast-expression vectors. Three different vectors were used for our receptors: pCCw-ste (GLP-1R) and pBT3-ste (GIPR, GLP-2R) are different generations of the same vector, driven by the same promoter. Sometimes using a stronger or weaker promoter increases transformation efficiency or resolves the self-activation tendency. Therefore, pTMBVMVα, which has a stronger TEF promoter, was used instead for GCGR, where we were having self-activation problems. All three vectors contain the same C-terminally tagged Cub-TF fused and selection markers. In the case of the GIPR, the human receptor proved to be incompatible and thus the rat receptor, which passed all validation tests, was chosen instead. Since the rat receptor shares >80% homology with the human receptor (Yamada et al. 1995), the receptor interactomes should be closely related as well. Possible reason why some genes do not pass the NubG/NubI test are 1) bait receptor may endogenously expresses or recruits ubiquitin which activates UBP-mediated release of TF on its own; and 2) mislocalization and misfolding due to high expression (Miller et al., 2005).

2.7.2 GCGR Subcloning It is important to note that the GCGR was not successfully subcloned into the mammalian expression vector and thus was not validated within the mammalian HEK293T cell line. However the receptor plasmid was sequence verified and shown to be in frame based on translation of the Cub-TF tag. It also passed both the yeast validation test, including membrane immunolocalization and the NubG/NubI compatibility test. While it is important to confirm

37 expression and function within a mammalian setting, I believe it was still appropriate to continue with MYTH screening of the GCGR.

2.7.3 IF Resolution Using immunofluoresence, we showed localized FITC staining at the yeast membrane, suggesting that each receptor was being efficiently transported and inserted into the plasma membrane. While immunofluoresence alone may not be sufficient to conclude plasma membrane localization due to inadequate resolution of the immunofluoresence microscope, taken together with sequence verification and the other 3 validation assays, there is confidence that the receptor is functional on the plasma membrane and capable of interacting properly within the MYTH system. A higher resolution imaging method of showing plasma membrane staining would be to use confocal microscopy where serial sectioning and 3D reconstruction of the entire stack of cell images can be generated to see if the receptor signal is only present in the cell periphery. Here we could costain for a plasma membrane marker like cadherin or sodium-potassium-ATPase to show colocalization. Furthermore, simple fractionation of the transformed yeast cells and western blotting analysis of each fraction could be performed to ensure the protein expression is localized in the plasma membrane fraction.

CHAPTER 3: IDENTIFICATION OF NOVEL INTERACTORS OF RECEPTORS

3.1 Rationale Despite certain limitations, the MYTH system represents one the most powerful tools today for studying the PPIs which compose multi-protein complexes that underly most cellular processes. Generation of the Cub-TF fused receptors, which were verified for function and expression in yeast and GLP-1R and GLP-2R in human cells, have prepared the way for identifying the novel protein binding partners coupled to the glucagon superfamily of receptors using the modified MYTH system. Since over 90% of GPCRs are expressed in the brain (Vassilatis et al., 2008), a human fetal brain NubG-X cDNA prey library was chosen to screen in order to identify biologically revelent protein interactors involved in glucagon receptor superfamily signaling complexes. As GLP-1R has been shown to be expressed in the kidney, a human kidney NubG- X cDNA prey library was also chosen to screen this receptor (Wei and Mojsov, 1995; Bullock et al., 1996).

3.2 Hypothesis Both known and novel GPCR binding proteins which compose GAPCs will be identified from MYTH screens of Cub-TF fused glucagon-related receptors.

3.3 Introduction

3.3.1 Glucagon Receptor Superfamily – Known Interactors Only a few studies have shown potential protein binding partners of the glucagon superfamily of receptors. Both GLP-1R and -2R have been shown to localize in lipid rafts (including a direct interaction of GLP-1R and caveolin-1) which was proven to be necessary for GLP-1R subcellular localization, trafficking and signaling activity (Syme et al., 2006). Additionally, Sonoda et al. (2008) later demonstrated that the physical association between the GLP-1R and the scaffolding protein β-arrestin-1, a protein involved in GPCR agonist-induced desensitization and endocytosis, is required to stimulate cAMP production and insulin secretion in INS-1 β-cell line. As well, both G-protein-coupled receptor kinase 2 (GRK2) and β-arrestin-1 may be involved in GIP-induced cAMP production and insulin secretion (Tseng and Zhang, 2000). GCGR has been shown to interact with receptor activity modifying proteins (RAMPs), specifically RAMP2, in transfected fibroblasts (Christopoulos et al., 2002). Finally, Mahon and Shimada (2005) demonstrated calcium-dependent calmodulin interaction with the cytoplasmic tails of subset of class-B GPCRs, including GLP-1R and GLP-2R. Nonetheless, what has been reported so far of the glucagon receptor superfamily interactome is not sufficient to explain most

39 of the known cellular actions and therefore strongly indicates the presence of undiscovered protein binding partners for this family of GPCRs.

3.3.2 Limitations of MYTH System

3.3.2.1 Lack of Receptor Activation One major limitation of the MYTH assay is that the receptor is not activated by the endogenous ligand, and as such does not allow for recruitment of protein complexes that would have been induced by agonist activation. While chemical non-peptide agonists could be incorporated into the system to activate the receptor during screens, peptide agonists cannot be used because they cannot penetrate through the yeast cell wall (Nekhotiaeva et al., 2004). The precise and comprehensive mechanism(s) for ligand-activated GPCRs remains to be fully elucidated and requires much further study with perhaps additional innovative strategies. The working model is that ligand agonist binding to a binding pocket within an extracellular domain of the receptor could induce a profound change in the overall receptor conformation, and in particular putative cytoplasmic domains of the receptor to effectively couple and activate intracellular effector proteins, including G-proteins, which then trigger specific cell signals (Rosenbaum et al., 2009). The YTH assay may not completely mimic this physiological process.

3.3.2.2 False Negatives Artifacts within the prey interactor datasets are quite common, including some bona fide interactors which are not picked up by the screen, so-called “false negatives.” These may arise from a number of possibilities: 1) failure of subcellular trafficking of these interacting proteins to the receptor; 2) disruption in the sequence of protein trafficking, protein modification (i.e. phosphorylation), their sequential assembly and disassembly, that collectively lead to the eventual functional multimeric receptor complex; 3) lack of required post-translational modification in the yeast host organism; 4) improper folding of the Nub fusion prey protein; or 5) interference of key binding domains of the receptor or interactor by fused ubiquitin tags (Fields, 2005; Miller et al., 2005). As well, partial cDNA clones which make up the cDNA prey libraries may also lack all the domains necessary to interact with the bait receptor as they normally would at full-length. In addition to the lack of receptor activation, this may in part explain why well-known interaction partners of GPCRs such as heterotrimeric G proteins are difficult to identify using this proteomics technique. Furthermore, these proteins may be underrepresented or even absent from the cDNA library used for YTH screening.

3.4 Method and Materials

3.4.1 Reagents The yeast strain used for MYTH screening was Saccharomyces cerevisiae TH4.AP4 3-reporter gene system. The human fetal brain NubG-X cDNA library (Dualsystems Biotech, Zurich) was generated from total human tissue-specific RNA and the human kidney NubG-X cDNA library (Dualsystems Biotech, Zurich) was generated from total human tissue-specific poly A+ RNA. The vector used, pPR3-N, carries a 2 μm origin of replication for high copy propagation, and driven by the weak CYC1 promoter, the mutated N-terminal (NubG) domain of yeast ubiquitin fused in frame with a hemagglutinin (HA) epitope tags, followed by a multicloning site (MCS), the CYC terminator, and the TRP1 gene for selection in yeast and AmpR gene for selection in bacteria. These distinct selection markers also allow for reisolation of prey plasmids after screening with respect to the bait plasmids, which have LEU2 and KanR marker. The human fetal brain NubG-X library contains about 1.8 x 107 independent clones, ranging in sizes 0.6 – 2.0 kb with 90% of vectors containing cDNA inserts and 100% of those inserts > 250 bp. The human kidney NubG-X cDNA library contains about 2.6 x 106 independent clones, ranging in sizes 0.6 – 0.8 kb with 100% of vectors containing cDNA inserts and 100% of those inserts > 250 bp. All plasmid amplifications were performed using the in E.coli strain XL-10 Gold prepared using the Inoue method as described in Sambrook and Russell’s Molecular Cloning: A Laboratory Manual (Vol.1 pt. 112-1.115).

3.4.2 cDNA Synthesis and RT-PCR Human fetal brain cDNA was generated from 14, 19 and 20 wk old RNA using the M-MLV Reverse Trascriptase Kit from Invitrogen. Briefly, a reaction mix of 1 μg of RNA, 1 μl dNTP and 1 μl oligo(dT) was constituted and brought to a total volume of 13 μl with sterile double distilled water. The mixture was heated to 65°C for 5 min and quickly chilled on ice. After brief centrifugation, 4 μl 5 x First-Stand (FS) Buffer and 2 μl 0.1M DTT was mixed in and incubated at 37°C for 2 min. Finally, 1 μl of Moloney Murine Leukemia Virus Reverse Transcriptase (M- MLV RT) was added and incubated at 37°C for 50 min and then 70°C for 15 min to inactivate the reaction. The cDNA was then used as a template for amplification in PCR using oligonucleotides generated from each receptor sequence. Oligonucleotides were verified using pancreatic islet cDNA template controls. PCR was carried out according to the method previous described in section 2.4.3.

3.4.3 Large-Scale Library Screen THY.AP4 yeast expressing the receptor of interest from a 50-ml overnight culture grown in a

200-ml culture to 0.6 - 0.8 OD546 was harvested at 700 g for 5 min at 4°C, washed in 30 ml of ice-cold sterile H2O, and resuspended in 12 x 1 ml LiOAc/TE master mix (1.1ml 1 M LiOAc, 1.1 ml 10 x TE at pH7.5, 7.8 ml sterile water) in each of twelve 1.5 ml tubes and centrifuged at 700 g for 5 min. Pellet was resuspended in 600 μl of LiOAc/TE master mix and combined with 7 ug library plasmid, 100 μl single stranded carrier DNA and 2.5 ml PEG/LiOAc mix (1.5 ml 1M LiOAc, 10 x TE at pH7.5, 12 ml of 50% PEG4000) in each of four 50 ml tubes and vortexed thoroughly for 1 min. The mixture was incubated for 45 min at 30°C, after which 53.3 μl of DMSO was added to each tube and inverted to mix. Following 20 min incubation at 42°C, cell suspensions were pelleted at 700 g for 5 min, and pooled in 12 ml of 2 xYPAD to recover at 30°C for 90 min. Cells were then pelleted at 700 g for 5 min, resuspended in 4.8 ml 0.9% NaCl and streaked 300 μl each onto SD-WLAH selection 150 mm plates. Remaining resuspended cells were used to prepare 100 mm SD-WL control plates of 1:100, 1:1000 and 1:10 000 dilutions in 0.9% NaCl. Plates were left to grow for 3-4 days at 30°C and then colonies were picked manually or with QArray Colony Picker System (Genetix, UK) and replated on SD-WLAH + 80μg/ml bromo-chloro-indolyl-galactopyranoside (X-gal) plates which were left to grow for 3-4 days at 30°C. All picking was done in a 96-well array format. Number of interactors screened = the number of colonies on SD-WL control plate x dilution factor x 10 x volume NaCl resuspended. The target number of interactors per screen is greater than 2.0 x 106. A pilot screen was run prior to large scale screen using a library of empty vectors and plated at 0, 5, 10, 25, 50 and 100mM concentrations of 3-aminotriazole (competitive inhibitor of HIS3 gene product) to determine optimal stringency conditions that would limit background.

