Proteomic Analysis of Pp2a Mutants and Pp2a-Related Tumor Virus Proteins

PROTEOMIC ANALYSIS OF PP2A MUTANTS AND

PP2A-RELATED TUMOR VIRUS PROTEINS

Yiwang Zhou

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

PROTEOMIC ANALYSIS OF PP2A MUTANTS AND

PP2A-RELATED TUMOR VIRUS PROTEINS

Yiwang Zhou Master of Science Graduate Department of Molecular Genetics University of Toronto 2015

ABSTRACT

Protein phosphatase 2A (PP2A) is a tumor suppressor, whose function and activity is influenced by mutations of PP2A subunits and PP2A-related tumor virus proteins. In this work, protein-protein interaction changes in the normal PP2A interaction network caused by mutations of PP2A scaffolding A (PPP2R1A) and catalytic C (PPP2CA) subunits have been characterized by AP-SWATH. The results show that the normal function and activity of PP2A holoenzyme may be significantly altered and influenced by these mutations. This study also characterizes the interactomes of several PP2A-related tumor viral oncoproteins, including E4orf4. It is revealed for the first time that ASPP-PP1 complex subunits are among the major interactors of E4orf4, suggesting the involvement of E4orf4 in the regulation of Hippo signaling pathway. The results gained in my M.Sc. work provide a deeper understanding of the consequences of PP2A subunits mutations and the PP2A-dependent and PP2A-independent functions of the PP2A-related tumor virus proteins.

! ii! ACKNOWLEDGEMENT

First and foremost, I would like to thank my supervisor, Dr. Anne-Claude Gingras for taking me as a master student, and for all the time and patience spent in providing me guidance throughout this study. Before joining Dr. Gingras' lab, I had no idea what real scientific research is and how to carry out an independent research project. These two years' experience develops my ability to work and think like a researcher, which is extremely worthwhile for my future career.

I would also like to express my appreciation to the members of Dr. Gingras' lab: Jean-Philippe Lambert for answering my numerous questions and for helping me analyze the SWATH data; Zhen-yuan Lin for teaching me affinity purification and for always being there when I had trouble dealing with the mass spectrometers; James Knight for helping me with data processing and visualization; Frank Liu for solving all the problems I had in ProHits; Wade Dunham and Marilyn Goudreault for helping me find everything I needed in the lab; and the rest of the lab members for assistance through the years. For smoothly carrying out this study, I also want to thank my committee members, Dr. Philip Kim, Dr. Stéphane Angers and Dr. Vuk Stambolic for their guidance, as well as Dr. Philip Branton and Dr. Egon Ogris for their collaboration.

In addition, I am indebted to my parents, who are always standing by me and offering me support and encouragement to pursue my dream. I am also grateful to have Huayun Hou as my roommate. Thanks for accompanying for these two years. Finally and most especially, I would thank to my boyfriend, Jiyuan Yang, for his understanding, support, patience and love during the past two years, no matter how far away we are separated.

! iii! TABLE OF CONTENTS

ABSTRACT...... ii ACKNOWLEDGEMENT...... iii LIST OF TABLES...... vi LIST OF FIGURES...... vii LIST OF ABBREVIATIONS...... ix

CHAPTER 1 INTRODUCTION 1.1 PP2A holoenzyme...... 1 1.2 The function of PP2A as a tumor suppressor...... 6 1.3 Structure-function of the PP2A subunits under study 1.3.1 Scaffolding A subunit, PPP2R1A...... 8 1.3.2 Catalytic C subunit, PPP2CA...... 9 1.3.3 Regulatory B subunit, PPP2R2A...... 10 1.4 PP2A-related tumor virus proteins 1.4.1 SV40 small T antigen...... 11 1.4.2 Polyomavirus middle T antigen...... 12 1.4.3 Adenovirus E4orf4 protein...... 13 1.5 Affinity purification and mass spectrometry...... 14 1.6 Proximity-dependent biotin identification with BioID...... 19 1.7 Quantitative mass spectrometry with the Data Independent Acquisition method SWATH...... 22 1.8 Objectives of this project...... 24 CHAPTER 2 MATERIALS AND METHODS 2.1 Plasmids...... 26 2.2 Cell lines, culture, transfection and collection...... 29 2.3 Affinity purification 2.3.1 Anti-FLAG affinity purification...... 30 2.3.2 Streptavidin affinity purification...... 32

