The Effect of RGS4 on Autophagic Flux in Min6 Pancreatic Beta Cells

Stephanie Alexandra Beadman

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

Stephanie Alexandra Beadman

Master of Science

Department of Physiology University of Toronto

2015

Abstract

Defective autophagy can lead to dysregulation of metabolic homeostasis. Previous studies in our laboratory have shown that RGS4-overexpressing HEK cells show increased autophagic activity. Herein, we study the potential role of RGS4 as a regulator of autophagy in the Min6 mouse pancreatic beta cell line, via inhibition of Gαi3, an established attenuator of autophagy. Min6 cells exposed to nutrient-deprived conditions undergo autophagic initiation demonstrated by increased expression of autophagy markers. When RGS4-YFP is ectopically expressed in Min6 cells, confocal microscopy imaging revealed colocalization between RGS4-YFP (both wild type and loss-of-function mutants), Gαi3 (RC)-CFP, and autophagy markers including Beclin1-DsRed and Atg12-RFP on intracellular punctae.

Despite its colocalization with known regulators of autophagy, RGS4 was apparently unable to modulate the activity of known mediators and markers of autophagic activity (phospho- p76S6K, LC3 II, phospho-Bcl-2). We conclude that Gαi3 and RGS4 are not major factors in the regulation of autophagic flux in Min6 cells.

Acknowledgements

First, I’d like to thank my supervisor, Dr. Scott Heximer. Scott, I really appreciate the opportunities you’ve given me over the last few years. I learnt a lot about science and the research process from you. Your guidance and encouragement helped me to keep doing experiments even when it seemed that nothing was working, and you pushed me to be a more critical thinker, a skill I will take with me wherever I go. You also (maybe unintentionally) afforded me many chances to do some self-discovery, which was very valuable to me. I’d also like to thank my supervisory committee members, Dr. Gramolini and Dr. Lam. I am grateful for your support and direction on this project. My time in the Heximer lab would not have been the same without the support from the wonderful people in the lab. Thank you Guillaume for your direction and willingness to share your knowledge and experience – and for making time for all my poorly-articulated questions. Thank you Alex, who I will never call Sorana, for your friendship and support, and for being a shoulder to lean on for matters both inside and outside lab. I will visit you in Oxford soon! Thank you Joey for being the most easygoing person in the world and always listening to my rants, or just being there to listen to me think about my project out loud. And thank you Joobin for coming up with creative ways to de-stress; I’m taking “GAP-a-ball” wherever I go. Importantly, I’d like to express my gratitude to my family, who have practically persevered through this degree alongside me. Mom, I’m sorry it took so long to complete this degree and how much stress that caused you, but I’m glad I did it. Thank you for always welcoming me home and always looking out for what is best for me. Dad, thank you for being so supportive and flexible about my schedule; I really appreciate you backing me when it didn’t feel like everyone else did. I also appreciate all the rides to the subway you gave me and your willingness to let me borrow your car sometimes. Jackie, thank you for always being there for me no matter what. You have no idea how much I needed your support sometimes. Thank you for making me think about the role model I was being, and giving me the courage to pursue my dreams. And finally, to my biggest motivator and best friend, Nikhil – thank you for celebrating with me in my triumphs and picking me up so many times when I was down. You were always there when I really needed it – no matter the distance, I knew I could count on you for anything. I can’t wait to start the next chapter of our lives together.

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Table of Contents

General abstract…………………………………………………………………………………………………………………..ii Acknowledgements………………………………………….………………………………………………………………….iii Table of contents…………………………………………………………………………………………………………………iv List of figures……………………………………………………………………………………………………………………….vi List of abbreviations…………………………………………………………………………………………………………..viii 1 Introduction…………………….………………………………………………………………………………………………..1 1.1 Autophagy…………………………………………………………………………………………..….…..……..1 1.1.1 Molecular Machinery of Autophagy…………………………………………………….2 1.1.2 Signaling Pathways that Regulate Autophagy…………..………………………….8 1.1.3 Autophagy is Important for Homeostatic Metabolic Regulation…………10 1.2 G-proteins and their Regulators……………………………………………………….…….………14 1.2.1 The Role of G-protein Signaling in Autophagy..………………….……….……..17 1.2.2 RGS4 is Highly Expressed in Pancreatic Islets…..…………………………………18 1.2.3 RGS4………………………………………………………..…………………………………..……19 1.2.4 RGS4 Attenuates M3 Muscarinic Receptor-Mediated Insulin Secretion in Min6 Cells………………………………………………………………………..………………..20 1.2.5 RGS4-Deficient Mice Show Metabolic Dysfunction and a Chronic Deficiency in Insulin Secretion……………………………………………………………20 1.2.6 The Putative Role for RGS4 as a Regulator of Autophagic Flux……………21 2 Rationale and Objective………….………………………………………………………………………….……………22 3 Hypothesis……………….……………………………………………………………………………………………………..22 4 Materials and Methods………………….……………………………………………………………………..……..…24 4.1 Reagents……………………………………………………………………………………………………..……24 4.2 Min6 Cell Culture and Transient Transfection………………………………………….……….24 4.2.1 Plasmids……………………………………………………………………………………………..24 4.2.2 Min6 Cell Culture and Transient Transfection……………………….……………25 4.3 Confocal Microscopy…………………………………………………………………………………………26 4.4 Western Blotting………………………………………………………………………………………….…..26 4.5 Statistical Analysis…………………………………………………………………………………………….28 5 Results…………………………………………….………………………………………………………………………….....29 5.1 Autophagy Occurs in Min6 Cells……………………………………………………………………….29 5.2 RGS4 Localization Patterns and Colocalization with Gαi3 and Autophagy Markers…………………………………….………………………………………………………………………33 5.2.1 RGS4, Gαi3, and Autophagy Marker Localization in Min6 Cells……………33 5.2.2 Characterization of RGS4 and Autophagy Marker Punctae Distribution and Localization in Min6 Cells………………………….…………………………………38 5.2.3 Characterization of RGS4 and Autophagy Marker Colocalization within Punctae in Min6 Cells…………………………………………………………………………43 5.2.4 Pearson Colocalization Coefficient Analysis………………………………………..47

5.3 RGS4’s Effect on Autophagy Marker Protein Expression……………………………………49 5.3.1 RGS4 and Phospho-p70S6K………………………………………………………………..49 5.3.2 Average Number of Beclin1 Punctae per Cell …………………………………….51 5.3.3 RGS4 and Phospho-Bcl-2……………….…………………………….…………………….53 5.3.4 RGS4 and LC3……………………………………………………………………………………..55 6 Discussion……………………….………………………….…………………………………………………………………..59 6.1 RGS4 Localization in Relation to Autophagosomes in Min6 Cells………………………59 6.2 The Effect of RGS4 on Autophagic Flux in Min6 Cells…………………………………………64 6.3 Conclusions……………………………………………………………….……………………………………..66 6.4 Limitations………………………………………………….…………………………………………………….67 6.5 Future Directions………………………………………………………………………………………………68 7 References……………………………….………………….………………………………………………………………….71 8 Appendix………………………………….……………….…………………………………………………………………….76

List of Figures

1 Introduction Figure 1-1: A schematic representation of the formation of the autophagosomal membrane…………………………………………………………………………………………………….7 Figure 1-2: A schematic diagram of the effects of defective or impaired autophagy on pancreatic beta cells……………………………………………………………………………………13 Figure 1-3: Heterotrimeric G-protein signaling and regulation by RGS proteins….………..16

3 Hypothesis Figure 3-1: A schematic diagram of our hypothesis…………………………………….………………..23

5 Results Figure 5-1: LC3 punctae counts show that autophagy occurs in Min6 cells ….………………31 Figure 5-2: pEYFP-transfected Min6 cells undergo autophagy when starved ……..………..32 Figure 5-3: Representative images showing RGS4 localization in Min6 cells……….…………35 Figure 5-4: Representative images of confocal microscopy photos of Beclin1-DsRed- expressing Min6 cells………………………………………………………………………….………36 Figure 5-5: Representative images of confocal microscopy photos of Atg12-RFP- expressing Min6 cells……………………………………………………………………….…………37 Figure 5-6: Punctae distribution in cells with punctae……………………………………………….….41 Figure 5-7: Punctae distribution in all cells……………………………………………………………….…..42 Figure 5-8: Colocalized punctae counts…………………………………………………………………………45 (a) Average number of RGS4 and Beclin1 colocalized punctae per cell (b) Average number of RGS4 and Gαi3 colocalized punctae per cell (c) Average number of Gαi3 and Beclin1 colocalized punctae per cell Figure 5-9: Pearson colocalization coefficient values for punctae of cells overexpressing an RGS4 construct and Beclin1…………………………………………………………..……….48 Figure 5-10: RGS4 overexpression does not change phospho-p70S6K protein expression levels significantly……………………………………………………………………….……………...50 Figure 5-11: Average number of Beclin1 punctae per cell……………………………………………….52 Figure 5-12: The effect of RGS4 and starvation on phospho-Bcl-2 protein expression in Min6 cells…………………………………………………………………………..……………………….54 Figure 5-13: LC3 II protein expression in fed Min6 cells………………………………………..………..57 (a) LC3 II protein expression in fed Min6 cells overexpressing RGS4 constructs, with and without bafilomycin A1 treatment (b) The effect of bafilomycin A1 on LC3 II protein expression in fed Min6 cells

Figure 5-14: LC3 II protein expression in starved Min6 cells…………………………………….……..58 (a) LC3 II protein expression in starved Min6 cells overexpressing RGS4 constructs, with and without bafilomycin A1 treatment (b) The effect of bafilomycin A1 on LC3 II protein expression in starved Min6 cells

Appendix Figure A-1: The effect of glucose concentration in Min6 medium on phospho-p70S6K protein expression when RGS4 WT or ENAA is overexpressed……………….……76 Figure A-2: No crosstalk of eGFP (488nm), DsRed (543nm) or DAPI (405nm) fluorescence occurred……………………………………………………………………………………………………..77

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List of Abbreviations

4E-BP1 Eukaryotic translation initiation factor 4E-binding protein 1 AGS3 Activator of G-protein signaling 3 AMP Adenosine monophosphate AMPK Adenosine monophosphate kinase Atg Autophagy-related protein ATP Adenosine triphosphate Baf Bafilomycin A1 Bcl-2 B-cell lymphoma 2 Bif-1 BAX-interacting factor 1 cAMP Cyclic adenosine monophosphate CCK Cholecystokinin CFP Cyan fluorescent protein CNS Central nervous system C-terminus Carboxy-terminus DAG Diacylglycerol ER Endoplasmic reticulum ERK Extracellular signal-regulated kinase FIP200 Focal adhesion kinase family interacting protein of 200 kDa

Gα12/13 G-protein involved in Rho family GTPase signaling

Gαi Inhibitory G-protein

Gαo G-protein causing “other” effects

Gαq Phospholipase C-activating G-protein

Gαs Stimulatory G-protein GAIP Gα-interacting protein GAP GTPase activating protein GDP Guanine diphosphate GEF Guanine exchange factor GIV Gα-interacting vesicle-associated protein GPCR G-protein-coupled receptor GSIS Glucose-stimulated insulin secretion GTP Guanine triphosphate HEK Human embryonic kidney HMGB1 High mobility group box 1

IP3 Inositol-1,4,5-trisphosphate IR Insulin receptor IRS-1 Insulin receptor substrate 1 Jnk1 c-Jun N-terminal kinase 1 kDa KiloDalton LAMP Lysosomal-associated membrane protein LC3 Microtubule-associated protein 1A/1B – light chain 3 M3 receptor Muscarinic acetylcholine 3 receptor mTOR Mammalian target of rapamycin

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mTORC1 Mammalian target of rapamycin complex 1 mTORC2 Mammalian target of rapamycin complex 2 N-terminus Amino-terminus NBR1 Neighbor of BRCA1 gene 1 p62 Nucleoporin 62 p70S6K p70 ribosomal protein S6 kinase PCC Pearson colocalization coefficient PE Phosphatidylethanolamine PERK ER stress-induced protein kinase PI Phosphatidylinositol PI3K Phosphoinositide 3-kinase PI3P Phosphatidyl inositol triphosphate

PIP2 Phosphatidylinositol 4,5-bisphosphate PLC Phospholipase C PTX Pertussis toxin RFP Red fluorescent protein RGS Regulator of G-protein signaling siRNA Small interfering RNA SQSTSM1 Sequestosome 1 TSC Tuberous sclerosis protein ULK1 Unc-51 like autophagy activating kinase 1 WT Wild type YFP Yellow fluorescent protein

1 Introduction

1.1 Autophagy

Autophagy (Greek origin: auto-, “self” and –phagein, “to eat”) is a normal catabolic process that involves intracellular degradation of unnecessary or dysfunctional cellular components. This recycling process occurs at a basal level in almost all cells of the body in order to maintain homeostasis; it plays a housekeeping role to remove misfolded or aggregated proteins, disposes of damaged organelles, and eliminates pathogens. However, during times of cellular stress, for example during glucose or amino acid starvation, autophagy is increased in order to maintain cellular energy levels and promote survival (1;

2). For this reason, autophagy is an important process in the regulation of cellular metabolism.

Autophagy is often considered to be a survival mechanism but in some cases, autophagy promotes cell death and morbidity (3). Autophagy can be selective or non- selective in the organelles and proteins that are chosen to be degraded. In addition to generally promoting survival during times of stress, autophagy promotes cellular senescence, cell surface antigen presentation, and prevents necrosis, making it a useful tool in the prevention of diseases such as cancer, neurodegeneration, cardiomyopathy, diabetes, liver disease, autoimmune diseases, and infection (2).

There are three commonly defined types of autophagy: macroautophagy, microautophagy, and chaperone-mediated autophagy. Macroautophagy is the main pathway; cytoplasmic cargo (damaged organelles or unused proteins) is delivered to the lysosome upon being encapsulated in a double membrane-bound vesicle called an autophagosome. The autophagosome fuses with the lysosome to form an autolysosome, and cargo is degraded via acidic lysosomal hydrolases. By contrast, cytoplasmic content is

directly engulfed by the lysosome in microautophagy. During this process, the lysosomal membrane invaginates to accept the cargo. Chaperone-mediated autophagy is the pathway of autophagy that has been least elucidated and is very complex and specific. Chaperone proteins such as Hsp-70 drive this pathway; cytosolic components that are tagged with a chaperone protein are recognized by lysosomal-associated membrane protein 2A (LAMP-

2A), resulting in unfolding of the protein and translocation across the lysosomal membrane to be degraded. Chaperone-mediated autophagy is very different from macroautophagy and microautophagy because the lysosome accepts proteins in a one-by-one manner and will only accept proteins that have been tagged with a chaperone to cross the lysosomal barrier (2; 4; 5). Due to recent increased interest and a large body of literature supporting the process, macroautophagy will be of particular importance to this thesis, henceforth referred to as “autophagy.”