3.4.4 Prey Isolation Yeast colonies that were positive on the X-gal plates (showed blue coloration) were inoculated manually into 5 ml SD-L liquid cultures and grown for 18-24 h at 30°C with shaking. Yeast cultures were harvested at 700 g for 5 min at 4°C, and plasmid was isolated using the GenElute plasmid miniprep kit (Sigma) and eluted in 15 ul of double distilled sterile water. 5 μl of miniprepped plasmid was then mixed with 50 ul XL-10 Gold E.coli competent cells and incubated on ice for 30 min. Following a 45 s heatshock at 42°C, 100 ul of cold LB was added to transformation mix and left to recover at 37°C for 2 h. Transformed bacteria was pelleted at 700 g for 15 sec, resuspended in 40 ul LB and plated on LB + ampicillin (100 ug/ul) agar plates and incubated for 16-18 h at 37°C. Bacterial colonies were inoculated into 5 ml LB+ ampicillin (100 ug/ul) liquid cultures and incubated for 16-18 h at 37°C. Overnight bacterial cultures were harvested at 700 g for 5 min at 4°C, and plasmid was isolated using the GenElute plasmid

42 miniprep kit (Sigma) and eluted in 50 ul of double distilled sterile water. Miniprepped samples were sent for sequencing (Quintarbio, CA; BioBasic, Richmond Hill, ON) and identified through NCBI BLAST anaylsis.

3.4.5 BLAST Analysis Nucleotide sequencing results were input into the NCBI Nucleotide BLAST database < http://blast.ncbi.nlm.nih.gov/Blast.cgi> to identify each protein interactor harvested in each of the 12 large-scale library screens. The accession number, gene name, transcript name and nucleotide match percentage along with size (basepair, kDa) and functional category for each interactor were recorded in data tables. Reading frame was also verified by making sure that translated protein included NubG tag. The Human Protein Reference Database (HPRD) was used to assign function to each prey interactor in summary tables and categorize each screen dataset by functional role.

3.5 Results

3.5.1 RT-PCR: GLP-1R is Expressed in Human Fetal Brain cDNA Since the human fetal brain cDNA prey library was chosen to screen our receptors, RT-PCR was performed to test for gene expression of GLP-1R, GLP-2R, GIPR and GCGR. Human fetal brain cDNA was generated from 14, 19 and 20 wk old human fetal brain RNA using MLV Reverse Trascriptase Kit from Invitrogen. Using oligonucleotides designed from eacn receptor’s nucleotide sequences, PCR was performed using the cDNA template. GLP-1R was shown to be expressed in 20 wk old human fetal brain and at low levels in 14 and 19 wk. However, GLP- 2R, GIPR and GCGR were not expressed at any brain age (Figure 10). GLP-1R, GIPR and GCGR primers were tested against human pancreatic islets cDNA as a positive control and as a negative control for GLP-2R (Figure 10).

Figure 10. GLP-1R gene expression shown in human fetal brain cDNA. Human fetal brain cDNA was generated from 14, 18 and 20 wk old human fetal brain RNA samples by RT- PCR and used as a DNA template to test for gene expression of GLP-1R, GIPR, GLP-2R and GCGR. Human islet cDNA was used as a positive control DNA template for GLP-1R, GIPR and GCGR, and as a negative control for GLP-2R oligonucleotide primers.

3.5.2 GLP-1R Large-Scale Library Screen The human fetal brain NubG-X cDNA library was successfully screened 3 times with GLP-1R- Cub-TF (Table 5). The average number of interactors screened was 1.81 x 106 clones and average library coverage was about 10.1%. Of the 51 prey plasmids sent for sequencing, BLAST analysis revealed 22 unique interactors for the GLP-1R.

GLP-1R Screen Library Coverage

Library Human fetal brain NubG-X

Complexity 1.8 x 107 independent clones

# times screened 3

# clones screened 1.81 x 106 (avg)

% library coverage 10.1% (avg)

# sequenced 51 samples

# clones identified 22 unique clones

Table 5. Summary of GLP-1R-Cub-TF screens of human fetal brain NubG-X cDNA library.

The human kidney NubG-x cDNA library was also successfully screened 1 time with GLP-1R- Cub-TF (Table 6). The average number of interactors screened was 1.78 x 106 clones and average library coverage was about 68.4%. Of the 28 prey plasmids sent for sequencing, BLAST analysis revealed 14 unique interactors for the GLP-1R (Table 7). A breakdown of the 37 total interactors identified from both cDNA libraries showed about 24% related to metabolism (energy, protein, nucleic acid) and 16% each related to cell signaling and transport (Figure 11).

GLP-1R Screen Library Coverage

Library Human kidney NubG-X

Complexity 2.6 x 106 independent clones

# times screened 1

# clones screened 1.78 x 106 (avg)

% library coverage 68.4% (avg)

# sequenced 28 samples

# clones identified 15 unique clones

Table 6. Summary of GLP-1R-Cub-TF screens of human kidney NubG-X cDNA library.

Accession # Gene Human Protein Function

NM_003224.2 ARFRP1 ADP-ribosylation factor related protein 1 Cell Signaling NM_014944.3 CLSTN1 calsyntenin 1 Cell Signaling NM_030760.3 EDG8 endothelial differentiation, sphingolipid GPCR, 8 Cell Signaling NM_194301.2 GARNL1 GTPase activating Rap/RanGAP domain-like 1 Cell Signaling NM_005764.3 PDZK1IP1 PDZK1 interacting protein 1 Cell Signaling NM_015894.2 STMN3 stathmin-like 3 (STMN3) Cell Signaling NM_016564.3 CEND1 cell cycle exit and neuronal differentiation 1 Cell growth/Maintenance NM_181746.2 LASS2 LAG1 homolog, ceramide synthase 2 Cell growth/Maintenance NM_021019.3 MYL6 myosin, light chain 6, alkali, smooth muscle and non-muscle Cell growth/Maintenance NM_001040058.1 SPP1 secreted phosphoprotein 1 Cell Growth/Maintenance NM_021109.2 TMSB4X thymosin, beta 4, X-linked Cell growth/Maintenance NM_014399.3 TSPAN13 tetraspanin 13 Cell growth/Maintenance NM_001025205.1 AP2M1 adaptor-related protein complex 2, mu 1 subunit Transport NM_004047.3 ATP6V0B ATPase, H+ transporting, lysosomal 21kDa, V0 subunit b Transport NM_013442.1 STOML2 stomatin (EPB72)-like 2 Transport NM_004209.4 SYNGR3 synaptogyrin 3 Transport

NM_018711.2 SVOP SV2 related protein homolog (rat) Transport NM_174917.1 ACSF3 acyl-CoA synthetase family member 3 Metabolism: Energy Pathways NM_020410.1 ATP13A1 ATPase type 13A1 Metabolism: Energy Pathways NM_002134.2 HMOX2 heme oxygenase (decycling) 2 Metabolism: Energy Pathways NM_177938.2 PH-4 hypoxia-inducible factor prolyl 4-hydroxylase Metabolism: Energy Pathways NM_014180.2 MRPL22 mitochondrial ribosomal protein L22 Protein Metabolism NM_016039.1 C14orf166 chromosome 14 open reading frame 166 Nucleic Acid Metabolism NM_022731.2 NUCKS1 nuclear casein kinase & cyclin-dependent kinase substrate 1 Nucleic Acid Metabolism NM_001099274.1 TINF2 TERF1 -interacting nuclear factor 2 Nucleic Acid Metabolism NM_017518.5 UCHL5IP UCHL5 interacting protein Nucleic Acid Metabolism NM_006817.3 ERP29 endoplasmic reticulum protein 29 Protein Folding NM_012298.1 CAND2 cullin-associated and neddylation-dissociated 2 Transcription NM_000204.2 CFI complement factor I Immune Response NM_021034.2 IFITM3 interferon induced transmembrane protein 3 (1-8U) Immune Response NM_032412.3 C5orf32 chromosome 5 open reading frame 32 Unknown NM_001035005.2 C18orf32 chromosome 18 open reading frame 32 Unknown NM_022821.2 ELOVL1 elongation of very long chain fatty acids -like 1 Unknown NM_198406.1 PAQR6 progestin and adipoQ receptor family member VI Unknown NM_017733.2 PIGG phosphatidylinositol glycan anchor biosynthesis, class G Unknown NM_016606.2 REEP2 receptor accessory protein 2 Unknown NM_032635.2 TMEM147 transmembrane protein 147 Unknown

Table 7. Summary of identified interactors (unvalidated) from GLP-1R-Cub-TF screens of both human fetal brain (black) and human kidney (grey) NubG-X cDNA libraries. This data was compiled from the NCBI nucleotide BLAST databse and the HPRD.

Figure 11. Breakdown of identified interactors (unvalidated) from GLP-1R-Cub-TF screens of both human fetal brain and human kidney NubG-X cDNA libraries.

3.5.3 GIPR Large-Scale Library Screen The human fetal brain NubG-x cDNA library was successfully screened 4 times with GIPR-Cub- TF (Table 8). The average number of interactors screened was 1.40 x 106 clones and average library coverage was about 7.7%. Of the 90 prey plasmids sent for sequencing, BLAST

analysis revealed 32 unique interactors for the GIPR (Table 9). A breakdown of the total interactors identified shows about 34% related to metabolism (energy, protein, nucleic acids, carbohydrates) and 19% each related to cell signaling and transport (Figure 12).

GIPR Screen Library Coverage

Library Human fetal brain NubG-X

Complexity 1.8 x 107 independent clones

# times screened 4

# clones screened 1.40 x 106 (avg)

% library coverage 7.7% (avg)

# sequenced 90 samples

# clones identified 32 unique clones

Table 8. Summary of GIPR-Cub-TF screens of human fetal brain NubG-X cDNA library.

Accession # Gene Human Protein Function

NM_024718.2 C9orf86 chromosome 9 open reading frame 86 Cell Signaling NM_006176.1 NRGN neurogranin (protein kinase C substrate, RC3) Cell Signaling NM_004040.2 RHOB ras homolog gene family, member B (G-protein) Cell Signaling NM_001012720.1 RGR retinal G protein coupled receptor Cell Signaling NM_206852.1 RTN1 reticulon 1 Cell Signaling NM_030593.1 SIRT2 sirtuin 2 Cell Signaling NM_014399.3 TSPAN13 tetraspanin 13 Cell growth/Maintenance NM_007285.6 GABARAPL2 GABA(A) receptor-associated protein-like 2 Transport NM_006783.2 GJB6 gap junction protein, beta 6 Transport NM_020533.1 MCOLN1 mucolipin 1 Transport NM_001860.2 SLC31A2 solute carrier family 31, member 2 (CTR2) Transport NM_152227.1 SNX5 sorting nexin 5 Transport NM_004209.4 SYNGR3 synaptogyrin 3 (SYNGR3) Transport NM_020244.2 CHPT1 choline phosphotransferase 1 Metabolism: Energy Pathways NM_006755.1 TALDO1 transaldolase 1 Carbohydrate Metabolism NM_138973.2 BACE1 beta-site APP-cleaving enzyme 1 Protein Metabolism NM_001402.5 EEF1A1 eukaryotic translation elongation factor 1 alpha 1 Protein Metabolism NM_024326.2 FBXL15 F-box and leucine-rich repeat protein 15 Protein Metabolism NM_014041.2 SPCS1 signal peptidase complex subunit 1 homolog (S. cerevisiae) Protein Metabolism

NM_014752.1 SPCS2 signal peptidase complex subunit 2 homolog (S. cerevisiae) Protein Metabolism NM_032317.2 WBSCR18 Williams Beuren syndrome chromosome region 18 Protein Metabolism NM_006985.2 NPIP nuclear pore complex interacting protein Nucleic Acid Metabolism NM_001006639.1 TCEAL1 transcription elongation factor A (SII)-like 1 Nucleic Acid Metabolism NM_145062.1 ZUFSP zinc finger with UFM1-specific peptidase domain Nucleic acid metabolism NM_004813.1 PEX16 peroxisomal biogenesis factor 16 Protein Binding NM_001025101.1 MBP myelin basic protein Immune response NM_017455.2 NPTN neuroplastin Immune response NM_016108.2 AIG1 androgen-induced 1 Unknown NM_015439.2 CCDC28A coiled-coil domain containing 28A Unknown NM_198406.1 PAQR6 progestin and adipoQ receptor family member VI Unknown NM_032635.2 TMEM147 transmembrane protein 147 Unknown NM_007267.5 TMC6 transmembrane channel-like 6 Unknown

Table 9. Summary of identified interactors (unvalidated) from GIPR-Cub-TF screens of human fetal brain NubG-X cDNA library. This data was compiled from the NCBI nucleotide BLAST databse and the HPRD.