! iv! 2.4 Immunoprecipitation-Western Blot...... 33 2.5 Mass spectrometry 2.5.1 MS/MS...... 34 2.5.2 SWATH...... 35 2.6 Data analysis and visualization 2.6.1 DDA data search...... 36 2.6.2 SAINT analysis...... 37 2.6.3 SWATH data analysis...... 38 CHAPTER 3 RESULTS 3.1 Protein-protein interaction changes imparted by PPP2R1A mutations...... 42 3.2 Validation of selected interaction changes for PPP2R1A mutations...... 48 3.3 Protein-protein interaction changes imparted by PPP2CA mutations...... 51 3.4 Validation of the interaction between ANKLE2 and PPP2CA mutants...... 59 3.5 Interacting proteins of PPP2R2A...... 62 3.6 Interacting proteins of PP2A-related tumor virus proteins 3.6.1 SV40 small T antigen interacting proteins...... 67 3.6.2 Polyomavirus middle T antigen interacting proteins...... 72 3.6.3 E4orf4 interacting proteins...... 72 CHAPTER 4 FUTURE DIRECTIONS AND DISCUSSION 4.1 Significance of the work...... 82 4.2 Discussion...... 83 4.3 Future directions...... 90 APPENDIX...... 92 REFERENCES...... 102

! v! LIST OF TABLES

Table 1. PP2A subunits...... 5 Table 2. Plasmids used in this study...... 27 Table 3. Mutations of PPP2R1A...... 43 Table 4. Mutations of PPP2CA...... 52 Table 5. Schematic representation of the various C subunit mutations...... 52 Table 6. Mutations of PPP2R2A...... 63 Table 7. Mutations of E4orf4...... 75

! vi! LIST OF FIGURES

Figure 1. Crystal structure of PP2A and the formation of PP2A holoenzyme...... 3 Figure 2. Workflow of affinity purification coupled with mass spectrometry (AP-MS)...... 16 Figure 3. Model for application of BioID method...... 20 Figure 4. AP-SWATH data analysis pipeline...... 39 Figure 5. Dot-plot representation of protein-protein interaction changes for eight PPP2R1A mutations relative to wild-type PPP2R1A...... 45 Figure 6. Validation of selected protein-protein interaction changes imparted by mutations of PPP2R1A...... 49 Figure 7. Dot-plots representation of protein-protein interaction changes for eleven PPP2CA mutations relative to wild-type PPP2CA...... 54 Figure 8. Validation of interaction changes for ANKLE2 imparted by mutations of PPP2CA...... 60 Figure 9. Characterization of the interacting proteins of wild-type PPP2R2A and PPP2R2A mutants...... 65 Figure 10. Characterization of the interacting proteins of wild-type PPP2R2A and PPP2R2A mutants using BioID...... 68 Figure 11. Characterization of the interacting proteins of wild-type SV40 ST and ST mutant...... 70 Figure 12. Characterization of the interacting proteins of PyMT...... 73 Figure 13. Characterization of the interacting proteins of wild-type E4orf4 and the class I E4orf4 mutant...... 77 Figure 14. Characterization of the interacting proteins of wild-type E4orf4, class I mutant and class II mutants...... 79 Figure 15. Immunofluorescence of Hela cells expressing wild-type PPP2CA and PPP2CA mutants...... 86 figure 1. Expression of FLAG tagged wild-type PPP2R1A and PPP2R1A mutants in HEK293 T-REx cells...... 92

! vii! figure 2. Expression of FLAG tagged wild-type PPP2CA and PPP2CA mutants in HEK293 T-REx cells...... 94 figure 3. Characterization of the interacting proteins of FLAG tagged wild-type PPP2CA and PPP2CA mutants...... 96 figure 4. Expression of FLAG tagged wild-type PPP2R2A and PPP2R2A mutants in HEK293 T-REx cells...... 98 figure 5. Expression of BirA*-FLAG tagged wild-type PPP2R2A and PPP2R2A mutants in HEK293 T-REx cells...... 100