1.1.1 Molecular Machinery of Autophagy

Autophagy begins when an isolation membrane (also known as a phagophore) is formed. The source of this membrane is not completely understood, and may be context specific, however it has been hypothesized to be a lipid bilayer pinched off from the endoplasmic reticulum (ER), trans-Golgi network, plasma membrane or mitochondrion. The isolation membrane engulfs cytoplasmic cargo, sequestering it into a closed double-walled membrane termed an autophagosome. The autophagosome fuses with a lysosome, allowing the lysosomal hydrolases to degrade its contents. Amino acids are produced, and lysosomal permeases and transporters allow them to travel back into the cytoplasm, where they can be used in the translation process to produce other proteins or can be shuttled into the citric acid cycle. This amino acid recycling process, which also results in the

production of ATP, is important in the basal state and under conditions of cellular stress to maintain cellular metabolic homeostasis (2; 4-6). The orchestration of this entire process can be divided into five important steps: 1) phagophore formation, 2) Atg5-Atg12 conjugation and interaction with Atg16, 3) LC3 maturation and insertion into the phagophore membrane, 4) recruitment of cargo for degradation, and 5) fusion of the autophagosome to the lysosome.

1) Phagophore formation

The source and mechanism of the phagophore membrane’s formation hasn’t fully been elucidated yet. The double-membraned phagophore seems to initiate chiefly from the

ER (7) but the trans-Golgi network (8), late endosomes (9), and the nuclear envelope (under restricted conditions) may possibly contribute to its formation (10). There is also a school of thought that due to the lack of transmembrane proteins in autophagosomal membranes, it is possible that there is a de novo membrane formation intracellularly (2). The Unc-51-like kinase 1 (ULK1) protein (a mammalian homolog of autophagy-related (Atg) protein 1 in yeast) localizes to the phagophore upon starvation when it complexes with Atg13 and the focal adhesion kinase family-interacting protein of 200 kDa (FIP200) (5). This stable complex assists in the maturation of the phagophore. It has been suggested that ULK1 phosphorylates both Atg13 and FIP200 as well as autophosphorylates in order to induce autophagy (11; 12).

Vps34 (vesicular protein sorting 34) is a member of the class III PI3K family and complexes with Beclin1 (a mammalian homolog of Atg6 in yeast) among other regulatory proteins. When not associated with Beclin1, Vps34 assists with various membrane-sorting processes in the cell, but when complexed with Beclin1, Vps34 uses phosphatidylinositol

(PI) as a substrate to produce phosphatidyl inositol triphosphate (PI3P)(13). PI3P recruits

other Atg proteins such as Atg2, Atg9, and Atg18 to the phagophore membrane, a crucial process for membrane elongation (14). Beclin1 regulates Vps34’s catalytic activity and the production of PI3P is increased during times of starvation. The regulation of the Vps34-

Beclin1 interaction during starvation has not been fully elucidated (15). The other regulatory proteins that associate with the Vps34-Beclin1 complex can either promote or inhibit autophagy. UVRAG, BAX-interacting factor-1 (Bif-1), Atg14, Ambra1, and the Vps34 regulatory kinase Vps15 all assist in the induction of autophagy (16-20), while Rubicon and

B-cell lymphoma 2 (Bcl-2) proteins impede autophagy (21). Bcl-2 disrupts the interaction of

Beclin1 with Vps34 but this inhibition can be prevented if c-Jun N-terminal kinase 1 (Jnk1) phosphorylates Bcl-2 in response to starvation-induced signaling – allowing autophagy to advance (22-24).

2) Atg5-Atg12 conjugation and interaction with Atg16

The Atg5-Atg12-Atg16 complex in unity with LC3 (see below) is vital for the formation of the autophagosome. To initiate the formation of the complex, Atg5 binds to the C-terminal glycine residue of Atg12 with the assistance of ATP and Atg7. Atg12 is transferred to Atg10, which potentiates the linkage of Atg12 to Atg5. The Atg5-Atg12 complex binds in pairs to Atg16 dimers, forming the final Atg5-Atg12-Atg16 complex. This complex assists in the elongation and importantly, the curvature of the phagophore. Atg5-

Atg12 complexes are formed even when autophagy is not occurring, and once the autophagosome is fully formed, the Atg5-Atg12-Atg16 complex detaches from the membrane, making these proteins poor markers for autophagy (4; 5; 25).

3) LC3 maturation and insertion into the phagophore membrane

The microtubule-associated light chain 3 (LC3B or simply LC3) is the mammalian homolog of Atg8 in yeast. When autophagy is induced, the cysteine protease Atg4 cleaves the C-terminal end of the LC3 protein, exposing a glycine residue, producing a variant of LC3 called LC3-I. The exposed glycine residue is activated by Atg7 similarly to the activation of

Atg12 by Atg7 (see above) and LC3-I is transferred to Atg3, which potentiates the linkage of phosphatidylethanolamine (PE) to the exposed glycine residue. This PE addition to LC3-I allows the protein to become a fully processed LC3-II protein. The Atg5-Atg12-Atg16 complex assists LC3-II to localize to both the internal and external membranes of the phagophore, where it is able to control the size of the autophagosome, determine membrane curvature, assist with hemifusion of the autophagosomal membrane to the lysosomal membrane, and select cargo for degradation (2; 5; 26).

4) Recruitment of cargo for degradation

Recent evidence indicates that the protein p62/sequestosome 1 (SQSTM1) has the ability to select which proteins and substrates will be degraded by autophagy. p62 directly binds both mono- or poly-ubiquitin and LC3-II, recruiting cargo to the autophagosome (27).

In a similar manner to p62, neighbor of BRCA1 gene 1 (NBR1) interacts with both ubiquitinated proteins and LC3-II, sequestering the proteins to the autophagosome. NBR1 and p62 can interact and form oligomers, but can also function independently (28).

5) Fusion of the autophagosome to the lysosome

Once the autophagosome is fully formed and both ends are fused, the autophagosome can fuse with a lysosome to form the autolysosome. It is postulated that prior to lysosomal fusion, the autophagosome can also fuse with early and late endosomes.

These endosomes are thought to deliver more cargo to the autophagosome and lower the pH of the autophagosome before it fuses with the highly acidic lysosome (29). The cytoskeleton assists in the process of autophagosome-lysosomal fusion; however, the mechanisms for its role in the process are unknown (30). The lysosome contains cathepsin proteases B and D which aid in the maturation of the autolysosome (31). The LAMP proteins 1 and 2 on the membrane of the lysosome are also crucial for the completion of autophagy, since when they are deleted in mice, autolysosomes were unable to mature

(32). All proteins inside the autolysosome are degraded, including LC3-II proteins that were tethered to the inner autophagosomal membrane. Atg4 assists in the dissociation of LC3-II proteins tethered to the outer autophagosomal membrane, which can remain in the cytosol to be reused (33). Amino acids are recycled to the cytosol for future protein and ATP production (34). See Figure 1-1 for a schematic representation of steps 1-5.

Bcl-2

Bafilomycin A1

mTOR

P70S6K

Figure 1-1: A schematic representation of the formation of the autophagosomal membrane. Autophagy begins with the formation of a double membrane around intracellular “cargo” to be degraded. Four main groups of autophagy-related proteins are required for this process to occur: 1) the ULK1 protein-kinase complex, 2) the VPS34-Beclin1 class III PI3-kinase complex, 3) the Atg9-Atg2-Atg18 complex, and 4) the Atg5-Atg12-Atg16 and LC3 conjugation systems. The ULK1 protein-kinase complex is responsible for the maturation of the autophagosome and inhibition of this complex by mTOR inhibits autophagy. The VPS34-Beclin1 class III PI3-kinase complex and the Atg9-Atg2-Atg18 complexes work together to promote autophagosomal membrane elongation; Beclin-1 can be inhibited by Bcl-2. The Atg5-Atg16-Atg12 complex assists with membrane elongation and importantly, the curvature of the autophagosomal membrane. Once formed and loaded with cargo, the autophagosome can fuse with a lysosome to become an autolysosome and cargo can be degraded and recycled to the cytosol for future protein production. See text for more details. Figure modified from Ding et al., Exp Biol Med, 2011 (35).

1.1.2 Signaling Pathways that Regulate Autophagy

Although autophagy is constitutively active at a basal level in most cell types, it is strongly induced by many factors, which include nutrient deprivation and hypoxia. One of the major contributors to increasing autophagy is the mammalian Target of Rapamycin

(mTOR) serine/threonine protein kinase. mTOR is a master regulator of cellular metabolism and has been shown to regulate cell growth, cell proliferation, cell motility, cell survival, and protein synthesis and transcription through its ability to sense cellular nutrient, oxygen, and energy levels (36). The mTOR pathway is dysregulated in many diseases including diabetes and obesity (37).

mTOR is the catalytic subunit of two independent and structurally different complexes, mTORC1 and mTORC2. mTORC1 consists of mTOR, regulatory-associated protein of mTOR (Raptor), MSLT8, and two other non-core components. mTORC1 acts as a nutrient/energy sensor and controls protein synthesis (38). An important pathway to consider is the insulin receptor (IR) pathway that ultimately leads to the activation of mTORC1. When the IR is activated, it activates the IRS-1, which acts on PI3K, resulting in

Akt activation. Akt inhibits TSC1/2, which inhibits mTORC1. mTORC1 in turn inhibits autophagy and although the mechanism isn’t clear in mammalian cells, in yeast, mTORC1 phosphorylates Atg13, preventing it from interacting with Atg1 (the mammalian homolog is

ULK1). Therefore, in the presence of insulin (i.e. the fed state, a growth-promoting condition), autophagy is suppressed (39). Under low-energy conditions, mTOR is suppressed; the AMP/ATP ratio rises and activates AMP kinase (AMPK). AMPK phosphorylates TSC2, activating it, and mTOR is inhibited, allowing autophagy to occur (40). mTOR can be pharmaceutically inhibited by treatment of cells with rapamycin (which has inhibitory activity against mTORC1) (41).

mTOR has downstream signaling effectors which can be used to determine autophagic flux. The best characterized pathway through which mTOR acts results in the phosphorylation of p70S6K, a serine/threonine kinase that is one of the main effectors of the PI3K pathway (42). mTOR also phosphorylates and thus activates eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1), which inhibits cap-dependent mRNA translation by binding eukaryotic initiation factor 4E (43). Such marked inhibition of cellular translation may also result in the reduced synthesis of autophagy-specific proteins (43).

Important to this thesis is mTOR’s role with p70S6K; upon mTOR activation, a resultant increase in p70S6K phosphorylation (producing phospho-p70S6K) and thus activation is seen. In turn, the activated phospho-p70S6K phosphorylates the ribosomal S6 protein, a component of the 40S ribosomal subunit, enabling cellular translation. Measuring expression of phosphorylated p70S6K is an indicator of increased mTOR activity and thus decreased autophagic activity (44).

Although less commonly examined in the literature, there are pathways downstream of mTOR that regulate autophagy. Beclin1 has been shown to interact with the anti-apoptotic Bcl-2 family of proteins via its Bcl-2 homology 3 (BH3) domain, preventing Beclin1 from assembling the pre-autophagosomal formation complex with

Vps34 (45). Cellular localization of the Beclin1-Bcl2 complex is an important factor in Bcl2 regulation of autophagic flux; only Beclin1-Bcl2 localized to the ER can result in inhibition of autophagy. Nutrient-deprivation autophagy factor-1 binds Bcl-2 at the ER independent of its BH3 domain and is required for Bcl-2 to inhibit Beclin1 (22).

Dissociation of the Beclin1-Bcl2 complex occurs via various mechanisms. Proteins such as high mobility group box 1 protein (HMGB1) and Bnip3 induce autophagy by competing with Bcl-2 for Beclin1. HMGB1 competes with Bcl-2 for interaction with Beclin1

and orients Beclin1 to autophagosomes (46). Bnip3 is capable of binding to Bcl-2 via its BH3 domain, thereby disrupting the interaction between Bcl-2 and Beclin1, inducing autophagy

(47). Regulation of phosphorylation of Bcl-2 is another mechanism through which autophagic flux can be controlled, and Jnk1 activation induces phosphorylation of Bcl-2, causing it to dissociate from Beclin1 and allowing autophagy to occur (24). This pathway to inhibit Bcl-2 is the most commonly studied in the literature. Jnk1 can be activated by numerous events within the cell, including during ER stress or through G-protein signaling;

IRE1, activated during the unfolded protein response, directly activates Jnk1 (48), and Gαs activation results in Jnk1 phosphorylation through the actions of adenylate cyclase and PKA

(49). Death-associated protein kinase has a similar role to Jnk1; it is able to phosphorylate a threonine within the BH3 domain of Beclin1, forcing dissociation of Bcl-2 and thus activation of Beclin1 (50).

1.1.3 Autophagy is Important for Homeostatic Metabolic Regulation

Due to its powerful role in metabolic homeostasis and as an adaptive catabolic process, dysregulation of autophagy can contribute to the development of metabolic disorders including insulin resistance, diabetes mellitus, and obesity. Several groups have explored the link between autophagy and conditions that would challenge the autophagic adaptive response such as obesity or insulin resistance.

In a novel study by the Hotamisligil lab, loss of autophagy was shown to be an important component of impaired insulin action seen in obesity. In both genetic (ob/ob mice) and dietary (high fat diet-fed mice) models of obesity, a severe downregulation of autophagy was observed in the liver. Expression of autophagy markers Atg7, Beclin1, Atg5,

and LC3 II were found to be decreased. This impairment of autophagy corresponded to defective insulin signaling and increased ER stress. In ob/ob mice with an Atg7 knockdown, restoration of Atg7 expression in the liver resulted in decreased ER stress, increased insulin action, and increased systemic glucose tolerance. In order to determine whether the impact of Atg7 in enhancing insulin action in the mice may be independent of autophagic flux, autophagy was blocked using a downstream mediator of autophagy, Atg5. Atg5 completely blocked the beneficial action of Atg7 restoration in the ob/ob mice, proving the importance of autophagy in insulin action in the liver (51).