Figure 12. Breakdown of identified interactors (unvalidated) from GIPR-Cub-TF screen of human fetal brain NubG-X cDNA library.

3.5.4 GLP-2R Large-Scale Library Screen The human fetal brain NubG-x cDNA library was successfully screened 3 times with GLP-2R- Cub-TF (Table 10). The average number of interactors screened was 3.37 x 106 clones and average library coverage was about 18.7%. Of the 136 prey plasmids sent for sequencing, BLAST analysis revealed 88 unique interactors for the GLP-2R (Table 11). A breakdown of the total interactors identified shows about 27% related to metabolism (energy, protein, nucleic acids, lipid, RNA), 22% related to cell signaling and 14% related to cell survival (cell growth, apoptosis) (Figure 13).

GLP-2R Screen Library Coverage

Library Human fetal brain NubG-X

Complexity 1.8 x 107 independent clones

# times screened 3

# clones screened 3.37 x 106 (avg)

% library coverage 18.7% (avg)

# sequenced 136 samples

# clones identified 88 unique clones

Table 10. Summary of GLP-2R-Cub-TF screens of human fetal brain NubG-X cDNA library.

Accession # Gene Human Protein Function

NM_001077628.1 APH1A anterior pharynx defective 1 homolog A (C. elegans) Cell Signaling NM_013263.2 BRD7 bromodomain containing 7 Cell Signaling NM_001745.2 CAMLG calcium modulating ligand Cell Signaling NM_001280.1 CIRBP cold inducible RNA binding protein Cell Signaling NM_005076.2 CNTN2 contactin 2 (axonal) Cell Signaling NM_139072.3 DNER delta/notch-like EGF repeat containing Cell Signaling NM_005458.5 GABBR2 gamma-aminobutyric acid (GABA) B receptor, 2 Cell Signaling NM_005302.2 GPR37 endothelin receptor type B-like Cell Signaling NM_007355.2 HSP90AB1 Heat shock protein 90kDa alpha, class B member 1 Cell Signaling NM_130470.1 MADD MAP-kinase activating death domain Cell Signaling NM_005312.2 RAPGEF1 Rap guanine nucleotide exchange factor Cell Signaling NM_001788.4 SEPT7 septin 7 Cell Signaling NM_006772.1 SYNGAP1 synaptic Ras GTPase activating protein 1 homolog (rat) Cell Signaling NM_001024807.1 APLP1 amyloid beta (A4) precursor-like protein 1 Cell Growth/Maintenance NM_016564.3 CEND1 cell cycle exit and neuronal differentiation 1 Cell Growth/Maintenance NM_003277.2 CLDN5 claudin 5 Cell Growth/Maintenance NM_016641.3 GDE1 glycerophosphodiester phosphodiesterase 1 Cell Growth/Maintenance NM_004639.3 BAT3 HLA-B associated Cell Growth/Maintenance NM_013312.2 HOOK2 hook homolog 2 (Drosophila) Cell Growth/Maintenance NM_006082.2 TUBA1B tubulin, alpha 1b Cell Growth/Maintenance NM_006088.5 TUBB2C tubulin, beta 2C Cell Growth/Maintenance NM_177987.1 TUBB8 tubulin, beta 8 Cell Growth/Maintenance NM_007285.6 GABARAPL2 GABA(A) receptor-associated protein-like 2 Transport

NM_000832.5 GRIN1 glutamate receptor, ionotropic, N-methyl D-aspartate 1 Transport K+ large conductance Ca2+-activated channel, subfamily M, NM_0145054 KCNMB4 Transport beta member 4 NM_145648.2 SLC15A4 solute carrier family 15, member 4 Transport NM_052944.2 SLC5A11 Solute carrier family 5 (sodium/glucose cotransporter) Transport NM_001860.2 SLC31A2 solute carrier family 31 (copper transporters), member 2 Transport NM_020410.1 ATP13A1 ATPase type 13A1 Metabolism; Energy pathways NM_004356.3 CD81 CD81 molecule Metabolism; Energy pathways NM_004462.3 FDFT1 farnesyl-diphosphate farnesyltransferase 1 Metabolism; Energy pathways NM_005125.1 CCS copper chaperone for superoxide dismutase Protein Metabolism NM_182983.1 HPN hepsin (transmembrane protease, serine 1) Protein Metabolism NM_001969.3 EIF5 eukaryotic translation initiation factor 5 Protein Metabolism NM_016034.2 MRPS2 mitochondrial ribosomal protein S2 Protein Metabolism NM_000967.3 RPL3 ribosomal protein L3 Protein Metabolism NM_014752.1 SPCS2 signal peptidase complex subunit 2 homolog (S. cerevisiae) Protein Metabolism NM_003345.3 UBE2I ubiquitin-conjugating enzyme E2I (UBC9 homolog, yeast) Protein Metabolism NM_004514.3 FOXK2 forkhead box K2 Nucleic Acid Metabolism NM_006769.2 LMO4 LIM domain only 4 Nucleic Acid Metabolism NM_006593.2 TBR1 T-box, brain, 1 Nucleic Acid Metabolism NM_005008.2 NHP2L1 NHP2 non-histone chromosome protein 2-like 1 Nucleic Acid Metabolism NM_145062.1 ZUFSP zinc finger with UFM1-specific peptidase domain Nucleic acid metabolism NM_001402.5 EEF1A1 eukaryotic translation elongation factor 1 alpha 1 Transcription NM_001831.2 CLU clusterin Immune Response NM_001025092.1 MBP myelin basic protein Immune Response NM_006698.2 BLCAP bladder cancer associated protein Unknown NM_022821.2 ELOVL1 elongation of very long chain fatty acids Unknown NM_014039.2 C11orf54 chromosome 11 open reading frame 54 (C11orf54) Unknown NM_016063.2 HDDC2 HD domain containing 2 Unknown NM_006694.3 JTB jumping translocation breakpoint Unknown NM_001080546.1 LOC219854 hypothetical protein LOC219854 Unknown NM_207119.1 LRRC20 leucine rich repeat containing 20 Unknown NM_032889.3 MFSD5 major facilitator superfamily domain containing 5 Unknown NM_017733.2 PIGG phosphatidylinositol glycan anchor biosynthesis, class G Unknown NM_017916.1 PIH1D1 PIH1 domain containing 1 Unknown NM_016304.2 RSL24D1 ribosomal protein L24 like Unknown NM_201430.1 RTN3 reticulon 3 Unknown NM_032547.1 SCOC short coiled-coil protein Unknown NM_144582.2 TEX261 testis expressed 261 Unknown NM_007364.2 TMED3 transmembrane emp24 protein transport domain containing 3 Unknown

Table 11. Summary of identified interactors (unvalidated) from GLP-2R-Cub-TF screens of human fetal brain NubG-X cDNA library. This data was compiled from the NCBI nucleotide BLAST databse and the HPRD.

Figure 13. Breakdown of identified interactors (unvalidated) from GLP-2R- Cub-TF screen of human fetal brain NubG-X cDNA library.

3.5.5 GCGR Large-Scale Library Screen The human fetal brain NubG-x cDNA library was successfully screened 2 times with GCGR- Cub-TF (Table 12). The average number of interactors screened was 2.26 x 106 clones and average library coverage was about 12.5%. Of the 60 prey plasmids sent for sequencing, BLAST analysis revealed 37 unique interactors for the GCGR (Table 13). A breakdown of the total interactors identified shows about 19% related to each of cell signaling, transport and cell survival (cell growth, apoptosis) (Figure 14). As GCGR is highly expressed in the kidney, it has yet to be screend with the human kidney NubG-X cDNA prey library.

GCGR Screen Library Coverage

Library Human fetal brain NubG-X

Complexity 1.8 x 107 independent clones

# times screened 2

# clones screened 2.26 x 106 (avg)

% library coverage 12.5% (avg)

# sequenced 60 samples

# clones identified 37 unique clones

Table 12. Summary of GCGR-Cub-TF screens of human fetal brain NubG-X cDNA library.

Accession # Gene Human Protein Function

NM_199282.1 ARHGAP27 Rho GTPase activating protein 27 Cell Signaling NM_006888.3 CALM1 calmodulin 1 Cell Signaling NM_001743.3 CALM2 calmodulin 2 (phosphorylase kinase, delta) Cell Signaling NM_024408.2 NOTCH2 Notch homolog 2 Cell Signaling NM_020416.3 PPP2R2C protein phosphatase 2 regulatory subunit B, gamma isoform, Cell Signaling NM_000327.2 ROM1 retinal outer segment membrane protein 1 Cell Signaling NM_003876.1 TMEM11 transmembrane protein 11 Cell Signaling NM_004052.2 BNIP3 BCL2/adenovirus E1B 19kDa interacting protein 3 Cell Growth/Maintenance NM_015282.1 CLASP1 cytoplasmic linker associated protein 1 Cell Growth/Maintenance NM_003277.2 CLDN5 claudin 5 Cell Growth/Maintenance NM_002086.4 GRB2 growth factor receptor-bound protein 2 Cell Growth/Maintenance NM_177433.1 MAGED2 melanoma antigen family D, 2 Cell Growth/Maintenance NM_016564.3 CEND1 cell cycle exit and neuronal differentiation 1 Cell Growth/Maintenance NM_001677.3 ATP1B1 ATPase, Na+/K+ transporting, beta 1 polypeptide Transport NM_004047.3 ATP6V0B ATPase, H+ transporting, lysosomal 21kDa, V0 subunit b Transport NM_001694.2 ATP6V0C ATPase, H+ transporting, lysosomal 16kDa, V0 subunit c Transport NM_005745.6 BCAP31 B-cell receptor-associated protein 31 Transport NM_006539.2 CACNG3 calcium channel, voltage-dependent, gamma subunit 3 Transport NM_004710.3 SYNGR2 synaptogyrin 2 Transport NM_152725.2 ZIP12 solute carrier family 39 (zinc transporter), member 12 (SLC39A12) Transport NM_014752.1 SPCS2 signal peptidase complex subunit 2 homolog (S. cerevisiae) Protein Metabolism NM_001281.2 TBCB tubulin folding cofactor B Protein Metabolism NM_006817.3 ERP29 endoplasmic reticulum protein 29 Protein Folding NM_005517.3 HMGN2 high-mobility group nucleosomal binding domain 2 (HMG17 ) Nucleic Acid Metabolism NM_002116.5 HLA-A major histocompatibility complex, class I, A Immune Response NM_001009959.1 ERMN ermin, ERM-like protein Unknown NM_133493.2 CD109 CD109 molecule Unknown NM_001048225.1 DBNDD2 SCF apoptosis response protein 1 / dysbindin domain containing 2 Unknown NM_030926.4 ITM2C integral membrane protein 2C Unknown NM_024897.2 PAQR6 progestin and adipoQ receptor family member VI Unknown NM_032635.2 TMEM147 transmembrane protein 147 Unknown NM_017814.1 TMEM161A transmembrane protein 161A Unknown NM_053045.1 TMEM203 transmembrane protein 203 Unknown NM_173834.2 YIPF6 Yip1 domain family, member 6 Unknown

Table 13. Summary of identified interactors (unvalidated) from GCGR-Cub-TF screens of human fetal brain NubG-X cDNA library. This data was compiled from the NCBI nucleotide BLAST databse and the HPRD.