! viii! LIST OF ABBREVIATIONS

AP Affinity purification AvgP Averaged probability CID Collision induced dissociation COSMIC Catalogue of Somatic Mutations in Cancer ctrl control DDA Data-dependent acquisition DIA Data-independent acquisition E4orf4 Early transcription region 4 open reading frame 4 ER Early region FDR False discovery rate HEAT Huntington-Elongation-A subunit-TOR HPLC High Performance Liquid Chromatography IP Immunoprecipitation LC Liquid chromatography LR Late region LT Large T antigen LUMIER Luminescence-based mammalian interactome mapping MLR most likely ratio MS Mass spectrometry MT Middle T antigen PP1 Protein phosphatase 1 PP2A Protein phosphatase 2A PPP Phosphoprotein phosphatase PyMT Polyomavirus middle T antigen S/MRM Selected/Multiple Reaction Monitoring SAINT Significance Analysis of INTeractome SILAC Stable Isotope Labeling by Amino acids in Cell culture ST Small T antigen

! ix! SV40 Simian virus 40 SWATH Sequential Window Acquisition of all THeoretical spectra TPP Trans-Proteomic Pipeline WB Western blot XIC extracted ion chromatography Y2H Yeast-two-hybrid

°C Degrees Celsius µg microgram µl microliter µM micromolar µm micrometer amu atomic mass units cm centimeter Da Daltons eV electron-volt m/z mass to charge ratio min minute ml milliliter mM millimolar ms microsecond ng nanogram nl nanoliter ppm parts permillion rpm revolutions per minute

! x! ! 1!

CHAPTER 1 INTRODUCTION

1.1 PP2A holoenzyme Reversible protein phosphorylation has been widely recognized as one of the most important regulatory mechanisms in eukaryotic cells. Proteins are phosphorylated by kinases and dephosphorylated by phosphatases, which results in altering the properties of those proteins, including their activities, localization, etc.[1]. Phosphorylation of serine and threonine residues is mediated by ~350 kinases[2], but a more limited number of serine/threonine phosphatases antagonize them[3]. How a limited number of catalytic subunits for phosphatases can still target specific substrates has been the topic of many studies, and it is now widely accepted that several members of the evolutionary conserved "PPP" (phosphoprotein phosphatase) subfamily of serine/threonine phosphatases (13 members in human) acquire this specificity in part by their association with non-catalytic subunits that provide localization or substrate recognition clues. In the best-characterized example, the protein phosphatase 1 (PP1) associates with at least 200 validated proteins in mammalian cells as dimers or trimers, by recognizing mutually exclusive short linear motifs on these interactors[4]; these interactors help bringing the phosphatase in the vicinity of the substrates, dock to the substrate and sometimes block substrate-binding channels, functioning in this last case as inhibitors.

Together with PP1, protein phosphatase 2A (PP2A) is a widely expressed Ser/Thr phosphatase, accounting for a large proportion of the total Ser/Thr phosphatase activity in the cell. Through regulation of multiple signaling pathways, PP2A is involved in controlling many essential aspects of biology, such the cell cycle, cell growth, apoptosis, etc.[5-7].

Like PP1, PP2A does not function in isolation in cells: it is most often present as a heterotrimer. The trimeric holoenzyme PP2A is composed of a catalytic C subunit (PP2A C; two genes, PPP2CA and PPP2CB, exist in mammals), a scaffolding A

! ! 2! subunit (PP2A A; two genes, PPP2R1A and PPP2R1B are expressed in humans), and one of many regulatory B subunits (PP2A B) (Fig. 1a). The PP2A B subunits can be classified into four structurally unrelated families: B, B', B'' and B'''[5, 6] (subunit classification is shown in Table 1). Multiple families, isoforms, and splice variants of the PP2A B subunits allow (together with the two catalytic and two scaffolding subunits) the combinatorial formation of more than 60 different PP2A holoenzymes[8]. The PP2A trimeric holoenzyme is thought to be assembled in two steps. First, one of the two isoforms of PP2A A and C subunits associate to generate the PP2A core dimer. In order to gain full activity towards specific PP2A substrates, this core dimer then binds to one PP2A B subunit to yield the trimeric holoenzyme[5-7, 9] (Fig. 1b). Isoforms for either PP2A A and C subunits have high sequence similarity[10-13]. Although PP2A B subunits within a same family (B, B’, B’’, B’’’) also exhibit sequence similarity, PP2A B subunits from different families have no sequence homology[5, 6]. Based on such variety, PP2A B subunits virtually determine the substrate specificity and localization of PP2A holoenzymes[9].