The insulin-secreting pancreatic beta cell is tuned to metabolic regulation as it senses blood glucose levels and secretes insulin as required, making the study of autophagy in these cells important (see Figure 1-2). Mitochondrial dysfunction in beta cells can play a role in the development of diabetes. The mitochondria is essential for cellular respiration and the production of ATP, which ultimately leads to insulin secretion. Autophagy maintains cellular homeostasis through the degradation and recycling of organelles such as mitochondria. When autophagy was inhibited by deleting the Atg7 gene, Atg7-mutant mice were shown to have reduced beta cell mass and pancreatic insulin content, and were hyperglycemic. In the beta cells that remained, mitochondria appeared swollen and there were other ultrastructural changes (52). These results indicate that autophagy is crucial to maintain the structure and function of beta cells including their ability to secrete insulin. It is important to note that studies have shown that mice with deficiencies in beta cell-specific autophagy show reduced beta cell mass and defects in insulin secretion that lead to hyperglycemia, but these mice do not have diabetes. However, when these mice are bred with ob/ob mice, the offspring develop diabetes, suggesting that autophagy-deficient beta cells struggle to compensate when increased metabolic stress is imposed by obesity (53).

In metabolic disease, the role of autophagic flux has been widely studied in relation to disease pathogenesis. In 2007, Kaniuk et al. published that ubiquitinated protein aggregates were formed in beta cells during oxidative stress in hyperglycemic animal models, and that normal autophagic activity may be required to remove them (54).

Consistent with these observations, Masini et al. (2009) showed that autophagy is also increased in beta cells derived from human subjects with type 2 diabetes (55). These studies have sparked a large body of literature to examine the putative protective role of autophagy in the prevention of diabetes.

ER stress caused by high levels of circulating free fatty acids, accumulation of misfolded proteins, and insulin resistance in beta cells can also contribute to a decrease in insulin secretion, since the ER is the site for insulin biosynthesis (56). It is known that autophagy is activated in response to ER stress in an effort to preserve the cell and not have the cell undergo apoptosis; however the exact role of autophagy and intracellular signaling pathways in ER stress remain to be elucidated. It has been reported that the conversion of

LC3-I to LC3-II is mediated by ER stress-induced protein kinase (PERK) phosphorylation (57).

In an effort to alleviate ER stress, autophagy can degrade and recycle stress-inducing fatty acids and misfolded proteins.

β cell

Functional Defective or Autophagy Impaired Autophagy

Recycling of unused or Toxic aggregates and damaged proteins and degenerative changes organelles

Impaired insulin

Maintenance of secretion and obesity normal metabolic homeostasis Diabetes Cell survival

Figure 1-2: A schematic diagram of the effects of defective or impaired autophagy on pancreatic beta cells. Stress can result in the formation of toxic aggregates in the β cell, which can lead to degenerative changes within the cell. Cell death may ensue, and insulin secretion decreases. This decrease in insulin secretion can cause the liver to increase glucose production, leading to obesity. The obesity phenotype may lead to diabetes, as obesity may cause insulin resistance. However, when functional autophagy occurs in the β cell, unused “cargo” such as damaged proteins or organelles can be recycled to provide energy for the cell and allow β cell survival.

1.2 G-Proteins and their Regulators

G-protein-coupled receptors (GPCRs) are a large family of receptors that can activate signal transduction pathways inside the cell upon ligand binding. As the name suggests, G- proteins that are intracellularly-coupled to the receptor initiate the intracellular signal transduction. There are three subunits that make up the heterotrimeric G-protein complex:

α, β, and ɣ subunits. The Gα subunit has intrinsic GTPase activity and may activate downstream effector molecules in its activated state. The Gβɣ heterodimer is responsible for activation of effector molecules when it is not bound to activated Gα (58-60). There are different types of Gα proteins; some examples include the Gαs subunit (stimulatory effects),

Gαi subunit (inhibitory effects), Gαq subunit (specifically activates PLC, resulting in cleavage of PIP2 to DAG and IP3), Gαo subunit (“other” effects), and Gα12/13 subunit (regulates actin cytoskeleton) (58-60).

When the Gα subunit is bound to GDP, it associates with the Gβɣ heterodimer to form a heterotrimeric complex. When an extracellular ligand binds to the GPCR-G-protein complex, a conformational change occurs such that the receptor acts as a guanine nucleotide exchange factor (GEF) for Gα, promoting the exchange of GDP for GTP. The Gα subunit is now active and can activate downstream effectors such as adenylyl cyclase, PLC, guanylyl cyclase, etc. This process often generates secondary messengers such as cAMP,

IP3, DAG, etc. When the GTP on the Gα subunit is hydrolyzed to GDP, the Gα subunit will reassociate with the Gβɣ dimer (58-60). G-proteins also shuttle rapidly between the plasma membrane and intracellular membranes such as endosomes, the Golgi complex, etc. This can result in a large pool of intracellular G-proteins as they are not stably constrained to the plasma membrane (61).

The intrinsic rate of GTP hydrolysis in vitro is less rapid than that found in vivo.

Regulator of G-protein signaling (RGS) proteins have GTPase-activating protein (GAP) activity and increase the rate of GTP hydrolysis of the Gα subunit; they are therefore potent inhibitors of heterotrimeric G-proteins (62; 63). RGS proteins are a mammalian family of more than 35 GAPs for the Gα subunit. The RGS family shares a 120-130 amino acid domain called the RGS domain that binds directly to the Gα protein to enhance its GAP activity by up to 2000 fold over baseline activity. This decreased GAP activity results in a decrease in both Gα and Gβɣ downstream signaling. RGS proteins themselves are also highly regulated by alterations in their expression levels, subcellular localization, post-translational modifications, and binding partners (64; 65). See Figure 1-3 for a schematic representation of the function of RGS proteins and GPCR signaling.

The RGS superfamily has been divided into six subfamilies based on sequence homology within the 120-130 amino acid RGS domain. These are the A/RZ (RGS17, 19

(GAIP), 20), B/R4 (RGS1-5, 8, 13, 16, 18, 21), C/R7 (RGS6, 7, 9, 11), D/R12 (RGS10, 12, 14),

E/RA (Axin, Conductin), and F/RL (RGS-like proteins including RhoGEFs, GRKs, AKAPs, and sorting nexins (SNXs)) subfamilies. The A/RZ and B/R4 subfamilies are small proteins of approximately 20-30 kDa and have a short N-terminal and C-terminal domains. The C/R7,

D/R12, E/RA, and F/RL subfamilies are larger (up to 160 kDa) and contain other domains that assist the signaling process (66).

Figure 1-3: Heterotrimeric G-protein signaling and regulation by RGS proteins. The exchange of GDP for GTP on the α-subunit results in the dissociation of the Gβɣ heterodimer. Both the Gα and Gβɣ subunits are now in the “on” state and are able to activate downstream effectors such as adenylyl cyclase, PLC, guanylyl cyclase, etc. When GTP is hydrolyzed to GDP, the Gα subunit can reassociate with the Gβɣ subunit to produce the inactive form of the heterotrimer. RGS proteins are GTPase-activating proteins that inhibit downstream signaling in two ways: 1) they rapidly turn off G-protein signaling by speeding up hydrolysis of GTP to GDP, and 2) they can bind the activated Gα subunit and inhibit downstream effectors.

1.2.1 The Role of G-Protein Signaling in Autophagy

Autophagy is sensitive to many stimuli since it is a metabolic process that needs to be regulated as chemical processes change within the cell. The first results showing the importance of G-proteins in the initiation of autophagy demonstrated that non- hydrolysable analogs of G-proteins (i.e. G-proteins that were always “ON”) inhibited autophagosome formation in rat hepatocytes (67). This study influenced the Codogno lab to examine both Gαi2 and Gαi3 in human colon cancer cells, and they found that autophagy was only stimulated when Gαi3 was GDP-bound, in an inactive state. Gαi2 knockdown did not alter the rate of autophagy in the HT-29 cells, but knocking down Gαi3 resulted in inhibited autophagic sequestration. Furthermore, transfecting the HT-29 cells with a mutant of Gαi3 that is restricted to the GTP-bound form, Q204L, caused arrested autophagy in the cells, highlighting the importance of Gαi3 in the regulation of autophagy (68).

The same group showed that GAIP/RGS19 regulates the guanine nucleotide activity of the intracellular pool of Gαi3 proteins and that by accelerating the rate of hydrolysis, GAIP is able to increase autophagic activity in HT-29 cells. Gαi3 localizes to both the plasma membrane of the cell (when it is associated with a GPCR), but also to an intracellular pool.

This pool preferentially colocalizes with the Golgi complex but can be found with the ER membrane as well. GAIP localizes to these intracellular pools too (69). Similarly to GAIP,

AGS3, a G-protein regulator that stabilizes the GDP-bound conformation of the α-subunit of the Gαi protein, was shown to interact with Gαi3 in the HT-29 cell line and plays a part in the

Gαi3-dependent control of autophagy, increasing autophagic sequestration (70).

Additionally, Garcia-Marcos et al. examined the interaction between AGS3 and Gαi3 in HeLa cells and showed that AGS3 directly binds LC3 and recruits Gαi3 to LC3-containing membranes upon starvation in addition to inhibiting Gαi3. Conversely, Gα-interacting,

vesicle-associated protein (GIV), a guanine nucleotide exchange factor for Gαi3, disrupts the

Gαi3-AGS3 complex, releasing Gαi3 from LC3-containing membranes, and inhibits autophagy by activating Gαi3. Garcia-Marcos et al. found that Gαi3 is able to enhance anti-autophagic signaling by altering mTOR activity (71).

Gαi3 also has anti-autophagic activity in the liver when GTP-bound. Gαi3 localizes not only to the plasma membrane, but also to membranes of autophagosomal compartments; when insulin is present, however, Gαi3 is redeployed away from autophagosomes, indicating a different role for Gαi3 when GTP-bound. The inhibitory action of insulin on autophagy is almost completely lost in the absence of Gαi3 or when Gαi3 is inhibited by pertussis toxin

(PTX), suggesting an essential function for Gαi3 on autophagosomal membranes (72).

Hypothetically, RGS proteins that can inhibit Gαi3 would be able to stimulate autophagy in these hepatic cells, but this hypothesis has yet to be tested.

1.2.2 RGS4 is Highly Expressed in Pancreatic Islets

The pancreas produces a wide number of hormones that regulate metabolism and glucose homeostasis. Many of the known RGS proteins have been shown to be expressed in the pancreas as well as in pancreatic cell lines. In the human pancreas, RGS expression has been studied in both the exocrine glandular cells and the islets of Langerhans. Studies of human exocrine cells showed expression of several RGS proteins, including RGS1, RGS2,

RGS3, RGS4, RGS6, RGS7, RGS10, RGS11, RGS13, RGS14, RGS16, RGS17, RGS18, RGS19,

RGS21, and RGS22 ((62) and Human Protein Atlas, http://www.proteinatlas.org/). Human pancreatic islets were shown to express a slightly different array of RGS proteins, including

RGS3, RGS4, RGS5, RGS6, RGS7, RGS10, RGS11, RGS17, RGS18, and RGS19 (Human Protein

Atlas). RGS8 and RGS16 have been shown to be expressed in embryonic, neonatal, and mouse weanling endocrine pancreas, but their expression decreased in adulthood (73). The potential physiologic importance of RGS proteins in the pancreas has been examined using

RGS-insensitive G-protein knock-ins, or specific RGS protein knockout/down in cultured cells and intact mouse models. Of particular importance to this work, RGS4 is expressed at relatively high levels in the islets of Langerhans. Consistent with its possible role as a physiologic regulator of insulin secretion from pancreatic beta cells, Ruiz de Azua and colleagues demonstrated that the mouse pancreatic beta cell line, Min6, expressed RGS4 mRNA at a higher level than that of any other RGS protein (74).

1.2.3 RGS4

RGS4, the focus of this project, is part of the B/R4 subfamily of RGS proteins and acts as a GAP for Gαi, Gαo, and Gαq families of G-proteins. RGS4 has not been shown to interact with and inhibit Gαs proteins. In humans, it is expressed primarily in the CNS and the heart but is also expressed in other cell and tissue types, such as the pancreas and adrenal cortex

((75), Human Protein Atlas). RGS4 contains a 33 amino acid-long N-terminus with 2 palmitoylatable cysteine residues (Cys2 and Cys12) and an amphipathic helix that allow it to interact with lipid bilayers, thus aiding its G-protein inhibitory capability (76-78). RGS4’s intracellular localization is differentially influenced by palmitoylation at cysteine residues 2 and 12. While it is normally found localized to both the plasma membrane and intracellular endosome-like pools within the cell, when cysteine 2 was mutated to an alanine (RGS4

C2A), RGS4 was unable to localize to the intracellular endosome-like pool. Likewise, when

RGS4’s cysteine 12 was mutated to an alanine (RGS4 C12A), RGS4 showed a markedly decreased association with the plasma membrane (79).

1.2.4 RGS4 Attenuates M3 Muscarinic Receptor-Mediated Insulin Secretion in Min6 Cells

It is known that M3 muscarinic receptors can promote insulin secretion from pancreatic beta cells (80). Notably, upon siRNA-mediated knockdown of RGS4 in Min6 cells, increased glucose-stimulated insulin secretion (GSIS) and calcium release were observed following activation of the muscarinic acetylcholine 3 (M3) receptor, a Gαq-coupled plasma membrane associated GPCR. When pancreatic islets from beta-cell specific RGS4 knockout mice were tested, similar observations were made. However, decreasing RGS4 expression and activating GPCRs other than the M3 receptor led to very little change in insulin secretion in vitro. In vivo, RGS4 knockout mice had increased plasma insulin and decreased blood glucose levels when treated with pharmacologic doses of a muscarinic agonist. It was confirmed that this was an M3 receptor effect with beta cell-specific M3 receptor knockout mice (74). Together, these data are consistent with the notion that RGS4 can inhibit acute

M3 muscarinic receptor mediated insulin secretion by attenuating Gq signals at the plasma membrane.

1.2.5 RGS4-Deficient Mice Show Metabolic Dysfunction and a Chronic Deficiency in Insulin

Secretion

In contrast to the data above suggesting that loss of RGS4 may promote increased insulin secretion, Iankova et al., (2008) showed that RGS4 knockout mice had increased catecholamines and fatty acids in the circulation, a higher glucose intolerance, and decreased insulin secretion compared to wild type controls. RGS4 was proposed to modulate adipose lipolysis by regulating catecholamine secretion from the adrenal glands

(81). Although catecholamines stimulate adrenergic receptors α2 and β2, which inhibit

insulin secretion in the pancreas (82), the precise mechanisms for the changes in insulin secretion were not fully elucidated in these studies.