Figure 14. Breakdown of identified interactors (unvalidated) from GCGR- Cub-TF screen of human fetal brain NubG-X cDNA library.

3.6 Summary of Findings Here we used the MYTH system to screen B-class GPCR in order to identify novel protein interactors. The human fetal brain NubG-X cDNA library has been successfully screened using Cub-TF-fused glucagon, GLP-1, GIP and GLP-2 receptors. A total of 181 (15 overlap) unique proteins were identified from 12 successful large-scale library screens. A breakdown of the total interactors identified shows 26% related to metabolism (energy, protein, nucleic acids, carbohydrate, lipid, RNA), 21% related to cell signaling, 13% related to transport, 13% related to cell survival (cell growth, apoptosis) and 21% with unknown function (Figure 15). The datasets are primarily composed of novel GBPs with very few typical GBPs.

Figure 15. Breakdown of the total identified interactors (unvalidated) from all 12 receptor MYTH screens.

3.7 Discussion

3.7.1 Human Fetal Brain Expression While GLP-1R was shown by RT-PCR to be expressed in human fetal brain, the remaining 3 receptors were not detected. However, we showed through in silico analysis of various online databases that the positive interactors are also expressed in tissues where each respective receptor is found. Therefore, any prey library can be used as a pool of interactors to screen with any Cub-TF fused receptor. Furthermore, all 4 receptors have been reported to be expressed in the human brain which strongly suggests that they should also be present in the fetal brain (Mayo et al., 2003). As well, studies have shown that over 90% of GPCRs are expressed in the brain (Vassilatis et al., 2003), and therefore there is high probability that our receptors are either expressed in the fetal brain or that at least the receptor signaling machinery is present. As well, it is also possible that the current RT-PCR protocol was just not sensitive enough or the fetal brain RNA (separate from that used for NubG-X libraries) was too degraded for the detection of these receptors. Further optimization of these protocols may be required. Alternatively, there may be specific regions in the brain (i.e. hypothalamus) that are more and distinctly enriched with each of these receptors. Differential expression of the GLP-1R at different ages of fetal brain may indicate the time-depedence of GLP-1R expression in brain development.

3.7.2 Selection of Yeast Colonies Each yeast colony which grew under growth selection (-WLAH) represents the cDNA of a single putative interactor. If the number of colonies was <50 per plate, colonies were inoculated manually. However if colonies were of high density then the Qpix Technolgoy QArray Colony Picker System (Genetix, UK) was used. Usually, all the colonies were not inoculated and instead were chosen based on programmed parameters: colony diameter and colour intensity (for X-gal test). While selecting the bigger or darker colonies should represent the stronger interactions, I realize that the strength of the interaction is not necessarily indicative of importance as many complexing proteins do not strongly interact with the rest of their binding partners. It is also important to note that the clones are only partial cDNAs ranging from 0.6-2.0 kb. Any given protein may interact weakly as a partial cDNA, but more strongly if expressed at full length.

3.7.3 Low Number of Interactors Screened For both GLP-1R and GIPR screens of the human fetal brain cDNA library, the average number of cloned screened fell below the target of 2 million or more. In the MYTH system, mammalian bait proteins have been shown to be more prone to variations in expression levels when compared to bait proteins encoded by yeast genes. While it is uncertain why this happens, some potential factors include RNA stability, protein stability, suboptimal integration into the membrane or activation of the unfolded protein response (Krebs et al., 2004). Two possible solutions have been suggested to increase protein expression: 1) clone the bait into an alternative plasmid driven by a stronger promoter such as the ADH1 or TEF1 promoters; or 2) implement a yeast Ste2p short leader sequence which will not affect subcellular targeting, but will presumably increase expression of bait protein by enhancing the initiation coding region of the gene of interest (Romanos et al., 1992).

3.7.4 List of Putative Interactors From these screens, I have identified 181 protein candidates as possible interactors of these GPCRs. The categorical breakdowns of these putative prey interactors from each receptor screen begins to reveal anticipated common types of binding partners as would be expected with members of the same class of GPCRs, but importantly, also distinct interactors attributed to some functional differences of each GPCR. Since the glucagon receptor superfamily of receptors is composed of endocrine targets primarily involved in glucose homeostasis, it is expected that the majority of the identified interactors would fall under a metabolic role (e.g.

NUCK1, BACE1, FDFT1). As GPCRs have been shown to tranduce most cellular functions mediated by this family of receptors, it is no surprise that many of the interactors are involved in cellular communication and signal transduction (e.g. RHOB, RAPGEF1, CALM1). Furthermore, the glucose regulatory receptors, GLP-1R, GIPR and GCGR show a higher percentage of ion channel transport proteins, such as solute transporters and ATPases (e.g. SYNGR3, SLC31A2, KCNMB4, ZIP12, ATP1B1) which would presumably be involved in controlling islet excitability to effect insulin and glucagon secretion. Surprisingly, the intestinotrophic GLP-2R screen displayed a relatively low percentage of cell growth and maintenance related interactors (e.g. CEND1, GDE1, BAT3), and conversely, a surprisingly high percentage of this category was identified for the GCGR screen (e.g. BNIP3, CLDN2, GRB2, MAGED2). It is important to keep in mind that some of the percentages may not be representative as the total number of interactors is often low, particularly in the GLP-1R, GIPR and GCGR screens. As the greater majority of the mapped human genome is still without assigned function, it is not unexpected that more than one-fifth of the identified interactors were of unknown function. Interestingly, the dataset of putative interactors is primarily composed of novel GBPs, which may highlight the novelty of these findings. However, a limitation of the system is the lack of built-in positive controls. Unfortunately, most known interactors of these receptors were not identified in the dataset, with the exception of CALM1 in the GCGR screen. As mentioned in section 3.3.2, the lack of receptor activation and prevalence of false negatives may restrict the recruitment of many typical GBPs. Finally, as the library derived from human fetal brain tissue, it is not surprising that within the datasets there is a significant representation of brain or CNS-specific proteins. However, further analysis may reveal unknown extra-neural tissue expression and function.

CHAPTER 4: VALIDATION OF NOVEL INTERACTORS

4.1 Rationale From the previous chapter, I have identified 181 protein candidates. Being aware of the high probability of false positives, it is imperative that the next step be to verify each putative interactor using multiple validation assays. Therefore, I used two validation assays, the YTH prey retransformation tests and co-purification in HEK293T cells to confirm receptor-interactor PPI in both yeast and human cells respectively to filter out the false positives from my putative interactor lists. Additonally, I made use of online proteomics databases to assess each positive clone for biological relevance and likelihood of interacting with each receptor. As well, prey retransformation tests also allowed PPI validation of each interactor with the other 3 receptor family members.

4.2 Hypothesis Meaningful true interactors identified from the MYTH B-class receptor screen can be validated and separated from false positives in the initial interactor datasets. Prey retransformation tests will reveal commonality or cross-interaction between each putative receptor interactomes.

4.3 Introduction

4.3.1 False Positives in YTH screens The prevalence of false positives is the most common issue of YTH screening, with estimation ranging between 25 to 45% for YTH HTP screens (von Mering et al., 2002). It is important to realize that there are two types of false positives. The first is bona fide binding of the study protein to bait protein of interest but only in the context of the YTH assay, but not truly a physiologic interaction occurring in vivo. An explanation for this phenomenon is that this study protein is a member of a class of proteins which contain requisite recognition sequences or property for the bait, but is not the endogenous or native member that normally interacts with bait protein in normal cellular milieu. The second type of false positive is when the study protein does not bind to the receptor in a physiologically meaningful way, but somehow could induce TF activity independent of any meaningful PPI. Such artifacts of the YTH assay include capturing non-relevant PPIs, as a consequence of overexpression of heterologous or bait proteins, a process that can inadvertently cause endogenous expression of ubiquitin tag leading to self-activation resulting in release of TF. As well, this artifactual process can induce plasmid rearrangements or copy number changes that generate such auto-activators, or alter reporter genes in a manner causing constitutive expression (Fields, 2005).

4.3.2 Alternative validation tests It is because of the high propensity for false positives that any protein candidate from the YTH screen has to be subjected to a rigorous battery of biochemical and eventual functional validation tests, many of which have been developed into HTP approaches including co- purification (Li et al., 2004), FRET and BRET (Bacart et al., 2008; Boute et al., 2002). Comparison with datasets generated using a complementary HTP technology such as MS (Domon and Aebersold, 2006; Ho et al., 2002), tandem affinity purification (TAP) (Gavin et al., 2002) or phage display (Tong et al., 2002) experiments, also significantly increases confidence in YTH candidate lists. Finally, computational applications toward distinguishing between true interactions and false positives involve employing advanced learning algorithms, such as support vector machine (SVM) to YTH datasets. This pattern recognition software can be modified to assign confidence ratings of biological likelihood or relevance based common functional annotation of interacting proteins, compatibility with the bait protein structure or domains or using data compiled from microarray gene analysis and MS peptide identification experiments to compare PPI of homologues and paralogues of the putative interactor identified from past screens (Fields, 2005; Miller et al, 2005).

4.4 Method and Materials

4.4.1 Reagents The yeast strain used for the generation of bait prey retransformtation assays was Saccharomyces cerevisiae TH4.AP4 3-reporter gene system. All plasmid amplifications were performed using the in E.coli strain XL-10 Gold prepared using the Inoue method as described in Sambrook and Russell’s Molecular Cloning A Laboratory Manual (Vol.1 pt. 112-1.115). Human Embroyonic Kidney 293T cells (HEK293T) were used for transient transfection in co- purification and western blot analysis experiments.

4.4.2 Cell Culture

HEK293T cells were grown at 37°C in 5% CO2 in DMEM supplemented with 10% fetal bovine serum (Invitrogen) and penicillin-streptomycin (100 units/ml, 100 µg/ml) (Invitrogen).

4.4.3 In Silico Analysis Those proteins which passed the prey retransformation test were then screened through various online databases to determine expression at the gene, protein and mRNA levels in specific tissues, cellular localization, functional category and known physiological and/or pathophysiological relevance were all recorded in data tables. The databases used include:

PubMed, Human Protein Reference Database (HPRD) , Human Protein Atlas (HPA) , Beta Cell Consortium and GNF SymAtlas .

4.4.4 Prey Retransformation Test Yeast transformation was performed as previously described for bait construction. THY.AP4 yeast expressing the receptor of interest was cotransformed with 0.25-0.5μg each of putative protein interactor plasmid. Transformed yeast was plated on SD deficient of leucine (for bait) and tryptophan (for prey). Three days later yeast was replated on interaction selection plates of SD deficient of leucine, tryptophan, adenine and histidine, supplemented with X-gal and the optimal concentration of 3-aminotriazole as used in the large-scale library transformation.

4.4.5 Interactor Cloning Each potential interactor cDNA was subcloned out of the yeast expression vector (library plasmid) and into a 3xFLAG mammalian expression vector using the Invitrogen Gateway LR clonase II Enzyme Reaction kit. Cloning was performed according to kit instructions. Briefly, the reaction mix (0.5 μl entry clone, 0.5 μl pV1900 destination vector, 0.5 μl TE buffer pH10, 1

μl LR clonase enzyme, 4.5 μl double distilled H2O) was vortexed and incubated at 25°C for 1 h. 0.5 μl Proteinase K solution was added to terminate reaction and incubated at 37°C for 10 min. 0.5 μl of the reaction mix was added to 50 μl of E.coli XL-10 Gold competent cells and incubated on ice for 30 min and then heat shocked at 42°C for 30 sec. 250 μl of S.O.C. medium (Invitrogen) was added and the culture was incubated at 37°C with shaking (200RPM) for 1 h then plated on LB +Ampicillin (100ug/μl) plates. Plates were incubated overnight for 16- 18 h at 37°C. Single colonies were picked into 5mL LB+Ampicillin (100ug/ul) liquid cultures and incubated overnight for 16-18hours at 37°C. Each culture was miniprepped using the GenElute plasmid miniprep kit (Sigma) and eluted in 50 μl of double distilled H2O and verified by sequencing.