The catalytic subunits of PP1 and PP2 have remained highly constant during the course of evolution and may be the most conserved among all known enzymes[14]. Studies of PP1 across different species have shown that the amino sequence of PP1 C subunits from mammals and Drosophila shared more than 90% overall identity. The corresponding PP1 C subunits in yeast and Aspergillus are over 80% identical to the mammalian PP1 C. PP2A is also well conserved[15]. For example, the α-isoform of the PP2A C subunit from human and rabbit are 100% identical and the β-isoform shares 99.7% identity between these species[16]. The remarkable conservation of the catalytic subunits of protein phosphatases may reflect the fact that they play an essential role in regulating cellular functions[14]. The A subunits of PP2A are also highly conserved during evolution and the α-isoform of PP2A A subunit has a similar changing rate with histone H4, one of the most conserved protein known so far. Although PP2A B subunits have diverse structures and substrate specificity, B subunits of the same family from different species exhibit some identity. Structural

! ! 3!

Figure 1. Crystal structure of PP2A and the formation of PP2A holoenzyme. (a) PP2A is composed of a scaffolding A subunit (red), a catalytic C subunit (blue) and one of many regulatory B subunits (yellow). The PP2A B subunit shown here is

PPP2R5A. Structure solved by Xu, et al.; Cell (2006) 127:1239-1251 (image from PDB

Japan). (b) PP2A C subunit first binds to A subunit to form the core dimer of PP2A. Then one of the B subunits interacts with this core dimer through its association with PP2A A at the other end, making the PP2A holoenzyme.

! ! 4!

! ! ! a

C subunit

A subunit

B subunit

! b

C C B C

A A A B

PP2A core dimer PP2A holoenzyme ! ! ! ! ! ! ! ! ! ! ! !

! ! 5!

Table 1. PP2A subunits Subunit function Family Protein Isoform Scaffolding A subunit PPP2R1A Aα PPP2R1B Aβ Catalytic C subunit PPP2CA Cα PPP2CB Cβ Regulatory B subunit B (B55) PPP2R2A Bα PPP2R2B Bβ PPP2R2C Bγ PPP2R2D Bδ B' (B56) PPP2R5A B'α PPP2R5B B'β PPP2R5C B'γ PPP2R5D B'δ PPP2R5E B'ε B'' PPP2R3A B''α PPP2R3B B''β PPP2R3C B''γ B''' STRN STRN3 STRN4

! ! 6! studies of human B55α subunit and the yeast ortholog Cdc55 reveal that they have a high degree of similarity, with approximately 56% identity in their crystal structures[17].

1.2 The function of PP2A as a tumor suppressor Dysregulation of the balance between protein phosphorylation and dephosphorylation plays an important role in cancer initiation and maintenance. Abundant evidence has supported that kinases are often mutated to active, oncogenic forms. In addition to kinases, recent findings have also pointed out the importance of protein phosphatases in malignant transformation. As a major Ser/Thr phosphatase, PP2A has been demonstrated to function as a tumor suppressor[8, 18-23]. Convincing evidence has been provided to show that suppression of PP2A activity can cooperate with other oncogenic changes to cause transformation of various cell types[8].