1.2.6 The Putative Role for RGS4 as a Regulator of Autophagic Flux

Unpublished data from our lab shows that RGS4 can be a potent regulator of autophagy in mammalian cells via its ability to inhibit Gαi3 within intracellular membrane pools. In an LC3-RFP stable HEK cell line, expression of RGS4 WT compared to control shows increased numbers of LC3 punctae (indicative of putative autophagosomes). Analysis by electron microscopy also revealed increased numbers of autophagosomes in the presence of RGS4 WT compared to the number of autophagosomes in RGS4 ENAA (a loss- of-function mutant of RGS4)-expressing cells. Indeed, expression of RGS4 appeared to induce the same extent of autophagic activity as nutrient starvation, with no additive effect between these two stimuli. Thus, Gαi3/RGS4 and the nutrient-sensing machinery may be part of a common regulatory pathway for autophagy (Guillaume Bastin, unpublished data).

Due to Gαi3’s ability to inhibit autophagy in the liver, in HT-29 cells, and in HeLa cells, and since RGS4 is a GAP for Gαi3, our lab tested the overexpression of both proteins on LC3 II expression in mammalian cells. It was found that Gαi3 alone decreases LC3 II expression, whereas there was an approximate 4-fold increase in LC3 II production when both Gαi3 and

RGS4 were co-expressed. Together, these data support the notion that RGS4 interferes with the ability of Gαi3 to inhibit autophagy. Since RGS4 is expressed in pancreatic beta cells and appears to regulate autophagic flux in some mammalian cell types, we asked whether

RGS4 may regulate autophagic activity in Min6 cells, a mouse pancreatic beta cell line.

2 Rationale and Objective

RGS4 is one of the most highly expressed RGS proteins in the mouse pancreatic islets. Gαi3 has been shown in some tissues to inhibit autophagy and our lab has seen a decrease in autophagy markers when Gαi3 is overexpressed in mammalian cells.

Furthermore, RSG4 is a GAP for Gαi3 (also expressed in the mouse pancreatic islets) in tissues other than the pancreas. Our lab has previously shown that overexpression of RGS4 in a mammalian cell line results in increased expression of autophagy markers (even when

Gαi3 is also overexpressed), and when RGS4 was knocked out in mice, expression of autophagy markers and glucose-stimulated insulin secretion decreased. These results suggest that insulin secretion is dependent on autophagic flux, which is regulated in part by

G-proteins (specifically Gαi3), and that manipulation of Gαi3 with a GAP like RGS4 may result in alterations in insulin secretion. However, mechanisms for this pathway have not yet been elucidated. The objective of this study is to characterize the mechanism by which

RGS4 is altering autophagic flux in insulin-secreting cells.

3 Hypothesis

In light of the previously described observations, we hypothesize that the Min6 pancreatic beta cell line would be an ideal cell model to study the effects of Gαi3 and RGS4 on autophagic signaling in insulin-producing cells. Previous studies have shown that RGS4 may inhibit two distinct pools of Gαi3: an intracellular pool and a plasma membrane pool that is activated by traditional agonist-mediated GPCR signaling. Via its ability to inhibit activated Gαi3 within the intracellular pool, it is anticipated that RGS4 activity will lead to increased autophagic signaling in Min6 cells.

Figure 3-1: A schematic diagram of our hypothesis. We hypothesize that overexpression of RGS4 in the Min6 pancreatic beta cell line may attenuate autophagy via Gαi3 inhibition. Previous studies have shown that there are two pools of Gαi3 that RGS4 may inhibit: an intracellular pool, activated by intracellular GEFs (e.g. GIV), and a plasma membrane pool of Gαi3. We believe that the intracellular pool of Gαi3 may primarily be responsible for the previously-studied inhibition of autophagy, and that this RGS4-mediated increase in autophagy may lead to an increase in insulin secretion in RGS4-overexpressing Min6 cells.

4 Materials and Methods

4.1 Reagents

High glucose Dulbecco’s modified Eagle’s Medium (DMEM) was obtained from

Sigma (D5796). Fetal bovine serum, penicillin, streptomycin, and Opti-MEM reduced serum medium for transfection were from Gibco. Bovine serum albumin and β-mercaptoethanol were from Sigma. Lipofectamine2000 was obtained from Invitrogen. Cells for confocal microscopy were seeded into 35mm “high” ibidi μ-dish plates to avoid birefringence and autofluorescence. Bafilomycin A1 was obtained from LC Laboratories. Secondary antibodies for Western blotting were obtained from Cell Signaling Technologies (anti-rabbit antibody) and GE Healthcare Ltd (anti-mouse antibody). Earle’s Balanced Salt Solution

(Gibco) was used as a starvation medium and was supplemented with 0.45 mmol/L calcium chloride, 0.53 mmol/L magnesium chloride, 0.1% w/v bovine serum albumin, and 0.2% v/v fetal bovine serum.

4.2 Min6 Cell Culture and Transient Transfection

4.2.1 Plasmids

The pEYFP-C1 plasmid (BD Biosciences Clontech, Mississauga, ON, Canada) expression vector was used for expression of all RGS protein constructs. For localization and protein expression studies, RGS4-YFP expression plasmids were generated in the pEYFP-

C1 vector by cloning the human RGS4 cDNA into the NheI/AgeI sites to generate a C- terminal YFP fusion. To produce the RGS4 C2A-YFP construct, a cysteine point mutation was introduce by site-directed mutagenesis (primer sequences: FWD 5’-

gcaggtctgccggctagcgcgctgaggagtgcaaaagata-3’, REV 5’- tatcttttgcactcctcagcgcgctagccggcagacctgc-3’). Gαi3-CFP was a kind gift from the Katie Berlot lab and the RC mutation was introduce by site-directed mutagenesis (primer sequences:

(FWD 5’-ccaactcagcaagatgttcttcggacatgtgtgaagaccacaggcattgtagaaacacat-3’, REV 5’- atgtgtttctacaatgcctgtggtcttcacacatgtccgaagaacatcttgctgagttgg-3’). Atg12-RFP was obtained from Origene and Beclin1-DsRed and S6K1-HA was obtained from Addgene. All plasmid constructs were purified by using the Endofree Maxi kit (Qiagen) and verified by sequencing analysis of the protein-coding region.

4.2.2 Min6 Cell Culture and Transient Transfection

Min6 mouse pancreatic beta cells (a kind gift from Dr. Michael Wheeler) were cultured at 37°C with 5% CO2 in high glucose (25mM) DMEM containing 10% (v/v) heat- inactivated fetal bovine serum, 100 u/mL penicillin, 10 μg/mL streptomycin, and 24.4

μmol/L β-mercaptoethanol. See Figure A-1 for optimization experiments of glucose concentration in Min6 cell culture medium.

Before each series of studies, cells were seeded the day before the transfection in

35mm or 6-well plates and were at 70-80% confluency immediately before transfection.

Cells were transfected using Lipofectamine2000 according to the manufacturer’s protocol.

For confocal microscopy experiments, cells were transfected with 1ug of each plasmid; for

Western blotting and calcium imaging experiments, cells were transfected with 2ug of each plasmid.

4.3 Confocal Microscopy

Cells were used between passages 30-40. Confocal microscopy was performed on

65-85% confluence live Min6 cells at 37°C with 5% CO2 using an Olympus Fluoview 1000 laser-scanning confocal microscope. Images are of a single equatorial plane on the basal side of the cell obtained with a 60x oil objective (Zeiss), 1.8 numerical aperture. Since in some experiments, cells were co-transfected with three different fluorescent-tagged proteins that are excited at three different wavelengths and laser interactions were tested to ensure no bleed-through into other channels (see Figure A-2). Lasers used were the

488nm laser (YFP), the 543nm laser (RFP and DsRed), and the 405nm laser (CFP). The resolution of the microscope was 212nm for the YFP and GFP proteins, 176nm for the CFP proteins, and 236nm for the RFP and DsRed proteins. Confocal images were processed with

Fluoview 1000 software. RGS4 punctae counts were performed in a blinded manner using the epifluorescent lamp with a GFP filter. Pearson colocalization coefficient for each punctum was calculated by the Fluoview 1000 software.

4.4 Western Blotting

Cells were used between passages 19-38. Cell culture medium was replaced 40 hours after transfection with Lipofectamine2000 (see protocol above) and 8 hours before cell lysis. Cells were washed with cold PBS twice before being lysed. For lysis, cells were exposed to a cold hypotonic lysis buffer (50mM Tris-HCl (pH 7.4), 1mM EDTA, 1 cOmplete

Mini cocktail protease inhibitor tablet (Roche) per 10mL solution) followed by three freeze/thaw cycles (vortexed after each thaw). Samples were centrifuged at 13 000 rpm for

two minutes in a cold room. The supernatant was removed and 2X Laemmli sample buffer

(BioRad) was added. Samples were boiled for 2 minutes then proteins were separated by electrophoresis through a 12% polyacrylamide gel, transferred to a nitrocellulose membrane (BioRad), and blocked for one hour with blocking buffer: 5% BSA (w/v) (Sigma) solubilized in Tris-buffered saline (50mM Tris, 150mM NaCl, pH 7.6) with 0.1% (v/v) tween-

20 (TBST). Following the blocking step, membranes were incubated on a shaker overnight at 4°C with primary antibody diluted in blocking buffer. Primary antibodies included anti- phospho-p70S6K rabbit antibody (~70kDa, Thr389, diluted 1:1000, Cell Signaling

Technology, Beverly, MA, USA), anti-p70S6K rabbit antibody (~70kDa, diluted 1:1000, Cell

Signaling Technology, Beverly, MA, USA), anti-phospho-Bcl-2 antibody (~28kDa, Ser70, diluted 1:1000, Cell Signaling Technology, Beverly, MA, USA), anti-Bcl-2 antibody (~28kDa, diluted 1:1000, Cell Signaling Technology, Beverly, MA, USA), anti-LC3 rabbit antibody

(~17kDa for LC3-I and ~19kDa for LC3-II, diluted 1:1000, Novus Biologicals Canada, Oakville,

ON, Canada), and anti-α-tubulin mouse antibody (~52kDa, diluted 1:1000, Cell Signaling

Technology, Beverly, MA, USA),. The next day, membranes were washed three times (15 minutes, 5 minutes, 5 minutes) with TBST at room temperature then incubated in the appropriate horseradish peroxidase-linked secondary antibody diluted in blocking buffer for minimum 1 hour at room temperature. The secondary antibody was visualized using Super

Signal West Pico Chemiluminescent Substrate (Thermo Scientific) used according to manufacturer’s instructions. ImageJ (version 1.47) and ImageLab software (version 5.2,

BioRad) was used to quantify band density. Band density was always normalized; in blots measuring phospho-p70S6K protein expression, expression was normalized to total S6K protein expression. In blots measuring LC3 II protein expression, expression was normalized to α-tubulin protein expression. And in blots measuring phospho-Bcl-2 expression, expression was normalized to total Bcl-2 expression.

4.5 Statistical Analysis

Values are expressed as means ± S.E.M. To compare whether two sets of data were significantly different from each other, the student’s T-test was used. Two-way ANOVA generated information about whether two independent variables affected the dependent variable in a statistically significant manner. One-way ANOVA was used to compare the means of three or more samples in order to determine if they were significantly different from each other. In all cases, a p-value of 0.05 was chosen to determine statistical significance.

5 Results

5.1 Autophagy Occurs in Min6 Cells

In order to determine whether transfected Min6 cells undergo autophagy, we transfected the cells with LC3-GFP. As outlined in Figure 1-1, LC3 protein expression can indicate the amount of autophagy that is occurring in a cell, since LC3 II is required for autophagosomal maturation. Bafilomycin A1 drug treatment was used to prevent the degradation of LC3 II which normally accumulates inside the autophagosome prior to fusion with the lysosome; bafilomycin A1 prevents autophagosome-lysosome fusion. Comparison of Bafilomycin A1-treated versus untreated cells thus provides a relative measure of autophagic flux. Nutrient-starvation was used as a mechanism to induce autophagy. Four conditions were tested: fed state with no drug treatment, fed state with bafilomycin A1 treatment for 4 hours, starved state for 4 hours with no drug treatment, and starved state with bafilomycin A1 treatment for 4 hours. We counted LC3-GFP punctae seen in the cells.

Consistent with the proper activation of autophagy in our cell model, Min6 cells in the fed state had the lowest number of average LC3-GFP punctae per cell whereas starved cells had the highest number of LC3 punctae (p < 0.00001). Fed cells without bafilomycin

A1 treatment had the lowest average number of LC3-GFP punctae per cell (average 7.175 punctae per cell), followed by fed cells with bafilomycin A1 treatment (average 7.363 punctae per cell). Starved cells with bafilomycin A1 treatment had the highest average punctae per cell (19.313 punctae per cell), and this number was much higher than starved cells with no drug treatment (average 15.425 punctae per cell, p = 0.012) indicating a significant degree of autophagic flux in the starved condition. These results are seen in

Figure 5-1.

An additional experiment was done to test the ability of transfected Min6 cells to undergo autophagy; cells were transfected with pEYFP, an “empty vector”, and then either fed or starved for 4 hours before measuring LC3 II by Western blotting. pEYFP, the vector from which the RGS4 constructs were created, can be used as a “baseline” transfection plasmid for autophagy marker expression. Starvation was used as a mechanism to induce autophagy. As above, the cells were either treated with bafilomycin A1, or left untreated.

We quantified LC3 II protein expression, since LC3 II is a marker of autophagosomal formation. As seen in Figure 5-2, starved cells treated with bafilomycin A1 had significantly more LC3 II than fed cells treated with bafilomycin A1 (p = 0.029), and starved, untreated cells had significantly more LC3 II than fed, untreated cells (p = 0.025). Bafilomycin A1 treatment led to very slight increases in LC3 II protein expression that were statistically insignificant. LC3 II protein expression was normalized to α-tubulin protein expression in order to control for well loading. Taken together, these data show that Min6 cells show proper regulation of autophagic flux in response to changing nutrient status.