4.4.6 Co-purification HEK293 cells plated in 6-well plates were preincubated in 1 ml OPTI-MEM for 30 min. For each well, 0.5ug of V5-His-tagged receptor construct, 0.5 μg of FLAG-tagged interactor construct and 2.5 μg LipofectAMINE 2000 (Invitrogen) were each added to 300 μl OPTI-MEM and incubated at RT for 5 min, before being added together and incubated for 30 min. Transfection mix was added drop-wise to each well after preincubation media was removed and fresh 1 ml OPTI-

MEM was added. Transfected cells were incubated for 4-6 h at 37°C in 5% CO2and then transfection mix was removed and replaced with 1 ml DMEM supplemented with 10% fetal

59 bovine serum (Invitrogen) and penicillin-streptomycin (100 units/ml, 100 µg/ml) (Invitrogen). Transfection efficiency in HEK293T cells was about 80%. 36-48 hours after transfection, the HEK293 cells were washed with ice-cold saline-buffered solution (phosphate-buffered saline at pH7.4), then harvested in 600 μl lysis buffer (1% digitonin, C12E8, 5mM imidazole, 400 μM PMSF, 10μM leupeptin, 2.9μM bestatin, 10μM pepstatin A, PBS). The cells were left on ice (4 °C) for 30 min and then centrifuged at 13000 rpm for 30 min. 60 µl of Ni2+ beads (50% slurry) (Sigma-Aldrich) was washed 3 times in 1 mL equilibration buffer (0.1% digitonin, C12E8, 5 mM imidazole, 400 μM PMSF, 10 μM leupeptin, 2.9 μM bestatin, 10 μM pepstatin A, PBS) at rotated at 4°C for 5 min and then centrifuged at 4100 rpm for 5 min. The beads were then incubated with 0.4 μl of cell extract and rotated for 2 h at

4°C. The precipitation lysate were washed three times with wash buffer (0.1% digitonin, C12E8, 5 mM imidazole, 400μ M PMSF, 10 μM leupeptin, 2.9 μM bestatin, 10 μM pepstatin A, PBS) and then eluted in 1mL of 500 mM imidazole in PBS. Precipitated proteins were identified by Western immunoblotting.

4.4.7 Immunoblotting Sample protein concentration was quantified using the Bradford method, and the optical density (OD) was measure by spectrocounter at 590nm. Twenty-five µg of protein from each sample was separated on a 10% polyacrylamide gel and transferred to PVDF-PlusTM membrane (Fisher). Anti-V5 and anti-FLAG primary antibodies form Invitrogen were detected with rabbit secondary antibody to mouse (horseradish peroxidase-conjugated) from Sigma-Aldrich for 1 h at room temperature. Visualization was by chemiluminescence (ECL; Amersham Biosciences) and exposure of immunoblots images were acquired using the Kodak image station 4000pro (Carestream Health, Inc, Rochester, NY)

4.5 Results

4.5.1 Validation by Prey Retransformation Tests To ensure that the prey interactors identified in the screens are true positive interactions, each of the receptor’s putative interactors was individually transformed back into AP4.THY yeast expressing the receptor. To pass the prey retransformation test, 2 of 3 colonies of a particular bait-prey transformation must grow on selection and colorimetric media in three independent tests. Additionally, this test was also used to verify each set of interactors against the three other Cub-TF fused receptors to test for cross-interaction among class members.

Of the 36 unique interactors identified by the GLP-1R-Cub-TF from both the human fetal brain and kidney NubG-X library screens, 9 passed prey retransformation tests. In addition, 1 unique GIPR interactor and 7 unique GLP-2R interactors were shown to cross-interact with GLP-1R, totalling 17 validated protein interactors (Figure 16; Table 14).

Figure 16. GLP-1R putative interactor proteins pass prey retransformation test. Validation of protein-protein interaction of each GLP-1R putative interactors was performed by individually retransforming each NubG tagged interactor back into yeast expressing the GLP-1R-Cub-TF tagged respective receptor. Here, TSPAN13, SYNGR3 and NRGN pass.

Accession # Gene Human Protein Function

NM_001077628.1 APH1A anterior pharynx defective 1 homolog A (C. elegans) Cell Signaling NM_006176.1 NRGN neurogranin Cell Signaling NM_016564.3 CEND1 cell cycle exit and neuronal differentiation 1 Cell Growth/Maintenance NM_001024807.1 APLP1 amyloid beta (A4) precursor-like protein 1, variant 1 Cell Growth/Maintenance NM_005563.3 STMN1 stathmin 1/oncoprotein 18 Cell Growth/Maintenance NM_014399.3 TSPAN13 tetraspanin 13 Cell Growth/Maintenance NM_145648.2 SLC15A4 solute carrier family 15, member 4 Transport NM_001860.2 SLC31A2 solute carrier family 31 (copper transporters), member 2 Transport NM_004209.4 SYNGR3 synaptogyrin 3 Transport NM_020410.1 ATP13A1 ATPase type 13A1 Metabolism: Energy Pathways NM_004356.3 CD81 CD81 molecule Metabolism: Energy Pathways NM_004462.3 FDFT1 farnesyl-diphosphate farnesyltransferase 1 Metabolism: Energy Pathways NM_182983.1 HPN hepsin (transmembrane protease, serine 1) Metabolism: Energy Pathways NM_177938.2 PH-4 hypoxia-inducible factor prolyl 4-hydroxylase Metabolism: Energy Pathways NM_012298.1 CAND2 cullin-associated and neddylation-dissociated 2 Transcription NM_001035005.2 C18orf32 chromosome 18 open reading frame 32 Unknown NM_022821.2 ELOVL1 elongation of very long chain fatty acids Unknown NM_032889.3 MFSD5 major facilitator superfamily domain containing 5 Unknown NM_017733.2 PIGG phosphatidylinositol glycan anchor biosynthesis, class G Unknown Table 14. Summary of GLP-1R-Cub-TF putative interactors which tested positive in prey retransformation tests.

Of the 32 unique interactors identified by the GIPR-Cub-TF from the human fetal brain NubG-X library screens, 14 passed prey retransformation tests. In addition, 8 unique GLP-2R interactors were shown to cross-interact with GLP-1R, totalling 22 validated protein interactors (Figure 17; Table 15). Figure 17. GIPR putative interactor proteins pass prey retransformation test. Validation of protein-protein interaction of each GIPR putative interactors was performed by individually retransforming each NubG tagged interactor back into yeast expressing the GIPR-Cub-TF tagged respective receptor. Here, RHOB, NTPN, CHPT1, MCOLN1 and AIG1 pass.

Accession # Gene Human Protein Function

NM_001077628.1 APH1A anterior pharynx defective 1 homolog A (C. elegans) Cell Signaling NM_005458.5 GABBR2 gamma-aminobutyric acid (GABA) B receptor, 2 Cell Signaling NM_005302.2 GPR37 endothelin receptor type B-like Cell Signaling NM_004040.2 RHOB Ras homolog gene family, member B Cell Signaling NM_001012720.1 RGR retinal G protein coupled receptor Cell Signaling NM_001024807.1 APLP1 amyloid beta (A4) precursor-like protein 1, variant 1 Cell Growth/Maintenance NM_005563.3 STMN1 stathmin 1/oncoprotein 18 Cell Growth/Maintenance NM_014399.3 TSPAN13 tetraspanin 13 Cell Growth/Maintenance NM_020533.1 MCOLN1 mucolipin 1 Transport NM_004209.4 SYNGR3 synaptogyrin 3 Transport NM_004356.3 CD81 CD81 molecule Metabolism: Energy Pathways NM_020244.2 CHPT1 choline phosphotransferase 1 Metabolism Energy Pathways NM_182983.1 HPN hepsin (transmembrane protease, serine 1) Metabolism Energy Pathways NM_138973.2 BACE1 beta-site APP-cleaving enzyme 1 Protein Metabolism NM_032317.2 WBSCR18 Williams Beuren syndrome chromosome region 18 Protein Metabolism NM_145062.1 ZUFSP zinc finger with UFM1-specific peptidase domain Nucleic Acid Metabolism NM_017455.2 NPTN neuroplastin Immune Response NM_016108.2 AIG1 androgen-induced 1 Unknown NM_032889.3 MFSD5 major facilitator superfamily domain containing 5 Unknown NM_198406.1 PAQR6 progestin and adipoQ receptor family member VI Unknown NM_017733.2 PIGG phosphatidylinositol glycan anchor biosynthesis, class G Unknown

NM_032635.2 TMEM147 transmembrane protein 147 Unknown

Table 15. Summary of GIPR-Cub-TF putative interactors which tested positive in prey retransformation tests.

Of the 88 unique interactors identified by the GLP-2R-Cub-TF from the human fetal brain NubG- X library screens, 20 were tested and 10 total passed prey retransformation tests (Figure 18; Table 16).

Figure 18. GLP-2R putative interactor proteins pass prey retransformation test. Validation of protein-protein interaction of each GLP-2R putative interactors was performed by individually retransforming each NubG tagged interactor back into yeast expressing the GLP-2R-Cub-TF tagged respective receptor. Here, MFSD5, SLC3A12, GABBR2 AND CD81 pass.

Accession # Gene Human Protein Function

NM_001077628.1 APH1A anterior pharynx defective 1 homolog A (C. elegans) Cell Signaling NM_005458.5 GABBR2 gamma-aminobutyric acid (GABA) B receptor, 2 Cell Signaling NM_005302.2 GPR37 endothelin receptor type B-like Cell Signalling NM_001024807.1 APLP1 amyloid beta (A4) precursor-like protein 1, variant 1 Cell Growth/Maintenance NM_005563.3 STMN1 stathmin 1/oncoprotein 18 Cell Growth/Maintenance NM_001860.2 SLC31A2 solute carrier family 31 (copper transporters), member 2 Transport NM_004356.3 CD81 CD81 molecule Metabolism: Energy Pathways NM_004462.3 FDFT1 farnesyl-diphosphate farnesyltransferase 1 Metabolism: Energy Pathways NM_182983.1 HPN hepsin (transmembrane protease, serine 1) Metabolism: Energy Pathways NM_145062.1 ZUFSP zinc finger with UFM1-specific peptidase domain Nucleic Acid Metabolism

Table 16. Summary of GLP-2R-Cub-TF putative interactors which tested positive in prey retransformation tests.

Retransfomation tests are still ongoing for both GCGR and GLP-2R receptors. Only 2 GLP-2R interactors were shown to cross react with the GCGR thus far (Table 17).

Accession # Gene Human Protein Function

NM_005302.2 GPR37 endothelin receptor type B-like Cell Signalling NM_004356.3 CD81 CD81 molecule Metabolism: Energy Pathways

Table 17. Summary of GCGR-Cub-TF putative interactors which tested positive in prey retransformation tests.

By compiling all the retransformation positive clones, we have generated a putative receptor interactome or “receptosome” for the glucagon superfamily of receptors (Figure 19A). Interestingly, 13 out of 30 (43%) of the candidate proteins show cross-interaction with multiple receptors (18 with 1 receptor, 8 with 2 receptors, 5 with 3 receptors and 2 with 4 receptors) (Figure 19B). A breakdown of the total interactors which passed the prey transformation test shows about 34% related to metabolism (energy, protein, nucleic acids, carbohydrates), 20% related to cell signaling, 10% to related to transport and 7% to cell growth and maintenance (Figure 19C).