The first line of evidence illustrating the function of PP2A as a tumor suppressor came from the studies of chemical and protein inhibitors of PP2A, including okadaic acid (OA), CIP2A, I1PP2A/I2PP2A, etc.[8, 19, 23]. OA is a tumor promoter that can stimulate premature meiosis and mitosis[5], and increased expression of several proto-oncogenes such as c-fos and c-jun[24], both of which will contribute to the promotion of carcinogenesis[25, 26]. As an inhibitor of PP2A, the experiments with OA suggested that PP2A plays a negative role in regulating cell growth [27]; however, it needs to be mentioned that OA, like all other chemical PP2A inhibitors identified to date, inhibit not only PP2A (all holoenzymes), but also its closest relatives PP4 and PP6 and in many instances other enzymes of the PPP family, including PP1[28]. Structural analyses of phosphatase catalytic subunits help explain this lack of specificity: all these compounds interact at the phosphatase active site, which is the most conserved area of these phosphatases. Results solely based on these chemical inhibitors therefore need to be interpreted with caution.

By contrast to the low intrinsic specificity of chemical inhibitors to the catalytic

! ! 7! subunits of PP2A, protein inhibitors have the potential to bind to surfaces specific to one but not another enzyme. For example, CIP2A (cancerous inhibitor of PP2A) selectively targets PP2A to inhibit its phosphatase activity towards c-Myc, resulting in the increased phosphorylation of c-Myc as well as the reduction in its degradation[29]. CIP2A expression is upregulated in transformed cell lines and cancer tissue samples[8], which correlates with the enhanced stability and overexpression of c-Myc in a wide variety of human cancers, suggesting one more link between PP2A and cancer[30]. I1PP2A and I2PP2A are two other protein inhibitors of PP2A activity toward several phosphorylated substrates[31]. Although the function of I1PP2A and I2PP2A remain incompletely understood, it has been proposed that the inhibition of PP2A by I2PP2A stimulates the activity of the MEK-ERK-MAPK pathway and c-Jun phosphorylation[32, 33]. Defects in the MEK-ERK-MAPK pathway have been identified in many human cancers, and lead to uncontrolled growth of the tumor cells[34, 35]. Activation of c-Jun by phosphorylation is required during tumor initiation and progression[36]. The identification of these PP2A inhibitors in contributing to cancer development contributed bolstering the role of PP2A as a tumor suppressor.

Alteration of PP2A function by mutations in specific PP2A subunits such as the scaffolding A subunit (PPP2R1A and PPP2R1B) has also been detected in several cancers. The earliest study has reported somatic mutations of PPP2R1B in 15% of primary lung tumors, in 6% of lung tumor-derived cell lines, and in 15% of colorectal carcinomas[37]. Further research also detected somatic alterations of PPP2R1B in colon and breast cancers[38-40]. Although at a low frequency, somatic mutations of PPP2R1A have also been identified in a variety of primary human tumors[38, 41, 42]. Biochemical studies showed that these cancer-associated PP2A scaffolding A subunit mutants were defective in binding to other PP2A subunits, including PP2A B' and C subunits, resulting in altered formation of the PP2A trimeric holoenzyme[43, 44]. Taken together, the mutations of PP2A A subunits cause the dysfunction of PP2A by preventing the formation of PP2A holoenzymes, which suggests that PPP2R1A and

! ! 8!

PPP2R1B act as tumor suppressor genes.

The last clue indicating the function of PP2A as a tumor suppressor came with the discovery that PP2A is the target of several viral oncoproteins, such as the small T antigen (ST) of two transforming DNA tumor viruses, simian virus 40 (SV40) and polyomavirus[18]. The ST disrupts PP2A by binding to the A subunit but not the C subunit, resulting in the displacement of specific PP2A B subunits[45-47]. The loss of B subunits further leads to the inhibition of PP2A activity towards certain substrates, resulting in enhanced phosphorylation of these proteins which are involved in the regulation of cell growth or cell proliferation[8]. For instance, the expression of SV40 ST can stimulate cell transformation through inhibiting the dephosphorylation of Akt and c-Myc by PP2A[48, 49]. The activation of Akt and c-Myc by hyperphosphorylation represent frequent alterations observed in human cancer cells[30, 50]. Other tumor virus proteins, including the polyomavirus middle T antigen (PyMT) and the adenovirus E4orf4 protein, also alter PP2A activity, and will be discussed later in Chapter 1.4.