A) B) Fed + baf Starved + baf

10um10um 10um10um

C) D) Fed NO baf Starved NO baf

10um 10um

p = 0.012 n = 80 p < 0.00001 25 p < 0.00001 20 15 10 5

per per cell 0 Fed Starved Fed Starved Bafilomycin A1 No Bafilomycin A1

Drug treatment and starvation state Average Average number LC3 of punctae

Figure 5-1: LC3 punctae counts show that autophagy occurs in Min6 cells. Min6 cells transfected with LC3-GFP and either starved for 4 hours or fed, and either treated or not treated with bafilomycin A1 (baf) show that Min6 cells undergo autophagy. Panel A: Fed Min6 cells treated with bafilomycin A1 show few LC3 punctae. Panel B: Starved Min6 cells treated with bafilomycin A1 show many LC3 punctae. Panel C: Fed Min6 cells not treated with bafilomycin A1 show very few LC3 punctae. Panel D: Starved Min6 cells not treated with bafilomycin A1 show fewer punctae than starved Min6 cells treated with bafilomycin A1 but a lot more punctae than fed cells. Panel E: Number of LC3 punctae quantified in each condition. Statistical significance assessed by student’s T test. n is number of cells.

n = 3 p = 0.029 3 p = 0.025 2.5

tubulin -

α 1.5

1 LC3 LC3 / II protein expression 0.5

0 Fed Starved Fed Starved Bafilomycin A1 No Bafilomycin A1 Drug treatment and starvation state

Figure 5-2: pEYFP-transfected Min6 cells undergo autophagy when starved. Min6 cells transfected with pEYFP (empty vector) and either starved for 4 hours or fed, and either treated with bafilomycin A1 (baf) or untreated show that Min6 cells undergo autophagy. LC3 II protein expression is a marker of autophagy, and starvation induced significantly increased LC3 II levels in both drug-treated (p = 0.029) or untreated states (p = 0.025). Bafilomycin A1 increased LC3 II protein expression in both the fed and starved states; however this increase was not statistically significant. All samples normalized to α-tubulin protein expression. Statistical significance assessed by student’s T test. n is number of cells.

5.2 RGS4 Localization Patterns and Colocalization with Gαi3 and Autophagy Markers

Confocal microscopy images were taken to determine the localization of various

RGS4 mutants, Gαi3 (RC), and the autophagy markers Atg12 and Beclin1. These studies were carried out to determine whether RGS4 might colocalize with signaling complexes/markers that are thought to regulate autophagic initiation in mammalian cells.

Although some groups have done studies with RGS4 in Min6 cells, none had previously characterized RGS4 localization in this cell line.

5.2.1 RGS4, Gαi3, and Autophagy Marker Localization in Min6 cells

In HEK cells, RGS4 has been shown to localize to the plasma membrane of the cell

(presumably with GPCRs) as well as to intracellular pools (79). RGS4 ENAA localizes very similarly in HEK cells as the mutation in the RGS domain does not alter its localization pattern and only affects its ability to act as a GAP. RGS4 C2A was shown to localize primarily to the plasma membrane of HEK cells.

As seen in Figure 5-3, RGS4 localization in over 130 Min6 cells follows the same patterns as in HEK cells. RGS4 WT localized to the plasma membrane and the cytosol, with concentrated staining also observed in intracellular pools (i.e. punctae). These intracellular punctae may be representative of putative autophagosomes. As expected, RGS4 ENAA localized nearly identically to RGS4 WT, with staining occurring at the plasma membrane as well as in the cytosol, and intracellular punctae, or putative autophagosomes, can be seen in this condition as well. The palmitoylation mutant RGS4 C2A localized strongly to the plasma membrane of the cell with weak, diffuse staining intracellularly. Intracellular RGS4

punctae were rarely observed in this condition. The inability of RGS4 C2A to localize to intracellular punctae may have also been reflected by its increased cytosolic localization.

Gαi3 (RC) is the constitutively active mutant of Gαi3. The localization of Gαi3 (RC) in

Min6 cells was similar to that of RGS4 with the exception that the intracellular staining was weaker than seen in the RGS4 phenotypes. Strong Gαi3 (RC) localization occurred on the plasma membrane and as intracellular punctae in all conditions. Beclin1 localized strongly to intracellular pools and weakly stained the cytosol in some cases; Beclin1 found in the cytosol was less rare than Atg12 being found in the cytosol. Representative images of the triple-stained Min6 cells with Beclin1-DsRed can be seen in Figure 5-4. Atg12 localized strongly to intracellular pools (punctae) and only weakly stained the cytosol in rare cases.

Representative images of triple-stained Min6 cells with Atg12-RFP can be found in Figure 5-

RGS4 WT RGS4 ENAA

3um 3um

RGS4 C2A

3um

Figure 5-3: Representative images showing RGS4 localization in Min6 cells. The top left panel shows RGS4 WT localization in Min6 cells. Similar to other cell types, RGS4 localizes to both the plasma membrane (indicated by the red arrow heads) and the cytosol. RGS4 also appears to localize to intracellular pools such as punctae, or putative autophagosomes (indicated by the white arrow heads). RGS4 ENAA (top right panel) localizes to both the plasma membrane and intracellularly, as expected, since RGS4 ENAA is a loss of function mutant and its localization pattern has not been reported to be different from the WT protein. Intracellular punctae are also seen in the RGS4 ENAA condition. The bottom panel shows RGS4 C2A localization in Min6 cells. Literature has shown that RGS4 C2A does not allow for intracellular trafficking and appears to primarily localize on the plasma membrane of the cells. The RGS4 C2A image above shows weak, diffuse cytosolic staining and no intracellular punctae. The inability of RGS4 C2A to localize to intracellular punctae may be seen by increased cytosolic localization.

Panel A Panel B

Panel C

Figure 5-4: Representative images of confocal microscopy photos of Beclin1-DsRed- expressing Min6 cells. In all panels, blue colouring represents Gαi3 (RC)-CFP, green colouring represents RGS4-YFP, and red colouring represents Beclin1-DsRed. The bottom right image is a merge image of all three images. Panel A: Min6 cells co-expressing Gαi3 (RC)-CFP, RGS4 WT-YFP, and Beclin1-DsRed show scattered punctae in all channels. Panel B: Min6 cells co-expressing Gαi3 (RC)-CFP, RGS4 ENAA-YFP, and Beclin1-DsRed show scattered punctae in all channels. Localization is very similar to Panel A. Panel C: Min6 cells co- expressing Gαi3 (RC)-CFP, RGS4 C2A-YFP, and Beclin1-RFP demonstrate clustered punctae in all channels. Gαi3 (RC)-CFP and Beclin1 localization is similar to Panels A and B, but RGS4 C2A localizes more strongly to the plasma membrane. White arrow heads indicate colocalized punctae. Images representative of at least 80 cells looked at in 3 experiments.

Panel A Panel B

Gαi3 (RC)-CFP RGS4 WT-YFP Gαi3 (RC)-CFP RGS4 ENAA-YFP

3 um 3um Atg12-RFP Merge Atg12-RFP Merge

Panel C

Gαi3 (RC)-CFP RGS4 C2A-YFP

3um Atg12-RFP Merge

Figure 5-5: Representative images of confocal microscopy photos of Atg12-RFP-expressing Min6 cells. In all panels, blue colouring represents Gαi3 (RC)-CFP, green colouring represents RGS4-YFP, and red colouring represents Atg12-RFP. The bottom right image is a merge image of all three images. Panel A: Min6 cells co-expressing Gαi3 (RC)-CFP, RGS4 WT- YFP, and Atg12-RFP show clustered punctae in all channels. Panel B: Min6 cells co- expressing Gαi3 (RC)-CFP, RGS4 ENAA-YFP, and Atg12-RFP show clustered punctae in all channels. Localization in all channels is very similar to Panel A. Panel C: Min6 cells co- expressing Gαi3 (RC)-CFP, RGS4 C2A-YFP, and Atg12-RFP demonstrate clustered punctae in all channels. Gαi3 (RC)-CFP and Atg12 localization is similar to Panels A and B, but RGS4 C2A localizes more strongly to the plasma membrane. Images representative of at least 60 cells looked at in 3 experiments.

5.2.2 Characterization of RGS4 and Autophagy Marker Punctae Distribution and

Localization in Min6 cells

An interesting cell biologic phenotype was observed while characterizing RGS4 localization in Min6 cells transfected with different autophagy markers. Specifically, intracellular RGS4 punctae appeared to either cluster or scatter depending on the marker used for characterization. It was therefore decided to stratify the results and consider clustered and scattered punctae separately to better define our model expression system with the various markers. Figures 5-4 and 5-5 show representative examples of cells from each condition to illustrate the difference between categorically “clustered” punctae and

“scattered” punctae. Broadly, groups of punctae that were congregated in a similar area of the cells were considered to be clustered; punctae that were individually found at intervals in different directions throughout the cytosol were considered to be scattered. Cells classified as having scattered punctae often had punctae throughout a majority of the area of the cytoplasm whereas cells classified with clustered punctae had punctae clustered in a small portion of the cytoplasm.

Thus RGS4 punctae localization patterns were identified and punctae distribution was quantified in Min6 cells co-transfected with an RGS4-YFP construct, an autophagy marker (Beclin1-DsRed and Atg12-RFP), and Gαi3 (RC)-CFP. Two different types of RGS4 punctae characterizations were performed: 1) a distribution quantification where only cells with RGS4 punctae were taken into consideration, giving information about the characteristics of the RGS4 punctae in cells where putative autophagosomes were forming, and 2) an RGS4 punctae distribution quantification where all cells, with and without punctae, were taken into consideration, giving information about the percentage of cells

that were forming RGS4 punctae (and putative autophagosomes). The transfection efficiency in all samples of all trials was 50-60%.

1) Punctae distribution in cells with punctae.

According to the punctae distribution in cells with punctae depicted in Figure 5-6, independent of the RGS4 construct expressed in the cells, about 85% of cells expressing

Beclin1 had scattered punctae throughout the cytoplasm, as opposed to clustered intracellular punctae (making up about 15% of cells expressing Beclin1). On the other hand, about 81% of cells expressing Atg12 showed clustered cytosolic punctae and only about

19% of cells had scattered intracellular punctae. The effect of Atg12 or Beclin1 on punctae patterning was significant; p = 0.0001 when Atg12 or Beclin1 were co-transfected with RGS4

ENAA and p = 0.0001 when Atg12 or Beclin1 were co-transfected with RGS4 WT (assessed by student’s T-test). These results were consistent when cells overexpressed RGS4 WT or

RGS4 ENAA; in fact, the RGS4 construct did not make a significant difference to punctae patterning (p > 0.05 for Atg12-expressing samples, i.e. RGS4 WT or ENAA co-expressing

Atg12, and for Beclin1-expressing samples, i.e. RGS4 WT or ENAA co-expressing Beclin1, student’s T-test). This clustered RGS4 punctae phenotype was mimicked in the Atg12-RFP channel; that is, Atg12-RFP intracellular punctae were clustered as well.

2) Punctae distribution in all cells

Figure 5-7 portrays the punctae distribution in all cells, including those without any

RGS4 punctae. A similar trend to Figure 5-6 can be seen, whereby Beclin1-transfected cells have more scattered RGS4 punctae than clustered RGS4 punctae (except in the case of samples overexpressing RGS4 C2A), and Atg12-transfected cells have more clustered punctae than scattered punctae. However, in this “global” punctae analysis, certain

conditions had a substantial ratio of cells with no punctae. In both conditions overexpressing RGS4 ENAA (RGS4 ENAA + Atg12 co-expression and RGS4 ENAA + Beclin1 co- expression), just over 20% of cells did not have punctae. Dissimilarly, the conditions overexpressing RGS4 WT (RGS4 WT co-expressing either Beclin1 or Atg12) differed in the distribution of cells that did not have punctae. When RGS4 WT was co-expressed with

Beclin1, close to 50% of cells did not produce punctae. However, when RGS4 WT was co- expressed with Atg12, approximately 15% of cells did not produce punctae, indicating that when RGS4 WT is co-expressed with Beclin1, unlike RGS4 ENAA co-expressed with Beclin1, punctae (and putative autophagosome) production is decreased. In the Beclin1 condition,

RGS4 ENAA co-expression resulted in more cells with punctae than RGS4 WT co-expression.

RGS4 C2A behaves differently than RGS4 WT or RGS4 ENAA; when co-transfected with Beclin1, more than 90% of cells don’t have RGS4 punctae. The remaining cells appear to have equal numbers of scattered versus clustered punctae, which differs from the trend observed in Figure 5-6 (whereby Beclin1-expressing cells have more scattered punctae than clustered punctae). When RGS4 C2A is co-transfected with Atg12, close to 50% of cells did not have punctae and the remaining cells had more clustered punctae than scattered punctae, consistent with the trend observed in Figure 5-6 whereby Atg12-expressing cells have more clustered punctae than scattered punctae.

p = 0.0001 p = 0.0001

100% 90% 80% 70% 60% 50% 40%

Percent Percent punctae 30% 20% 10% 0% Beclin1 Atg12 Beclin1 Atg12 n = 183 n = 231 n = 181 n = 241

RGS4 WT RGS4 ENAA Construct expressed

Scattered Clustered

Percentage of all punctae observed [%  SEM (n)]:

RGS4 WT RGS4 ENAA Beclin1 Atg12 Beclin1 Atg12 Scattered punctae 85.25  18.67  86.5  19.5  2.78 (183) 7.45 (231) 6.86 (181) 4.43 (241) Clustered punctae 14.75  81.33  13.5  80.5  2.78 (183) 7.45 (231) 6.86 (181) 4.43 (241)

Figure 5-6: Punctae distribution in cells with punctae. Independent of which RGS4 construct is expressed, the autophagy marker expressed dictates whether punctae are scattered or clustered. Atg12 expression leads to significantly more clustered punctae, while Beclin1 leads to significantly more clustered punctae. The RGS4 construct did not make a significant difference in scattered vs clustered punctae distribution (p = 0.461 between RGS4 ENAA + Atg12 and RGS4 WT and Atg12; p = 0.436 between RGS4 ENAA + Beclin1 and RGS4 WT + Beclin1). All samples were co-transfected with Gαi3 (RC)-CFP. Statistical significance assessed by student’s T test. n is number of cells; data collected from 4 experiments.

p = 0.003 p = 0.009 100% 90% 80% 70% 60% 50% 40%

Percent Percent punctae 30% 20% 10% 0% RGS4 WT RGS4 ENAA RGS4 C2A RGS4 WT RGS4 ENAA RGS4 C2A n =126 n =125 n =131 n =61 n =123 n =136

Beclin1 n =123 Atg12

Constructs expressed

Scattered Clustered No punctae

Percentage of all punctae observed [%  SEM (n)]:

Beclin1 Atg12 RGS4 WT RGS4 ENAA RGS4 C2A RGS4 WT RGS4 ENAA RGS4 C2A Scattered 43.5  5.5 68.5  8.5 4  1 26.5  1.5 21.5  3.5 20.5  1.5 (126) (125) (131) (61) (123) (136) Clustered 8.5  2.5 5.5  0.5 4  3 59.5  2.5 56  3 31.5  24.5 (126) (125) (131) (61) (123) (136) No punctae 48  3 26  9 92  2 14  1 22.5  6.5 48  23 (126) (125) (131) (61) (123) (136)

Figure 5-7: Punctae distribution in all cells. Similarly to punctae distribution in cells with punctae, there is a significant difference in scattered vs clustered punctae distribution corresponding to Atg12 or Beclin1 overexpression in the RGS4 WT and RGS4 ENAA- overexpressing samples (p = 0.048 in RGS4 WT samples and p = 0.018 in RGS4 ENAA samples). In all samples expressing Beclin1 with RGS4 WT or RGS4 ENAA, the number of cells expressing punctae was significantly greater than the number of cells expressing punctae in the RGS4 C2A samples (p = 0.009 for RGS4 ENAA samples, p = 0.003 for RGS4 WT samples). In the Beclin1 condition, RGS4 ENAA co-expression resulted in more cells with punctae than RGS4 WT co-expression (p > 0.05). In samples overexpressing RGS4 C2A with Atg12, close to 50% of cells did not have punctae and in samples overexpressing RGS4 C2A with Beclin1, over 90% of cells did not have punctae (p > 0.05). Statistical significance assessed using student’s T test. n is number of cells.