Figure 19. Summary of all putative interactors which tested positive in prey retransformation tests. A) Putative receptor interactome for the glucagon superfamily of receptors. Bolded circles represent prey interactors with 3 or more receptor interacting partners. B) Categorization of all retransformation positive clones based on the number of receptor interacting partners. C) Breakdown of all retransformation positive clones based on putative cellular function.

4.5.2 In Silico Analysis of Validated Interactors Interactors that passed the prey retransformation test were then thoroughly screened through various online databases to determine potential function and expression at the gene (GNF SymAtlas), mRNA transcript (Beta cell Corsortium) or protein level (HPRD, HPA) in tissues where receptors are expressed. For GLP-1R and GIPR any protein that showed no evidence of expression in the pancreas or brain were discarded. For GCGR, pancreas, liver or brain expression was required; and for GLP-2R, small intestine, colon, brain or lung expression was required. NCBI PubMed was also used to explore past literature regarding each interactor to gain insight on any potential relation to known glucagon-related peptide receptor function, signaling, regulation or interaction. Analyses of a few selected interactors of interest are described in the discussion (section 4.7.3).

4.5.3 Validation by Co-purifcation To ensure that our receptors and their validated (in yeast) interactors could interact in a mammalian setting, some full length interactors were cloned using the Invitrogen Gateway Technology into pV1700 mammalian expression vectors containing an NT 3xFLAG tag. The V5-His tagged receptor was transiently cotransfected with the 3xFLAG tagged putative interactor in HEK293T cells, and the His-tagged receptor along with any interacting proteins were pulled down with Ni2+ resin bead (Sigma-Aldrich) (Figure 20).

Figure 20. Co-purification to validate receptor interactors. Receptor and prey interactor were cloned into tagged mammalian expression vectors, pcDNA3.1D V5-his and pV1900 3xFLAG respectively, and cotransfected into HEK293T cells. Ni2+ beads were used to pull down the His-tagged receptor which was co-immunoprepitated with the 3xFLAG- tagged bound prey interactor.

With a focus on validating interactors which had interacted with 3 or more receptors, 3 of the 3xFLAG tagged putative interacting proteins, APLP1-3xFLAG, CD81-3xFLAG and STMN1- 3xFLAG, were successfully pulled down with each of the three V5-his tagged receptors, GLP- 1R-V5-His, GIPR-V5-His and GLP-2R-V5-His (Figure 21). We conclude that from the MYTH system and co-purification assays that APLP1, CD81 and STMN1 interact with GLP-1R, GLP- 2R and GIPR both in yeast and human cells.

Figure 21. APLP1, CD81 and STMN1 are co-immunoprecipitated with GLP-1R, GIPR and GLP-2R in HEK293T cells. Each V5/His-tagged receptor (GLP-1R, GIPR, GLP-2R) was cotransfected with each 3xFLAG tagged prey interactor (APLP1, CD81, STMN1) in HEK293T cells and co-purified with Ni2+ beads. Anti-V5 and anti-FLAG antibodies were used to immunoblot (IB) against the V5-tagged receptor and 3xFLAG-tagged interactor respectively.

4.6 Summary of Findings Here we show that the interactors identified in the large-scale library screens can be validated in both yeast and mammalian settings. Several prey interactors, primarily those originally identified from incretin hormone receptors, GLP-1R and GIPR, screens were validated through prey retransformation assays. To assess which of these are physiologically relevant interactors I have utilized various online proteomics databases to select out biologically unlikely binding partners based on relevant cellular localization, tissue expression and cellular function. Finally, interactions of 3 proteins were successfully validated by co-purification in a mammalian cell line, HEK293T cells.

4.7 Discussion

4.7.1 Screening out False positives In my study, while the NubG/NubI test and pilot screens were performed to optimize stringency conditions, it was realized that background or false positive could not be completely eliminated from the MYTH screens. Therefore, retransformation tests are necessary to confirm bait-prey interaction in a 1-to-1 ratio to weed out false positives. This assay also allows us to test each interactor against other receptor class members. Each of the 4 class-B GPCRs used in this study shares at least 50% homology with each other and thus cross-over within interactomes is highly probable. One further test that will be performed involves testing each interactor against a non-B-class GPCR or non-cognate bait to make sure that each interactor is bait-dependent or B-class GPCR specific. Those putative interactors that are positive for the original bait and negative for the non-cognate bait can be considered specific to the B-class. Thus, false positives from MYTH screens can be rapidly tested and eliminated using a simple set of genetic criteria.

4.7.2 Co-purification There is an argument that overexpressing any two proteins will promote them to stick together. However, controls were run to ensure as much confidence as possible in the results. In

67 addition to the eluted sample, total lysate, unbound protein and wash buffer residue were also taken to run in parallel on the polyacrylamide gel. No bands in the wash lanes indicate that the interactor protein in the elution is bound to the receptor protein and is not just an artifact of overexpression. To date, co-immunoprecipitation (co-IP) is the only method enabling purification of protein complexes from native tiessues expressing endogenous receptors (Daulat et al., 2009). Ideally we would use monoclonal antibodies against endogenous proteins available to perform co-immunoprecipitation, thus avoiding the use of epitope tags which may interfere with PPI. Unfortunately, good quality antibodies that are sufficient for immunoprecipitation are not always available, which is the case for our 4 receptors. Furthermore, with the number of putative prey interactors identified from our large scale screen, it would be impractical to acquire each individual specific antibody.

4.7.3 Potential Relevance of Validated Interactors The cross-interaction seen between the glucagon receptor superfamily (Figure 19) is not unexpected based on the shared homology between receptors. The existence of common interactors may explain how these different receptors are able to mediate such similar function, specifically between the two incretin hormone receptors, GLP-1 and GIPR, which share many insulintropic and cytoprotective action. Furthermore, it is more likely that common interactors to the entire class of GPCRs are genuinely physiologically important and not likely to be false positives; and thus, such common molecules should take priority over the non-common interactors for further higher yield study. I therefore focused on validating the following interactors which I found to interact with multiple receptors and discuss each of them further below. This of course does not mean that non-common interactors which may confer distinct cellular actions by the different members of the glucagon class of GPCRs are not important, and thus will be pursued later. In addition the three interactors which have been successfully confirmed by co-purification (APLP1, CD81, STMN1), I will also discuss the potential biological relevance of 4 additional putative interactors of interest (APH1A, GABBR2, GPR37, HPN).

4.7.3.1 APH1A Anterior pharynx defective 1 homolog A (C. elegans) (APH1A) was identified from the GLP-2R MYTH screen and further shown to interact with GLP-1R and GIPR through prey retransformation tests. The HPRD report shows APH1A as an integral membrane protein expressed in the brain, kidney, liver, small intestine, stomach, testes and uterus. According to GNF SymAtlas, the gene is expressed ubiquitously; however, it is most enriched in the lung, thyroid, B lymphocytes, prostate and heart. Lower levels of gene expression are shown in the

68 pancreatic islets which are further confirmed by a 100% matched prediction of expression in pancreatic islet by the β-cell corsortium DoTS transcripts. APH1A is a multipass transmembrane protein that obtained its name from an initial observation where mutation of the Aph1 resulted in a lack of anterior pharynx development in C.elegans (Goutte et al., 2002). APH1A complexes with preseniln and nicstrin to form the gamma- secretase protease complex (Kimberly et al., 2003; Lee et al., 2002), which, along with beta- secretase, functions in the proteolysis of amyloid-beta precursor protein (described in 4.6.3.1) resulting in release of amyloid beta (Aβ). When misfolded, Aβ can aggregate and accumulate in the brain inducing an ER unfolded protein response and apoptosis which can lead to Alzheimer’s disease (AD) (Francis et al., 2002). GLP-1 has been shown to not only protect neurons from Aβ-induced apoptosis in vitro, but also lower brain levels of Aβ in mice (Perry et al., 2003), and has therefore been suggested as a novel therapeutic strategy to treating a variety of neurodegenerative disorders including AD (Perry and Grieg, 2005). Perhaps GLP-1R reduces Aβ by downregulating APH1A expression which has been shown to correlate with gamma-secretase activity (Marlow et al., 2003). Furthermore, GLP-2 has also demonstrated to increase neural cell survival by protecting hippocampal cells from glutamate-induced apoptosis in vitro (Lovshin et al. 2004). Gamma-secretase complex is also responsible for intramembrane proteolysis of Notch, which is a signaling pathway critical for proper tissue development and differentiation of many tissues. Suzuki et al. (2003) demonstrated that GLP-1 induces differentiation of developing and adult intestinal epithelial cells into insulin-producing cells through upregulation of Notch-related gene neurogenin3 (NGN3). Furthermore, all four Notch receptors have been shown to be involved in pancreatic oragnogenesis (Lammert et al., 2000). Therefore, both GLP-1R and GLP-2R signaling may regulate APH1A to mediate their neural cytoprotective effects and cell proliferative and differentiation effects.

4.7.3.2 APLP1 Amyloid beta (A4) precursor-like protein 1 (APLP1) was identified from the GLP-2R MYTH screen and further shown to interact with GLP-1R and GIPR through prey retransformation test. The HPRD report shows APLP1 to be expressed primarily in the perinuclear region of blood and brain tissue where it exhibits transcription regulation activity to coordinate synapse organization and biogenesis. Furthermore, GNF SymAtlas and β-cell corsortium DoTS transcripts suggest expression of APLP1 in the pancreatic islet at the gene and mRNA transcript level. The APLP1 gene encodes this human membrane-associated glycoprotein, which is a member of the highly conserved amyloid precursor protein (APP) gene family. While the primary

69 function of this family of integral membrane proteins remains unknown, it is most highly expressed in neuronal synapses where is believed to regulate both synapse formation and neural plasticity. Similar to many APP family members, APLP1 has also been shown to play a role in synaptic maturation during cortical development. However, studies on APPs have focused on its role in the accumulation of amyloid plaques seen in the development of AD, where it acts as a precursor protein for Aβ which comprises the primary constituent of the amyloid plaques (Yankner and Lu, 2009). As mentioned above, GLP-1 has well-established neurotrophic effects which include reducing Aβ-induced apoptosis and overall Aβ brain levels in mice (Perry et al., 2003), thus implicating GLP-1 as a promising therapeutic strategy to treating AD (Perry and Grieg, 2005). Furthermore, GLP-2 has also demonstrated to increase neural cell survival by protecting hippocampal cells from glutamate-induced apoptosis in vitro (Lovshin et al. 2004). Perhaps, both GLP-1R and GLP-2R signaling regulates APLP1 to mediate their neural cytoprotective effects. Upon intracellular cleavage of APLP1 by proteases in the secretase family, a cytoplasmic fragment is released which may act as a transcriptional activator to mediate apoptosis (Yankner and Lu, 2009). Similarly, islet amyloid polypeptide (or amylin) which is related to Aβ can induce apoptotic cell death of pancreatic β-cells which has been implicated in the development of type 2 diabetes (Lorenzo et al., 1994). Normally, amylin is cosecreted with insulin from the β-cells in response to nutrient ingestion to synergistically regulate glucose homeostasis by reducing food intake, gastric emptying, release of digestive enzymes and glucagon secretion (Haataja, et al., 2008). Most interestingly, Needham et al. (2008) demonstrated that if you knockout of APLP1 and APLP2, the mice become both hypoglycaemic and hyperinsulinemic which strongly suggests that these proteins play a role in regulating glucose homeostasis. Both incretin hormones, GLP-1 and GIP have both been shown to protect β-cells from apoptosis (Drucker, 2006), however not specifically against amylin-induced apoptosis. It is possible that GLP-1R or GIPR receptor activation regulates APLP1 to mediate known cytoprotective and even gluco- regulatory effects. Whether these two receptors have a common pathway downstream APLP1 needs to be further explored. As well, the differential upregulation of APLP1 seen in small intestinal carcinomas suggests a novel role for this protein as a gastrointestinal neuroendocrine tumour-specific marker and therapeutic target (Arvidsson et al., 2008). As such, APLP1 could potentially play a role in the anti-apoptotic and proliferative actions of GLP-2 on the small bowel which has strongly implicated tumour cell growth in many human cancer cell lines (Masur et al. 2006) and murine cancer models (Iakoubov et al., 2009; Thulesen et al., 2004).

4.7.3.3 CD81 The CD81 molecule or antigen (CD81) or cluster of differentiation 81 was identified from the GLP-2R MYTH screen and further shown to interact with GLP-1R, GIPR and GCGR through the prey retransformation test. The HPRD and GNF SymAtlas reports show ubiquitous tissue expression and distribution at the protein and gene levels, including in the pancreatic islet, as confirmed by the β-cell corsortium DoTS transcripts prediction. CD81 was also shown to be an enzymatic plasma membrane protein involved in metabolic energy pathways in the HPRD report. Originally called target of antiproliferative antibody 1 (TAPA1) or tetraspanin 28 (TSPAN28), CD81 is a member of the tetraspanin transmembrane 4 superfamily which are integrin- associated cell surface glycoproteins. These proteins play roles in diverse cellular actions including cell adhesion and motility, cell proliferation and differentiation (Berditchevski, 2001), protein trafficking (Berditchevski and Odintsova, 2007), cell fusion (Miyado et al., 2000) and in tumour metastasis (Zoller et al., 2006, 2009). The ability of these proteins to interact with each other and a wide range of other integral membrane proteins lead to the hypothesis that tetraspanins may work to facilitate the formation and stability of functional molecular signaling (Maecker et al., 1997; Yunta and Lazo, 2003). Furthermore, tetraspanins may act as transmembrane scaffolds that tightly regulate transient interactions by coordinating the presentation and spatial organisation of various membrane complexes and thus participate in many different biological roles (Charrin et al., 2009). CD81 is most well studied for its role in signal transduction and cell adhesion in B and T lymphocytes. CD81 coordinates and stabilizes the association with CD19, CD21 and Leu-13 to form a signaling complex which lowers the threshold for B cell activation, and complexes with CD4 and CD8 in T cells to generate a costimulatory signal for CD3 (Levy et al., 1998). Additionally, CD81 functionally interacts with many integrins and is reported to influence adhesion, morphology, activation, proliferation, and differentiation in other cell types including Jurkat cells, thymocytes and astrocytes (Maecker et al., 1997). Therefore, it is quite feasible that CD81 may serve as a molecular facilitator of the various glucagon receptor superfamily signalling complexes, particularly those relating to cell proliferation and differentiation.

4.7.3.4 GABBR2 Gamma-aminobutyric acid (GABA) B receptor, 2 (GABBR2), originally known as GPR51 was identified from the GLP-2R MYTH screen and further shown to interact with GIPR through prey retransformation tests. The HPRD report shows a GPCR that is expressed in many tissues including pancreas, brain, heart, liver, kidney, small intestine, ovary, testis and skeletal muscle.

GNF SymAtlas displays expression only in the brain with highest levels in the prefrontal cortex, while the β-cell consortium displayed a predicted DoTS transcript similar to GABBR2.

GABBR2 is one of 2 subtypes of GABAB receptors which are inhitory receptors of the metabotropic glutamate C-class GPCRs (Dutar and Nicoll, 1988). GABBR2 exists primarily as a heterodimer with GABBR1 localized to neuronal membranes of the central and peripheral autonomic nervous system (Jones et al., 1998; White et al., 1998). Stimulation of K+ channel opening causes hyperpolarization of the neuron and inhibiton of AC (Martin et al., 1999) decreasing cell conductance to Ca2+ and therefore inhibiting neurotransmitter release (Flippov et al., 2000). Since GABAB receptors are expressed in most of the biologically revelant tissues of GLP-1R and GIPR, it is plausible that each of these receptor may couple to GABBR2 to regulate their opposing effects on AC and on K+ channels to modulate insulin secretion in pancreatic β-cells.

4.7.3.5 GPR37 Endothelin receptor type B-like (GPR37) was identified from the GLP-2R MYTH screen and further shown to interact with GLP-1R, GIPR and GCGR through prey retransformation tests. The HPRD report shows GPR37 to be a GPCR expressed primarily at the plasma membrane of the brain and liver. The GNF SymAtlas confirms gene expression at the brain and very low levels in pancreas and islet; however the β-cell consortium shows 88% identity of a 100% predicted DoTS transcripts similar to GPR37. The orphan G-protein-coupled receptor 37 (GPR37) is also known as parkin-associated endothelin receptor-like receptor (PAELR) because it is a major substrate of the ubiquitin ligase (E3) parkin, which is responsible for ubiquination and degradation of PAELR. However, in the absence of functional parkin or when GPR37 is overexpressed, accumulation in dopaminiergic neurons induces ER stress leading to the neurodegeneration seen in autosomal recessive juvenile Parkinsonism (Imai et al., 2001, 2002). GPR37 expression is highly concentrated in the brain (Zeng et al., 1997), and has been specifically shown to form insoluble aggregates in the Lewy bodies and neuritis seen in patients with Pakrinson’s disease (PD) (Murakami et al., 2004). Furthermore, Marazziti et al. (2009) recently demonstrated that overexpression of GPR37 promotes protection against PD and related neurodegenerative diseases. All four glucagon receptor superfamily members are expressed in the brain, and GLP-1R and GLP-2R have specifically been shown to promote neural cell survival. Interestingly, studies on the effect of GLP-1R receptor activation in different murine models of PD have shown convincing evidence of GLP-1’s ability to reverse neurodegeneration (Bertilsson et al., 2008; Harkavyi et al., 2008; Li et al., 2009). It is plausible that GPR37 may play a role in downstream signaling pathways leading to GLP-1 and GLP-2 mediated neuroprotective effects.

4.7.3.6 HPN Hepsin or transmembrane protease serine 1 (HPN) was identified from the GLP-2R MYTH screen and further shown to interact with GLP-1R and GIPR through prey retransformation tests. The HPRD report shows HPN to be a cell surface serine protease expressed in the liver where it participates in proteolysis and peptidelysis. GNF SymAtlas shows major gene expression in the liver but also significant levels in the pancreatic islet and pancreas relative to other tissues, while the β-cell corsortium DoTS transcripts predict a 100% match of expression in pancreatic islet. The HPN gene encodes a type II transmembrane serine protease which is present at low levels in most tissues, but is most enriched in the liver (Tsuji et al., 1991). This protein may be involved in diverse cellular functions including blood coagulation (Kazama et al., 1995), maintenance of mammalian cell morphology and the growth (Torres-Rosado et al., 1993) and progression of certain cancers (Chen et al., 2006; Nakamura et al., 2006, 2008) particularly prostate cancer (Klezovitch et al., 2004). HPN may play a role in the protein complexes which mediate the proliferative actions of GLP-1 and GIP seen in the pancreatic β-cell.

4.7.3.7 STMN1 Stathmin 1 (STMN1), also known as oncoprotein 18, was identified from the GLP-2R MYTH screen and further shown to interact with GLP-1R and GIPR through prey retransformation test. Similar to CD81, the HPRD report demonstrates ubiquitous tissue expression and distribution, including in the pancreatic islet, as confirmed by the β-cell consortium DoTS transcripts prediction. Furthermore, the report suggests that STMN1 is a cytoplasmic signaling protein involved in cell growth and maintenance. STMN1 is a member of the stathmin gene family and its role in regulating the rate of microtubule assembly is well established. It is a ubiquitously expressed cytosolic phosphoprotein which primarily acts to promote microtubule disassembly (Rubin and Atweh, 2004). Since STMN1 is critical for regulating mitotic initiation and termination, mutation or dysfunction of STMN1 leads to uncontrolled cell division eventually resulting in cancer (Cassimeris, 2002). Microtubule interaction plays a key role in insulin synthesis and release, specifically in proinsulin biosynthesis and conversion (Pipeleers et al., 1980). Both GLP-1 and GIP increase insulin biosynthesis (Drucker, 2006) and it is thus plausible that downstream signaling may involve STMN1 activation. As well, the rapid proliferative capability of GLP-2 action may also involve regulation of STMN1 to promote intestinal growth.

CHAPTER 5: GENERAL DISCUSSION

5.1 Summary of Findings The present work is the first example of a split-ubiquitin interaction screen using an in situ expressed full-length GPCR of the secretin-like B-class, demonstrating the suitability of the described improvements in the screening protocol. I have identified novel interactors of the glucagon receptor superfamily, employing this newly adapted MYTH system on a large scale basis, whereby PPIs were assessed in situ at the cell membrane simulating live-cell physiology, which was not previously possible. GLP-1R, GIPR, GLP-2R and GCGR bait constructs were generated by in vivo recombination in yeast Saccharomyces cerevisiae THY.AP4 3-reporter system. Cloned receptor function was verified by immunofluoresence, western blot analysis and cAMP generation. Cub-TF fused receptors were screened with a tissue-specific human fetal brain and kidney cDNA libraries using MYTH system, revealing 181 novel candidate protein interactors associated primarily with signal transduction, transport, metabolism and cell survival. Each candidate was validated using YTH prey retransformation tests, and some were further confirmed by co-purification in HEK293T mammalian cell line.

5.2 MYTH System The importance of studying GBPs that form GAPCs is illustrated in the fact that virtually all cellular processes are mediated through specific PPI complexes. In the post-genomic era, the next major goal of systems biology is characterization of the entire humane proteome. Of all the genetic and biochemical technologies that have been developed to undertake various genome sequencing projects, the YTH system is the method of choice. While the high incidence of false positives remains a major obstacle of HTP YTH screening, the advantages of this powerful PPI screening tool outweigh the cost of often laborious follow-up experiments required to validate each putative interactor. As well, being aware of the limitations of the YTH assay provides the drive to continually develop better YTH and HTP validation methods. However, despite the great progress made in evolving this technology, thus far, PPI studies have focused on soluble proteins creating a severe underrepresentation of integral membrane proteins due to their hydrophobic nature. Relative to how novel this HTP technology is, the MYTH system has already made significant contributions towards the mapping of human interactomes. Recent advances, including adaptation to a cDNA library-based (Thaminy et al., 2003) and array-based screening format (Miller et al., 2005) have made the system more efficient and easy to use. In the integrated MYTH (iMYTH) system, since baits are endogeonous Cub-TF-tagged open reading frames (ORFs), expression is under the control of its endogenous promoter thus ensuring that the 73

74 protein is expressed at its proper stoichiometric ratio with other protein complexing members which should both limit false positive and eliminate of overexpression artifacts involving posttranslational modifications and localization (Paumi et al., 2007). The so-called “MYTH 2.0” applies serial truncation of a bait protein to pinpoint specific binding domains of receptor proteins (Gisler et al., 2008). The versatility of MYTH system has been proven through its broad applications including identification of novel interacting partners of the yeast ABC transporter Ycf1p (Paumi et al., 2007), and elucidating the novel interactors using components of the Wnt-Frizzled signaling pathways (Dirnberger et al., 2008). In a recent study, five mammalian full-length renal transporters were screened using their PDZ domain binding motifs located in their CT tails (a structural similarity in many integral membrane proteins) to identify novel interacting proteins. In this application of MYTH, the transcription factor moiety was shifted to the NT to permit detection of CT PDZ domain interactions (Gisler et al., 2008). However, a major limitation of the any YTH system is that it is restricted to identifying only binary interactions, leading to an underrepresentation of those proteins which interact only within entire protein complexes. Therefore, pairing the MYTH system with an AP/MS method such as the novel TAP technique, which is capable to capturing the entire protein complex, would provide a more comprehensive tool for characterizing receptor interactomes.