5.2.3 Characterization of RGS4 and Autophagy Marker Colocalization within Punctae in

Min6 Cells

In order to assess the number of punctae that colocalized, punctae counts were performed for three groups: colocalization between RGS4-YFP and Beclin1-DsRed (shown in

Figure 5-8(a)), colocalization between RGS4-YFP and Gαi3 (RC)-CFP (shown in Figure 5-8(b)), and colocalization between Gαi3 (RC)-CFP and Beclin1-DsRed (shown in Figure 5-8(c)). RGS4

WT and Beclin1 colocalized the most frequently, with just over 1 punctate per cell on average. This was statistically significantly higher than the colocalization frequency between RGS4 C2A and Beclin1 punctae (p = 0.009) and also higher than the colocalization frequency between RGS4 ENAA and Beclin1 punctae. RGS4 ENAA and Beclin1 punctae colocalization was significantly more frequent than RGS4 C2A and Beclin1 punctae colocalization as well (p = 0.034).

RGS4 and Gαi3 (RC) colocalization (Figure 5-8(b)) frequency followed a similar trend to RGS4 and Beclin1 colocalization frequency. RGS4 WT and Gαi3 (RC) colocalized the most frequently, with just over 1 punctate per cell on average. This was statistically significantly higher than the colocalization frequency between RGS4 C2A and Gαi3 (RC) punctae (p =

0.021) and also higher than the colocalization frequency between RGS4 ENAA and Gαi3 (RC) punctae. RGS4 ENAA and Gαi3 (RC) punctae colocalization occurred more often than RGS4

C2A and Gαi3 (RC) punctae colocalization as well.

Lastly, Gαi3 (RC) and Beclin1 punctae colocalized with similar frequency no matter which RGS4 construct was expressed (Figure 5-8(c)). With RGS4 WT expression, Gαi3 (RC) and Beclin1 colocalized slightly less frequently than when RGS4 C2A was overexpressed, and

RGS4 ENAA overexpression led to the lowest incidence of Gαi3 (RC) and Beclin1 punctae colocalization. Gαi3 (RC) and Beclin1 colocalized the most frequently out of all three groups,

with an average of 6 to 7 colocalized punctae per cell (dependent on the RGS4 constuct co- expressed).

p = 0.009 1.4 p = 0.034 1.2

0.8

0.6

0.4 colocalized punctae 0.2

Average Average number RGS4 and Beclin1 0 RGS4 WT RGS4 ENAA RGS4 C2A n =130 n =97 n =81

Construct expressed

Figure 5-8(a): Average number of RGS4 and Beclin1 colocalized punctae per cell. RGS4 WT and Beclin1 punctae colocalized the most frequently, and RGS4 C2A and Beclin1 punctae colocalized the least frequently. Significant differences in RGS4-Beclin1 punctae colocalization was observed between RGS4 WT and RGS4 C2A (p = 0.009) and RGS4 ENAA and RGS4 C2A (p = 0.034). Statistical significance assessed by using student’s T test. n is number of cells; data collected over minimum 3 experiments.

p = 0.021

1.6 i3

α 1.4

1.2

0.8

0.6

colocalized punctae 0.4

0.2 Average Average number RGS4 andG 0 RGS4 WT RGS4 ENAA RGS4 C2A n =130 n =97 n =81

Construct expressed

Figure 5-8(b): Average number of RGS4 and Gαi3 colocalized punctae per cell. RGS4 WT and Gαi3 (RC) punctae colocalized the most frequently, and RGS4 C2A and Gαi3 (RC) punctae colocalized the least frequently. A statistically significant difference in occurrence of colocalization with Gαi3 (RC) punctae occurred between RGS4 WT punctae and RGS4 C2A punctae (p = 0.021). Statistical significance assessed by using student’s T test. n is number of cells; data collected over minimum 3 experiments.

10 9 8

7 and Beclin1 andBeclin1

i3 6 α 5 4

3 colocalized punctae 2

Average Average number G 1 0 RGS4 WT RGS4 ENAA RGS4 C2A n =130 n =97 n =81

Construct expressed

Figure 5-8(c): Average number of Gαi3 and Beclin1 colocalized punctae per cell. Gαi3 (RC) and Beclin1 punctae colocalized similarly independent of the RGS4 construct co-expressed. On average, at least 6 Gαi3 and Beclin1 colocalized punctae were seen per cell. n is number of cells; data collected over minimum 3 experiments.

5.2.4 Pearson Colocalization Coefficient Analysis

It is difficult to visually assess the degree of colocalization from a pair of images when they are overlaid, so to determine punctae colocalization, Pearson colocalization coefficients (PCCs) between three groups of proteins was measured: Gαi3 (RC)-CFP and

RGS4-YFP constructs, Gαi3 (RC)-CFP and Beclin1-DsRed, and RGS4-YFP constructs and

Beclin1-DsRed, as seen in Figure 5-9. In general, a PCC between 0 and 1 indicates colocalization and a PCC between -1 and 0 indicates no colocalization. The closer the value to the outer limit (-1 or 1), the stronger the colocalization/non-colocalization phenotype

(83).

PCC analysis between both RGS4 WT- and ENAA-containing punctae and Gαi3 (RC) punctae yielded a positive PCC, indicating that there was indeed colocalization between the two. When the plasma membrane-localized RGS4 construct RGS4 C2A was co-expressed with Gαi3 (RC), a negative PCC was observed, indicating that there is no localization between the two proteins.

Colocalization between Gαi3 (RC)-containing punctae and the autophagy marker

Beclin1 was also indicated by a positive PCC. Indeed, the PCC for this colocalization was the highest of any of the three groups examined, with a mean PCC > 0.2.

Colocalization analysis between RGS4 punctae and Beclin1 also indicated colocalization (albeit at somewhat lower PCC values). Interestingly, RGS4 WT colocalization with Beclin1 was similar to RGS4 ENAA and Beclin1 colocalization (PCCs of less than 0.1).

The RGS4 C2A construct also colocalized poorly with Beclin1.

0.5 0.4 0.3 0.2 0.1 0

-0.1

Pearson colocalizationcoefficient

i3RC and RGS4 and i3RC RGS4 and i3RC RGS4 and i3RC

α α α

i3RC and Beclin1 and i3RC i3RC and Beclin1 and i3RC Beclin1 and i3RC

RGS4 and Beclin1 and RGS4 RGS4 andBeclin1 RGS4 andBeclin1 RGS4

G G G

α α α

G G G RGS4 ENAA RGS4 WT RGS4 C2A n =94 n =115 n =80

Constructs co-expressed

Figure 5-9: Pearson colocalization coefficient values for punctae of cells overexpressing an RGS4 construct and Beclin1. Gαi3 (RC) and RGS4 weakly colocalized in all samples except when RGS4 C2A was expressed; RGS4 C2A localizes to the plasma membrane of the cell. Gαi3 (RC) and autophagy marker Beclin1 also strongly colocalized in all conditions. RGS4 and Beclin1 weakly colocalized in all conditions. P > 0.05 for all statements above; statistical significance assessed by one-way ANOVA. n is number of cells; data collected over minimum 3 experiments.

5.3 RGS4’s Effect on Autophagy Protein Marker Expression

5.3.1 RGS4 and Phospho-p70S6K

In order to examine the functional role of RGS4 as a regulator of autophagy in Min6 cells, immunoblotting was performed in Min6 cells co-transfected with various RGS4-YFP constructs and S6K1-HA. S6K1-HA had to be expressed in the Min6 cells in order to see its phosphorylation levels; the Western blot is not sensitive enough to detect the endogenous amounts of p70S6K expressed in Min6 cells that get phosphorylated. RGS4 ENAA and RGS4

WT autophagy marker expression were compared. The first autophagic regulatory pathway marker quantified in these experiments was phospho-p70S6K normalized to total p70S6K protein expression, as it is a readout for mTOR activity; thus, when there are high levels of phospho-p70S6K, it generally means that mTOR activity is elevated, and as a consequence autophagic flux is diminished (see section 1.1.2 and Figure 1-1).

As seen in Figure 5-10, in the RGS4 WT samples, there was a trend toward a decrease in normalized phospho-p70S6K compared to the RGS4 ENAA samples, which might coincide with increased autophagy in our Min6 cells. Phospho-p70S6K protein expression was normalized to total p70S6K protein expression in order to determine mTOR activity.

Notably, this difference did not reach statistical significance (p = 0.211).

n = 6 1.4

1.2

0.8

0.6

P70S6K P70S6K S6K total / -

protein expression 0.4

Phospho 0.2

0 RGS4 WT RGS4 ENAA Construct expressed

Figure 5-10: RGS4 overexpression does not change phospho-p70S6K protein expression levels significantly. Phospho-p70S6K is an indicator of increased mTOR activity, which also acts to inhibit autophagosome formation. When RGS4 WT was overexpressed in Min6 cells, there was a slight decrease in phospho-p70S6K protein expression compared to RGS4 ENAA. Phospho-p70S6K expression normalized to total S6K protein expression. P > 0.05; statistical significance assessed by student’s T-tests. n is number of trials.

5.3.2 Average Number of Beclin1 Punctae per Cell

As discussed above, RGS4 did not significantly affect mTOR activity in our Min6 cell model system, however, data indicated a potential trend toward increased autophagic activity in most of the experiments. To test whether co-expressing different RGS4 constructs would have an effect on the number of Beclin1-DsRed punctae seen per cell, which indicate putative autophagosomes, Beclin1 punctae counts were performed under the confocal microscope. The results are shown in Figure 5-11. RGS4 ENAA expression resulted in the highest average punctae count of about 11 Beclin1 punctae per cell. RGS4

C2A and RGS4 WT expression resulted in very similar numbers of Beclin1 punctae per cell; about 9 Beclin1 punctae per cell were seen in these conditions. However, none of these results were statistically significant, indicating that RGS4 may not increase Beclin1 punctae expression in Min6 cells.

4 punctaeper cell

2 Average Average numberBeclin1 of 0 RGS4 WT RGS4 ENAA RGS4 C2A Construct expressed

Figure 5-11: Average number of Beclin1 punctae per cell. RGS4 WT, RGS4 ENAA, and RGS4 C2A overexpression led to similar numbers of Beclin1 punctae per cell, with RGS4 ENAA samples expressing slightly higher numbers of Beclin1 punctae. P > 0.05; statistical significance assessed by one-way ANOVA and student’s T-tests. 309 cells examined.

5.3.3 RGS4 and Phospho-Bcl-2

RGS4 did not significantly affect Beclin1 punctae counts in Min6 cells. In order to determine whether RGS4 has an effect on Bcl-2 activity, phospho-Bcl-2 protein expression was measured (Figure 5-12). As described in section 1.1.2, Jnk1 phosphorylates Bcl-2 in order to prevent it from inhibiting the Beclin1-Vps34 interaction, which is required for autophagosomal formation and maturation. Preliminary data from our lab suggest that this assay is among the most sensitive measures of intracellular Gαi3-mediated Jnk inhibition during autophagic signaling.

Phospho-Bcl-2 protein expression was measured in Min6 cells overexpressing RGS4

WT or RGS4 ENAA and either fed or starved for 8 hours. Starvation increased phospho-Bcl-2 expression generally, in a statistically insignificant manner. Phospho-Bcl-2 protein expression was highest when Min6 cells were starved and overexpressed RGS4 WT; however, in the fed state, RGS4 ENAA overexpression produced the most phospho-Bcl-2. In general, RGS4 did not make a significant difference to phospho-Bcl-2 expression. In all phsopho-Bcl-2 Western blots, phospho-Bcl-2 protein expression was normalized to total Bcl-

2 expression in order to get a more accurate quantification of pro-autophagic activity.

n = 3 3.5

2 2 - 2.5

2 2 Bcl total / -

Bcl 1.5 -

protein expression 1

Phospho 0.5

0 RGS4 WT RGS4 ENAA RGS4 WT RGS4 ENAA Starved 8 hours Fed Fed/starvation state and constructs expressed

Figure 5-12: The effect of RGS4 and starvation on phospho-Bcl-2 protein expression in Min6 cells. Bcl-2 is must be phosphorylated in order for autophagy to occur. In the fed state, RGS4 ENAA caused the highest increase in phospho-Bcl-2. In the starved state, RGS4 WT-overexpression resulted in the highest phospho-Bcl-2 expression compared to RGS4 ENAA, but this result was not statistically significant (p = 0.906, assessed by one-way ANOVA). Starvation vs fed state resulted in a difference in phospho-Bcl-2 expression; however, RGS4 expression did not make a significant difference to phospho-Bcl-2 expression. Phospho-Bcl-2 protein expression was normalized to total Bcl-2 protein expression. n is number of trials.

5.3.4 RGS4 and LC3

Since the phopsho-p70S6K Western blots did not show any significant change in mTOR activity and the phospho-Bcl-2 Western blots did not show any significant change in

Jnk activity in the presence of RGS4, we tested whether RGS4 could alter autophagy through an alternate non-mTOR- and non-Jnk-regulated pathway. LC3 II expression is used as a measure of autophagic flux.

In the fed state, LC3 II protein expression increased with bafilomycin A1 treatment for 4 hours (compared to no bafilomycin A1 treatment). This difference in protein expression was significant when RGS4 WT was expressed (p = 0.046, assessed by student’s T test) but insignificant in the presence of RGS4 ENAA, indicating that bafilomycin A1 had a larger effect on LC3 II expression in the presence of RGS4 WT. LC3 II protein expression was highest when RGS4 WT was expressed in combination with bafilomycin A1 treatment; however, without bafilomycin A1 treatment, LC3 II expression was very similar in both conditions. Figure 5-13a depicts LC3 II protein expression in fed Min6 cells with and without bafilomycin A1 treatment and Figure 5-13b illustrates the effect of bafilomycin A1 on LC3 II protein expression in fed Min6 cells.

Min6 cells overexpressing RGS4 mutants were also starved for 4 hours or 2 hours and treated with bafilomycin A1 for 4 hours, 2 hours, or not at all. Cells starved for 4 hours were treated with bafilomycin A1 for 4 hours; cells starved for 2 hours were treated with bafilomycin A1 for 2 hours; and cells not treated with bafilomycin A1 were starved for 2 hours. Starvation was used as a tool to induce autophagy. Similarly to the fed state, LC3 II protein expression was highest in both conditions when treated with bafilomycin A1 for 4 hours and the higher difference seen was in cells expressing RGS4 WT and treated with bafilomycin A1 for 4 hours. Without bafilomycin A1 treatment, LC3 II protein expression

was similar in all conditions. However, RGS4 WT-expressing cells had the highest LC3 II protein expression under bafilomycin A1 treatment. Figure 5-14a depicts LC3 II protein expression in starved Min6 cells with and without bafilomycin A1 treatment and Figure 5-

14b illustrates the effect of bafilomycin A1 on LC3 II protein expression in starved Min6 cells. In all LC3 II Western blots, LC3 II protein expression was normalized to α-tubulin protein expression in order to control for well loading.

n=3 p = 0.046 0.6 0.5

0.4 tubulin

- 0.3 α 0.2

0.1 LC3 / LC3 II protein expression 0 Baf 4h no Baf Baf 4h no Baf RGS4 WT RGS4 ENAA Construct expressed and bafilomycin A1treatment

Figure 5-13(a): LC3 II protein expression in fed Min6 cells overexpressing RGS4 constructs, with and without bafilomycin A1 treatment. LC3 II protein expression was increased when treated with bafilomycin A1 for 4 hours (Baf 4h); this increase was significant when RGS4 WT was co-expressed (p = 0.046). There was an increase in LC3 II protein expression in the presence of bafilomycin A1 in the RGS4 WT sample compared to the RGS4 ENAA sample. All samples normalized to α-tubulin protein expression. Statistical significance assessed by student’s T test. P = 0.298 in two-way ANOVA for all samples. n is number of trials.

n = 3 0.4

with 0.3 LC3 LC3 II protein

without 0.2 -

0.1 bafilomycin A1

expression expression 0 LC3 II expression LC3 expression II

RGS4 WT RGS4 ENAA bafilomycin A1 Construct expressed Figure 5-13(b): The effect of bafilomycin A1 on LC3 II protein expression in fed Min6 cells. Bafilomycin A1 treatment affected RGS4 WT-overexpressing Min6 cells more highly than RGS4 ENAA-overexpressing cells. RGS4 WT-overexpression led to a large increase in LC3 II protein expression. However, the results are not statistically significant (assessed by one- way ANOVA). n is number of trials.

n=4 1.2 1

0.8

tubulin -

α 0.6 0.4

LC3 LC3 / II 0.2 protein expression 0 Baf 4h Baf 2h no Baf Baf 4h Baf 2h no Baf RGS4 WT n=3* RGS4 ENAA Construct expressed and bafilomycin A1 treatment

Figure 5-14(a): LC3 II protein expression in starved Min6 cells overexpressing RGS4 constructs, with and without bafilomycin A1 treatment. LC3 II protein expression was highest when cells overexpressing RGS4 WT were treated with bafilomycin A1 for 4 hours and lowest when cells overexpressing RGS4 ENAA were not treated with bafilomycin A1. Generally, it appears as though cells overexpressing RGS4 ENAA had the lowest expression of LC3 II and cells expressing RGS4 WT expressed LC3 II most highly. All samples normalized to α-tubulin protein expression. *n=4 for all samples except RGS4 WT samples; n=3 for these samples. n is number of trials.

n = 4 1 0.8

0.6 with

bafilomycin 0.4 LC3 LC3 II protein

- 0.2 A1

without 0 Baf 4h Baf 2h Baf 4h Baf 2h

LC3 II expression LC3 expression II RGS4 WT n = 3* RGS4 ENAA

bafilomycin A1 Construct expressed and bafilomycin A1 treatment expression expression

Figure 5-14(b): The effect of bafilomycin A1 on LC3 II protein expression in starved Min6 cells. Bafilomycin A treatment affected RGS4 WT-overexpressing Min6 cells most highly. RGS4 WT-overexpression led to a large increase in LC3 II protein expression. However, the results are not statistically significant (assessed by two-way ANOVA). *n=4 for all samples except RGS4 WT samples; n=3 for these samples. n is number of trials.

6 Discussion

6.1 RGS4 Localization in Relation to Autophagosomes in Min6 Cells

The hypothesis for this thesis was that Min6 cells make a good cell model to study the effects of RGS4 and Gαi3 on autophagic flux. We thus set out to confirm findings from other groups showing that we could induce and measure induction of autophagy in our

Min6 cell line (84; 85). As expected, Min6 cells exposed to nutrient-deprived conditions showed increased numbers of LC3 punctae, a marker of autophagic flux. This increase was significant in both bafilomycin A1-treated and untreated Min6 cells; however, owing to its role as an inhibitor of autophagosome breakdown, bafilomycin A1 treatment led to increased absolute counts of LC3 punctae in our system. Secondly, as another index of autophagic activity, we measured LC3 II protein expression from Min6 cells transfected with a control vector. LC3 II levels provide a good marker of autophagy since LC3 I must mature into LC3 II in order for the autophagosome to form, and thus LC3 II is considered to be a good marker of late-stage autophagy and mature autophagosomes. Consistent with Min6 cells containing the appropriate machinery for upregulation of autophagy, nutrient- deprivation increased LC3 II expression in the presence and absence of Bafilomycin A1.

Together, these data suggested that Min6 cells contained most of the relevant autophagic signaling machinery and that this pathway responded properly to nutrient-deprivation stimuli in our hands.

We next tested whether RGS4 and one of its physiologic G-protein targets, Gαi3, were properly localized within Min6 cells. Indeed, RGS4 localized to the plasma membrane and to intracellular membrane pools as had been previously observed for HEK cells. Also consistent with previous observations, RGS4 WT and ENAA localization was similar while the palmitoylation mutant RGS4 C2A showed a markedly different localization pattern. Due to

lack of its palmitoylation on Cys2, the RGS4 C2A trafficking dynamics are altered such that it undergoes less internalization on intracellular membranes (punctae) and stronger plasma membrane localization. Together, these data suggest that Min6 cells contain all of the cellular machinery (e.g. proper DHHC expression and activity) required for the correct localization of RGS4 WT. These data are important because although other groups had expressed RGS4 in Min6 cells, not study had confirmed its proper localization. Also, as expected, the ENAA mutation showed similar localization as the WT protein, consistent with our previous observations that the primary determinants of RGS4 localization lie with domains outside the G-protein binding (GAP) domain. Notably, Gαi3 (RC) also localized in the expected manner with strong staining at the plasma membrane and within intracellular membranes (punctae) of Min6 cells. Importantly, Gαi3 (RC) and RGS4 appeared to be colocalized on a large number of these intracellular punctae, consistent with the notion that they may both populate the same intracellular signaling domains within Min6 cells. Beclin1 and Atg12 also localized predominantly to intracellular domains in Min6 cells, as expected.

Plasma membrane localization for these autophagy markers would have been surprising since autophagy occurs intracellularly. Distinct punctae of Beclin1 and Atg12 were seen and these are typically thought to be associated with autophagosome structures.

RGS4 punctae distribution next provided some insight into the effects of Beclin1 and

Atg12 on RGS4 localization. In distribution quantification of only cells containing visible punctae (Figure 5-6), Beclin1 overexpression led to a scattered RGS4 punctae phenotype

(punctae distributed stochastically throughout the cell), whereas Atg12 overexpression led to a more clustered RGS4 punctae phenotype (punctae appeared to be larger, more centrally located and coalesced) and both of these phenotypes were significant and striking.

A similar result was seen in the punctae distribution of all cells (Figure 5-7) obtained by our

lab in HEK cells in the past. Not only did RGS4 punctae appeared clustered in the Atg12- overexpression samples, Atg12 punctae also appeared clustered suggesting that Atg12 overexpression results in global changes to the intracellular membrane pools and thus may be potentially confounding to the interpretation of autophagic flux data. Importantly, the unusual clustering phenotype caused by Atg12 overexpression is not one reported in the literature, and while the mechanism for this process is not understood, this work provides a cautionary note to others who wish to use this as a marker. For our own work we decided to focus on Beclin1 as a marker, since this clone did not appear to have the same dramatic effect on intracellular membrane homeostasis.

RGS4 punctae distribution in all cells did not show RGS4 punctae forming in all cells; in fact, every condition tested had at least 15% of cells that did not have any punctae at all.

This was not unexpected, since not all cells will be undergoing autophagy at all times and in addition, transfection efficiency was never 100%. In the future, starvation could be used as a method to induce autophagy in these cells before observing their punctae ratios. As expected, RGS4 C2A conditions had a majority of cells that did not have RGS4 punctae, but surprisingly, there were still some cells where RGS4 C2A localized away from the plasma membrane to form punctae, especially when Atg12 was overexpressed. This result made us further suspicious of the unusual phenotype caused by Atg12 overexpression, and led us to be cautious about further analysis of Min6 cells overexpressing Atg12.

An unexpected observation was that the co-expression of RGS4 ENAA and Beclin1 induced somewhat more punctae versus co-expression of RGS4 WT and Beclin1. Since it was hypothesized that RGS4 WT would induce increased autophagy (compared to ENAA) and the punctae observed are putative autophagosomes, we may have expected that there would be more punctae under the RGS4 WT conditions than the RGS4 ENAA conditions. As

the opposite was documented, this was the first suggestion that RGS4 may not have the same robust activity as an autophagic regulator in Min6 cells as it does in other culture cell models.

As mentioned above, the observed frequency of colocalization between RGS4 and

Gαi3 within punctae may be indicative of their cooperative role in autophagic regulation.

We expected RGS4 WT and RGS4 ENAA to colocalize with Beclin1 with similar frequency, since RGS4 ENAA should not colocalize any differently than RGS4 WT. However, we expected RGS4 C2A to colocalize with Beclin1 very infrequently due to its decreased ability to localize to intracellular pools. We found that RGS4 WT and Beclin1 colocalized to a similar extent as RGS4 ENAA and Beclin1, and that both RGS4 WT and RGS4 ENAA colocalized with Beclin1 significantly more frequently than RGS4 C2A, exactly as expected

(Figure 5-8(a)). Similarly, we anticipated that RGS4 WT and ENAA would colocalize with

Gαi3 (RC) with similar frequency, but that RGS4 C2A would not, for the same reasons listed above. RGS4 WT did in fact colocalize with Gαi3 (RC) more frequently than RGS4 C2A did, in a statistically significant manner, but surprisingly, RGS4 ENAA did not colocalize as well with

Gαi3 as RGS4 WT (Figure 5-8(b)). Since Gαi3 (RC) is a constitutively active mutant, it is possible that there is a small contribution of the G-protein binding domain of RGS4 to its localization in Min6 cells that would explain these data. The final analysis of frequency of colocalization was done between Gαi3 (RC) and Beclin1. Because of previous studies showing that Gαi3 acts on autophagy (67; 68; 72), we postulated that Gαi3 (RC) and Beclin1 would colocalize frequently, independent of the RGS4 construct co-expressed. This hypothesis proved to be correct, as Gαi3 (RC) and Beclin1 colocalized very frequently (with

6-8 punctae per cell), no matter the RGS4 construct expressed (Figure 5-8(c)). Generally, of all three colocalization groups examined, Gαi3 (RC) and Beclin1 colocalized the most

frequently, and RGS4 and Gαi3 (RC) as well as RGS4 and Beclin1 colocalized much less frequently per cell (both groups had about 0-1 punctae per cell). This low colocalization incidence may be indicative of either RGS4 participating within a very narrow time window during the assembly and regulation of Beclin1 punctae or that RGS4 plays a relatively minor role in the regulation of autophagic flux in Min6 cells.

While frequency of punctae colocalization counts gave us information about how often our proteins of interest were colocalizing, Pearson colocalization coefficient analysis told us how well our proteins were colocalizing (Figure 5-9). Since RGS proteins act as GAPs on G-proteins, the colocalization of Gαi3 (RC) and RGS4 (either ENAA or WT) was anticipated to be relatively strong. PCC was positive, indicating colocalization was occurring, but the

PCC value was relatively low. Perhaps these data reflect a “hit-and-run” model for RGS4, where it is found associated with Gαi3-containing endosomes for a brief period of regulation before shifting to another intracellular compartment. Colocalization analysis between Gαi3

(RC) and RGS4 C2A actually resulted in a negative PCC, which was expected since RGS4 C2A localizes primarily to the plasma membrane of the cell. By contrast, PCC analysis between

Gαi3 (RC) and Beclin1 was very strong in all conditions – no matter which RGS4 construct was expressed. This strong colocalization was also consistent with what was observed in the frequency of colocalization punctae counts, since it can be postulated that proteins that colocalize frequently may also colocalize strongly (Figure 5-8(c)). This was an expected result, as before, since none of the RGS4 constructs we used are expected to change Gαi3

(RC) localization. PCC analysis between RGS4 constructs and Beclin1 always gave a small, positive PCC, similar to the PCC between RGS4 and Gαi3 (RC). We next proceeded to test whether RGS4’s localization within these autophagy-regulating domains had significant functional consequences in our Min6 cell line.

6.2 The Effect of RGS4 on Autophagic Flux in Min6 Cells

Western blotting experiments showed that there was a consistent trend toward an increase in autophagy in the presence of RGS4 WT in Min6 cells, however, these data did not reach statistical significance in any of the assays used. Specifically, when RGS4 WT was overexpressed in the Min6 cells, there was a very small decrease in phospho-p70S6K compared to RGS4 ENAA. We had predicted that if RGS4 was acting to promote autophagy via inhibiting mTOR, then we would see a much greater decrease in the phospho-p70S6K signal. From these data, we concluded that RGS4 did not have a significant direct effect on mTOR activity and therefore we considered other possible sites of autophagic regulation that lie downstream of the mTORC1 master regulator complex.

One such point of regulation is Beclin1, a signaling node for autophagosome initiation. Beclin1 is normally complexed with Bcl-2 to keep it in the quiescent state.