5.3 B class GPRC Interactomes It is now apparent that GPCR signaling is not solely dependent on coupling to heterotrimeric G- proteins, but also determined by additional adaptor proteins which interact directly with GPCRs to facilitate and modulate signal transduction. Previous studies have shown that these GBPs primarily act to regulate GPCR targeting to a specific cellular compartment, its association with other signaling or structural proteins, and the fine-tuning of its signal transduction including desensitization and resensitization. Such studies, however few, include those which look specifically at identifying GBPs and their potential function roles in modulating B-class GPCRs. Interaction with RAMPs has been demonstrated with VPAC1R, PTHR and GCGR and was specifically shown to couple with calcitonin receptor-like receptor (CLR) and related calcitonin receptor (CTR) to yield calcitonin gene related peptide receptor (CGRP), adrenomedullin (AM) or amylin receptors (McLatchie et al., 1998; Sexton et al., 2006). As well, Sneddon et al. (1998) revealed that NHERF1 inhibits the agonist-independent PTHR1 endocytosis while NHERF2 interaction switches PTHR1 signaling from a cAMP-dependent pathway to a PLC-PKC- dependent pathway (Mahon et al., 2002). As summarized in section 3.1.1, GBPs of the glucagon superfamily of receptors also include a similar group of regulatory proteins like β- arrestin, GRK2, caveolin and calmodulin (Mahon and Shimada, 2005; Sonoda et al., 2008;

Syme et al., 2006; Tseng and Zhang, 2000). Interestingly, of the 181 interactors identified from the MYTH screens, none of the GBPs commonly found in the interacomes of all GPCR classes were found, with the exception of calmodulin 1 and 2. As discussed in section 3.1.2, this may be due to the absence of receptor activation or false negatives which may lead to a lack of recruitment or underrepresentation of typical adaptor proteins. However, this lack of consistency with the previous literature may also substantiate the novelty of these protein interactors which could not only further uncover the mechanism of receptor activation leading to activation of downstream signaling pathways but also provide novel therapeutic drug targets.

5.4 Pharmacological Relevance In addition to elucidating unknown protein function, the MYTH technology provides several applications for drug discovery. In this study, I demonstrate the versatility of the YTH method which I have adapted to study a subset of B-class GPCRs, the glucagon superfamily of receptors, which not only embody important physiological targets, but also represent a series of exciting and promising therapeutic drug targets. The most intensively pursued by far in terms of pharmacological development is GLP-1, which presently has more than 10 DPPIV-resistant analogues in clinical trial, the most well-studied of which are exendin-4 and liraglutide which are currently in clinical use. These drugs are not only directed towards reversing diabetes-related pathologies, but studies have shown evidence of other potential pharmacological applications including in enhancing cardiac function following myocardial infarction (Ban et al., 2008), reducing food intake and promoting weight loss in obese patients (Drucker and Nauck, 2006) and slowing the progression of neurodegenerative disorder such as stroke, PD (Li et al., 2009) and AD (Perry and Grieg, 2005). In contrast, the therapeutic potential of GIP has proven quite limited since the response to GIP is markedly attenuated in T2DM patients, and unlike GLP-1, GIP increases glucagon secretion which further worsens the diabetic state (Drucker, 2005). Some recent studies with DPPIV-resistant GIP agonists (e.g. Pro3-GIP) have created hope of an anti-obesity GIP drug (McClean et al., 2007), however a proper understanding of the role of GIP in human adipocyte biology is still far from attempting any clinical trials (McIntosh, 2009). As described previously, pharmacological studies of GLP-2 administration have uncovered several potential applications of restoring small and large bowel growth and function following the intestinal injury seen in various forms of gastrointestinal disease (Estall and Drucker, 2006; L'Heureux and Brubaker, 2001). Strategies aimed at decreasing hepatic glucose production and lowering blood glucose seen in T2DM patients lacking glucagon suppression have led to the pharmacological development of glucagon receptor antagonists. GCGR knockout mice exhibit improved glucose tolerance, resistance to diet-induced obesity, increased levels of GLP- 1, decreased gastric emptying, and resistance to streptozotocin-induced diabetes (Conarello et

76 al., 2007; Gelling et al., 2003). A glucagon receptor antagonist has been tested in a preliminary clinical trial showing positive short-term effects (Peterson and Sullivan, 2001), however little more has been pursued beyond that despite remaining pharmaceutical interest (Djuric et al., 2002). The advantage of using GBPs as drug targets is that they provide a solution to the common pharmacological obstacle of tissue-specificity. Since GBPs differ from cell to cell, depending where the receptor is expressed, this could allow for the design of new pharmacological approaches designed to specifically target the GPCR-GBP interaction in a given tissue without affecting the interaction of the same GPCR with other GBPs in other tissues. Thus, insights gained from my work could reveal novel interactors that transduce cell, tissue or organ-specific actions towards which therapeutic strategies could then be designed to select the desired actions (insulin secretion, islet growth) from undesired actions (cancer growth, pancreatitis) of current glucagon-related receptor drug molecules.

5.5 Function of Novel Interactors – Preliminary Data

The obvious next step is to characterize the function of each of these novel interactors. In an attempt to select out potential protein candidates of interest for further functional studies, a preliminary study was performed where selected interactors identified in the GLP-1R MYTH screens were transiently transfected into a GLP-1R stably expressing Chinese Ovarian Hamster (CHO) cell line and intracellular cAMP accumulation was measured according to the protocol described in section 2.4.8. The cAMP generation assay was chosen since cAMP is the primary signaling pathway triggered by this class of GPCRs. Tetraspanin 13 (TSPAN13), neurogranin (NRGN), progestin adipoQ receptor 6 (PAQR6), and synaptogyrin 3 (SYNGR3) were chosen from the list of GLP-1R prey retransformation positive clones and acquired in full-length cDNA constructs from Openbiosystems (Huntsville, AL, USA). A dose of 5 x 10-11M GLP-1 was chosen as the lowest dose which would elicit a cAMP response in order to avoid saturdation of the expressed receptors. Compared to the empty vector and non-specific control, neuroplastin (NPTN), none of the 4 interactors had a significant effect on intracellular cAMP accumulation (n=4-6) (Figure 22). This result suggests if these interactors regulate GLP-1R function, they may signal through a cAMP-independent pathway. I have yet to test the three candidate interactors (APLP1, CD81, STMN1) that were successfully co-immunoprecipiated. I would suspect that they may likewise trigger downstream signaling pathways that could also be cAMP-independent. Further tests would still need to be performed to confirm this result including pharmacological activation and blockade of AC and testing of other pathways including calcium and protein phosphorylation. This is potentially very exciting as it opens up a

77 whole new spectrum of novel cAMP-independent signaling pathways that could be activated by this class of GPCRs.

Figure 22. Preliminary study showing no effect of selected interactors on cAMP accumulation. Chinese Hamster Ovarian (CHO) cells which stably expressed human GLP-1R was transiently transfected with selected interactor constructs tetraspanin 13 (TSPAN13), neurogranin (NRGN), progestin adipoQ receptor 6 (PAQR6) and synaptogyrin 3 (SYNGR3). Following stimulation of transfected CHO- GLP-1R cells with 5 x 10-11M concentrations of GLP-1 peptide agonist, intracellular cAMP accumulation was measured using a cAMP RIA kit. Both empty vector and a non-specific interactor construct, neuroplastin (NPTN), were used as negative controls.

5.6 Future Directions Future experiments in this project will focus first on the 7 candidates (APH1A, APLP1, CD81, GABBR2, GPR37, HPN, STMN1) discussed in Chapter 4 in the following specific areas:

1. Further validation of all the interactors by co-purification. As there might still be false positives, we will need to do more co-purifications to verify the authentic interactions, including not only binary complexes (two proteins) but higher order complexes (3 or more proteins). There is also the possibility of complex assembly and disassembly of these protein complexes where one protein might negatively or positively influence the binding between two other proteins requiring more complex protein binding studies.

2. Use of qPCR and co-purification to explore native expression and PPI in cell and intestinal cell lines. Heterologous systems have the advantage of being very clean since only defined proteins can be expressed without confounding presence of any other proteins, however, such systems are not physiological. Protein expression and interactions need to be verified as cell- and subcellular (plasma membrane) context- specific. This will require qPCR to detect in low levels of these proteins. Clever co-

immunoprecipitation strategies will have to be devised. If the endogenous proteins are abundant and commercial antibodies are available and of high affinity, then co- immuniopreciipitations could be carried out to show their interactions. In the absence of appropriate antibodies, we could generate antibodies to novel proteins ultimately. Alternatively, we could perform GST-pull downs wherein an exogenously generated protein coupled to a solid support (i.e. sepharose beads) can be used to pull down in greater abundance and limited quantities of the endogenous proteins.

3. Use of Immunofluorescence microscopy to demonstrate co-localization of bait- prey interaction on plasma membrane. In vitro protein binding interactions do not necessarily indicate genuine endogenous interactions. In vivo evidence of such protein interactions should be demonstrated. Confocal microscopy will be used to demonstrate the spatio-temporal relationships of these interacting proteins. Presumably these proteins will already be on the plasma membrane and in particular the GPCR. However, the interactors may be at a different compartment away from the GPCR on the plasma membrane or in the cytosol, and may require stimulation or activation to then translocate to the GPCR. The activation might be specific cellular signals such as calcium, cAMP, PKA or PKC, which could be triggered by specific pharmacological agents. Thus, confocal microscopy with both GPCR and interactomes tagged should be done under basal and stimulated conditions. While this could be facilitated with available polyclonal and monoclonal antibodies, if such are not available, then paired fluoresecent protein tags (GFP, RFP) could be employed. The latter strategy however faces the possibility that GFP tagging on the N- or C-termini of the proteins could interfere with function or binding particularly if those domains are where their function or specific binding are conferred. Furthermore, confocal microscopy demonstration of colocalization of two proteins does not necessarily indicate true in vivo interactions. A more sophisticated method to show in vivo molecular interaction is by FRET analysis of the paired fluorophor-tagged GPCR and interactome, using FRET paired fluorescent proteins (ie. CFP and YFP, or GFP and RFP).

4. Gene knockdown and overexpression of selected interactors. Ultimately, the GPCR-interactome interactions should trigger a physiologically relevant signalling and cell actions. This can be demonstrated by strategies to demonstrate loss of function or gain of function. Nowadays, the most popular inexpensive strategy for loss of function is by gene knockdown using siRNA strategies, and for gain of function by overexpression strategies. The latter however, is not always the best strategy as overexpression could

lead to stoichiometric distortion of proteins forming the multimeric complex which would actually inhibit function rather than promote function. Thus, it would be preferred to perform rescue studies in cell lines in which the novel protein is stably knocked down, and then express the protein to normal levels. The next is to determine which of the putative signaling pathways are activated. While the conventional signaling pathway of this class of GPCR is cAMP, our initially results suggest this to not be the case. Depending on the category of these novel interactomes, we will examine the specific signals that could be triggered (or blocked) by each interactome (calcium generation, protein phosphorylation) and then confirm whether these signals could be blocked by specific pharmacological agents (calcium by BAPTA, phosphorylation by PKA and PKC inhibitors, etc). Furthermore, specific organelle function could be activated including insulin secretion, mitochondrial function, ER stress or cell survival, etc., each of which could be determined by specific assays.

5. Further MYTH screening of a pancreatic islet-specific cDNA prey library. As mentioned, this GPCR-interactome may be cell context specific, and the brain that I had tested might not have been the preferred cell type for such PPI. The islet is the lead tissue or cell(s) type for this class of GPCR, particularly GLP-1R and GIPR, to effect specific cell actions, and hence we will need to confirm the current candidates in islets and further identify other candidates missed with the fetal brain library. The additional novel interactomes in islets may confer the cell-context specific actions (i.e. insulin secretion, beta cell proliferation, etc.).

5.7 Conclusion I have developed a prospective tool for studing B-class GPCRs which may draw further insight into the structural and functional homology of this class of receptors. This work may lead to a greater understanding of the tissue specific functions of each receptor and the discovery of novel, more specific drug targets.

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