Activation of autophagic machinery results in the phosphorylation of Bcl-2, subsequent release of Beclin1 and initiation of autophagosome initiation. Thus, phospho-Bcl-2 is a robust surrogate marker of autophagic initiation. We tested phospho-Bcl-2 protein expression under the influence of WT and ENAA RGS4 constructs, expecting RGS4 WT overexpression to result in higher phospho-Bcl-2 expression if it were indeed an activator of autophagy via regulation of the Beclin1-Bcl-2 axis. As expected, nutrient deprivation led to increased phospho-Bcl-2 levels showing that the pathways were responding appropriately to autophagic stimuli. These data were consistent with previous reports in the literature

(24). However, no difference between phospho-Bcl-2 levels were detected between RGS4

WT and ENAA constructs in either state, suggesting that RGS4 and Gαi3 may not play an important role in modulating the Beclin1-Bcl-2 axis in Min6 cells.

RGS4 did not have a strong effect on phosphorylation of Bcl-2 nor mTOR activity. As discussed in section 1.1.2, Bcl-2 inhibits Beclin1’s ability to participate in the formation of the autophagosome; however, other mechanisms disrupt the Bcl-2-Beclin1 interaction other than phosphorylation of Bcl-2 (for example, HMGB1 and Bnip3 can compete with Bcl-

2 for Beclin1 interaction). Therefore we next wanted to determine whether RGS4 may have an effect on proteins directly involved in the formation of the autophagosome, i.e. downstream of mTOR activity and Bcl-2 activity. LC3 II is a good marker of mature autophagosomes being formed, because LC3 II is inserted into the autophagosomal membrane and even gets degraded by lysosomes when the mature autophagosome binds to the lysosome. Upon autophagosomal binding to the lysosome, any LC3 II that is inside the autophagosome will get degraded, making it difficult to assess the number of mature autophagosomes formed and therefore autophagic flux. Bafilomycin A1 is a drug that prevents autophagosomes from binding to lysosomes, meaning that LC3 II will not get degraded and the total amount of autophagy that has occurred can be measured. In experiments done in both the fed and starved state, the amount of LC3 II that would have been degraded without bafilomycin A1 was plotted in Figures 5-13(b) and 5-14(b).

Consistent with our hypothesis, LC3 II protein expression in both the fed and starved states in the presence of bafilomycin A1 treatment was consistently higher when RGS4 WT was expressed compared to RGS4 ENAA controls. However, this result was not statistically significant, perhaps due to an unusually high level of variability in our system. Notably, in the absence of bafilomycin A1 treatment, it was more difficult to interpret the relative effects of RGS4 WT and ENAA because steady-state levels of LC3 II protein were a reflection of its synthesis and degradation via the autolysosomes under this condition. For this reason autophagic flux is often examined by comparing the bafilomycin-treated with vehicle-

treated samples (as in Figures 5-13(b) and 5-14(b)). However, these analysis were still not sufficient to show significant differences between these conditions.

6.3 Conclusions

Taken together, these data show that RGS4 expression in Min6 cells was not able to induce robust effects on autophagic signaling, despite the fact that the protein appears to be correctly expressed and localized in this cell model. These data were somewhat unexpected since: i) genetic deletion of RGS4 results in deficient autophagic signaling in murine pancreatic beta cells; and ii) RGS4 expression inhibits Gαi3-mediated autophagy in other culture cells models (i.e. HEK293 cells). We therefore propose the following reasons for these possible discrepancies. Gαi3 is known to be a key regulator of autophagy in many different cell types (68; 71). It is possible, therefore, that the effects of RGS4 on autophagic signaling observed in other settings require significant constitutive activity of the Gαi3 signaling pathway, and its proper coupling to the metabolic homeostatic machinery. If, for example, Min6 cells contained an insufficient level of Gαi3 constitutive activity to inhibit autophagy, or if the available Gαi3 pool in Min6 cells was not optimally coupled to nutrient- sensing pathways, it might be expected that RGS4 would have only a modest effect on autophagic flux in this system (86). Also, as discussed above, Min6 cells already have a relatively high level of RGS4 mRNA expression relative to other cell lines. Thus, it may be that the endogenous RGS4 expression levels in Min6 cells are sufficient to attenuate Gαi3 signaling and therefore addition of exogenous signaling fails to produce a robust physiologic

response. As discussed below, testing these hypotheses would require development of a system for inhibiting RGS4 expression and/or function in the Min6 cell line (74; 87).

6.4 Limitations

There are several possible limitations to our study design. Min6 cells are a mouse pancreatic beta cell line and the characteristics of the cells may not represent mechanisms that will occur in mouse beta cells. This is a function of the cell line having been immortalized and cultured for numerous passages during which time genetic drift away from the islet genotype may occur. Additionally, because we used a cell line and not ex vivo tissue or in vivo experimentation, we must consider the possibility that if these experiments were replicated in isolated pancreatic islets or in mice, the results attained may be very different. This could be a result of altered physiology of the beta cells, but it could also be a result of paracrine signaling from the surrounding cells or organs. For example, since the beta cells are surrounded by other cell types in the islets, paracrine signaling could cause changes in intracellular signaling and autophagic flux. Or, since the neuronal system regulates signaling throughout the body (and specifically, the hypothalamus regulates glucose effectiveness (88)), perhaps neural signaling resulting in insulin secretion alteration could also lead to RGS4 up- or down-regulation.

Other studies have shown that the passage number of the Min6 cell line may affect the cells’ physiology (89; 90). Although the cells were used between passages 19 and 38, as suggested by the groups who published the studies, it is possible that in our particular strain of Min6 cells, the optimal passage number was different. Min6 cells are widely used

because they secrete insulin in response to glucose stimulation (91). Experimental passage number could have been optimized by testing the cells for their ability to undergo glucose- stimulated insulin secretion at various passages, or prior to performing experiments.

Another important limitation is the overexpression of RGS4 in the Min6 cells.

Overexpressing any protein in a cell line could lead to the activation of other pathways in the cell – for example, additional RGS4 protein being produced in Min6 cells could lead to an increase in autophagic flux, as hypothesized, but could also activate a pathway that in turn attenuates the initiation of autophagy. RGS proteins play a large role in intracellular signaling especially since GPCRs are so common; it is therefore difficult to know whether a pathway that RGS4 activates may actually work to inhibit the pathway being studied.

Similarly, overexpressing any protein in a cell could lead to a large production of the overexpressed protein and decreased production of endogenous proteins or altered trafficking of proteins, which may modify the pathway being examined; it is difficult to glean meaningful physiologic insights when genes and proteins are expressed at nonphysiologic levels. Nevertheless, cells are perturbed regardless of how the pathway is disrupted and no experimental method is without its caveats.

Other groups showed that Min6 cells have high RGS4 mRNA expression (74) and our laboratory also showed that mouse pancreatic islets have high RGS4 mRNA expression.

However, the protein expression in the cells has not been elucidated. RGS4 is a dynamic protein with a short half-life in mammalian cells (76; 92). This is another limitation to our project; it is possible that despite having high RGS4 mRNA expression, there is low RGS4 protein expression. However, we did not assess protein expression of RGS4 for the reasons mentioned above.

Although we examined whether RGS4 colocalized to Gαi3 and some autophagosome markers such as Beclin1, determining whether RGS4 colocalized to other intracellular markers such as the endoplasmic reticulum, Golgi complex, late endosomes, autophagosomes, etc. would have provided insight into where along the autophagy pathway RGS4 may play a role. Naturally, there are implicit limitations in doing these experiments, for example, overexpressing many marker proteins (for intracellular organelles) in the cell may alter the natural physiology of the cell and perhaps also change intracellular trafficking pathways; additionally, many of these intracellular compartment markers traffic between various organelles and so that would have to be taken into account.

A further restriction to our study is that a positive control was not included for our phospho-p70S6K Western blots. Since these experiments were not consistent with our hypothesis, it is important to include a positive control to ensure that the Min6 cells will deliver the expected phenotype. Had a positive control been included (and behaved as expected) and the results were still inconsistent with our hypothesis, we could rest assured that the Min6 cell line has the appropriate machinery for the mTOR pathway tested.

Without a positive control, we cannot be certain that these cells use mTOR to inhibit autophagy and activate phospho-p70S6K as other cell types do.

6.5 Future Directions

In this MSc thesis, I have demonstrated that RGS4 does not significantly alter autophagic flux in Min6 cells. Gαi3 has been shown to inhibit autophagy in some tissues.

Through RGS4’s proposed inhibition of Gαi3 in Min6 cells, we expected to elucidate a mechanism for the Gαi3-mediated autophagy inhibition. Additional studies can be carried out to elucidate the mechanism through which Gαi3 inhibits autophagy and whether RGS4 has an effect on this process. These studies can be done in other cell lines, such as INS-1 cells or RIN cells (rat insulin-secreting cell lines), or in primary beta cell culture.

In order to fully elucidate underlying mechanisms for the effect of RGS4 on Gαi3 and beta cell autophagy, we propose the following experiments. Firstly, Gαi3 colocalized strongly with the autophagy markers Beclin1, but RGS4 colocalized less well with these markers. We usually think of RGS4 acting downstream of Gαi3 signaling but perhaps RGS4 has a role upstream of Gαi3. Further studies would be required to elucidate any possible activity of RGS4 alternative to Gαi3 signaling in Min6 cells. Secondly, since RGS4 mRNA is highly expressed in Min6 cells (74), the phenotypes we were seeing may not have been statistically significant because RGS4 may have reached a ceiling in its functionality; any more RGS4 being produced may not have altered any intracellular signaling pathways.

RGS4 protein expression should be quantified in the Min6 cells to determine whether RGS4 mRNA gets degraded quickly in Min6 cells and allowing us to determine whether RGS4 may have indeed reached a ceiling in its functionality when overexpressed. Furthermore, studies knocking down RGS4 in Min6 cells should be pursued as they would provide insight into the relationship between RGS4 and Gαi3 without the caveat of possibly reaching the height of peak protein expression. These knockdown studies should include glucose-stimulated insulin secretion assays, as autophagy has been shown to be a regulator of insulin secretion

(51). An alternative to RGS4 knockdown is RGS4 inhibition; potent pharmacological inhibitors of RGS4 such as CCG-50014 or CCG-4986 exist (93; 94). Should the knockdown or

RGS4 inhibition studies show that a decrease in RGS4 activity causes a significant decrease in autophagy, then experiments measuring insulin secretion in RGS4 knockout mice can be carried out – giving a translational approach to the study.

Additionally, it would be interesting to determine which pool of Gαi3 might alter autophagic flux in Min6 cells, given that the intracellular pool of Gαi3 has been shown to play a role in regulation of autophagy in some cell lines already studied (liver cells, HT-29 colon cells, and HEK cells (67; 68)). Colocalization of both RGS4 and Gαi3 to various intracellular organelles may provide insight into the roles of both the Gαi3 pool and RGS4 in autophagy. Many methods have been developed to analyze this colocalization (95).

Subcellular fractionation (density-gradient centrifugation to separate certain organelles into layers and then analysis of each layer under the electron microscope) would have allowed us to quantify the number of autophagosomes associated with various organelles, with and without RGS4 overexpression (96). Alternatively, intracellular compartments can be identified with the use of markers such as LysoTracker Red dye (which is retained in acidic subcellular compartments such as the lysosome or late endosome) (97), LAMP1 (a transmembrane protein which resides primarily across lysosomal membranes) (98), Pep12

(an endosomal marker) (99), TGN 38 (an integral membrane protein of the trans-Golgi network) (100), and ER Tracker Green (a live-cell stain highly selective for the endoplasmic reticulum) (101). Visualization of these fluorescent-tagged markers along with RGS4-YFP and Gαi3-CFP under the confocal microscope could allow for determination of where in the cell RGS4 and Gαi3 are localizing and determination of autophagic flux as well.

A positive control should be included in the phospho-p70S6K protein expression experiments. Phopsho-p70S6K is a marker for mTOR activity and widely-used inhibitors of mTOR activity are rapamycin or Torin1 drug treatment (102). We performed pilot studies with the rapamycin and Torin1, expecting to see much lower phospho-p70S6K protein expression in the Min6 cells, but the expression of phospho-p70S6K did not change compared to the non-treated cells. It would an interesting future study to determine why the mTOR inhibitors did not work in the Min6 cells.

Our studies examined localization of RGS4, Gαi3, and various autophagy markers in

Min6 cells and we concluded that the three proteins weakly colocalize in most cases. One of the phenotypes observed during these experiments was that depending on the autophagy marker used – Beclin1 or Atg12 – the pattern of putative intracellular autophagosome formation was different and distinct. Beclin1 appeared to cause scattered autophagosome formation throughout the cytosol, while Atg12 caused clustered autophagosome formation intracellularly. Because it was outside the scope of our study, we did not pursue the mechanism behind this vivid pattern difference, and further studies must be carried out in order to determine whether overexpressing different autophagy markers leads to differences in autophagosome formation, independent of RGS4 overexpression.

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8 Appendix

n=1 2.5

1.5

p70S6K Total / S6K -

Protein Expression 0.5 Phospho 0 WT ENAA WT ENAA WT ENAA 5.5mM 12.0mM 24.9mM Construct and Glucose Concentration of Culture Medium

Figure A-1: The effect of glucose concentration in Min6 medium on phospho-p70S6K protein expression when RGS4 WT or ENAA is overexpressed. Mean physiological concentration of glucose in the human body is 5.5mM. Min6 cells are typically kept in a 24.9mM glucose medium (as per a literature search). An optimization experiment was done to determine which glucose concentration resulted in the largest difference in protein expression when Min6 cells were overexpressing RGS4 WT and RGS4 ENAA. The difference in phosphpo-p70S6K protein expression between RGS4 WT-overexpressing Min6 cells and RGS4 ENAA-expressing Min6 cells was most prominent when cells were cultured in 24.9mM glucose medium; it was almost double the difference in phospho-p70S6K protein expression seen when cells were cultured in medium with 5.5mM glucose. n is number of trials.

A) B)

Figure A-2: No crosstalk of eYFP (488nm), DsRed (543nm) or DAPI (405nm) fluorescence occurred. Artifacts from bleed-through of fluorescence emission due to broad bandwidths exhibited by the fluorophores used in these experiments was checked. Min6 cells co- transfected with RGS4 WT-YFP, Beclin1-DsRed or Atg12-RFP, and Gαi3 RC-CFP were visualized prior to every confocal microscopy experiment. A representative sample is shown here. Panel A illustrates potential crosstalk from the 488nm laser, panel B illustrates potential crosstalk from the 543 laser, and panel C illustrates potential crosstalk from the 405nm laser. This control was performed for all confocal microscopy experiments.