1.3 Structure-function of the PP2A subunits under study 1.3.1 Scaffolding A subunit, PPP2R1A PPP2R1A is the α-isoform of the PP2A scaffolding A subunit. This isoform is ubiquitously expressed in all normal tissues and is typically 10-100 times more abundant than the β-isoform PPP2R1B[12, 51]. It contains 15 repeated HEAT (Huntington-Elongation-A subunit-TOR) motifs, each of which consisting of 39 amino acids[12, 52, 53]. These HEAT motifs generate a curved and hook-like helical structure for PPP2R1A[52, 54, 55], which acts as a structural assembly base to bind the C subunit and the B subunits[20]. The PP2A B and C subunits interact with PPP2R1A at different regions. The HEAT motifs 11-15 form strong hydrogen bonds and hydrophobic interactions with PP2A C subunits, while HEAT motifs 2-7 have loose interaction with different PP2A B subunits and no interaction with C subunit[9, 55-58].

! ! 9!

There are 107 mutations of PPP2R1A reported so far in COSMIC (Catalogue of Somatic Mutations in Cancer). Among these somatic mutations, 60 are located in the subunit B binding region of PPP2R1A, and 22 are within the subunit C binding region. These mutations may cause significant changes to the normal function of PP2A by influencing the interaction between PPP2R1A and PP2A B/C subunits.

1.3.2 Catalytic C subunit, PPP2CA PPP2CA is the α-isoform of the PP2A catalytic C subunit. It shares 97% sequence identity with the β-isoform PPP2CB and is ubiquitously expressed in almost every tissue[20]. PPP2CA consists of seven exons and six introns. Exons 2-6 are involved in substrate binding and catalysis. Exons 1 and 7, however, serve to regulate the interaction between PPP2CA and PP2A A/B subunits[59]. The C-terminal tail of PPP2CA ("T304-PDYF-L309") is uniquely conserved from yeast to human[60]. It harbors extensive post-translational modifications (Leu309 carboxymethylation; Thr304 and Tyr307 phosphorylation)[61-65]. Although as mentioned above in the structure of PPP2R1A, the PP2A B subunits bind to the C subunit through its interaction with the scaffolding A subunit, both biochemical and structural studies have highlighted the importance of the post-translational modifications of the PPP2CA C-terminal tail in regulating the dynamic exchange of the B subunits, which influences the specificity of PP2A holoenzymes[9, 56].

Carboxymethylation of Leu309 is catalyzed by LCMT1 (leucine carboxyl methyltransferase 1)[62, 64] and is reversible through the function of phosphatase methylesterase PME-1[66, 67]. Leu309 methylation is specifically required in recruiting B subunits to PP2A core dimer. However, regulatory subunits from other subfamilies, including B', B'' and B''', have apparently no preference for the methylation at Leu309 or not[68-77]. Phosphorylation of Thr304 and Tyr307 was reported to be catalyzed by several kinases, and the dephosphorylation process can be accomplished by PP2A itself[61]. In contrast to Leu309 methylation, phosphorylation at these two sites was suggested to be associated with PP2A inactivation[60].

! ! 10!

However, the consequences of the phosphorylation events are still not clear. The phosphorylated sites also act in concert with another functional element in PP2A, the β12-β13 loop that includes an arginine at position 268. Expression of PPP2CA R268E in NIH3T3 cells induces a massive increase in cell volume and the formation of large, irregularly shaped nuclei. This phenotype is most likely dependent on the interaction between PPP2CA and B subunits since only the PPP2CA mutations (R268E and R268E/T304A/Y307F) that maintain the interaction with B subunits cause the severe phenotype[78]. All these observations suggest the important roles PPP2CA C-terminal tail and R268 play in keeping the normal function of PP2A holoenzymes.

1.3.3 Regulatory B subunit, PPP2R2A PPP2R2A is the α-isoform of the PP2A B55 regulatory subunits. Structural analysis of the four isoforms in the B55 subfamily revealed that PPP2R2A, PPP2R2B, PPP2R2C, and PPP2R2D only have minor differences in their structures[79]. Therefore, PPP2R2A serves as a good model to study the substrates binding sites in regulatory subunits from PP2A B55 family.

The resolved crystal structure of PPP2R2A shows that it is a seven-bladed β-propeller protein. Each of the blades consists of four anti-parallel β-strands. The three-dimensional structure of the PP2A holoenzyme containing PPP2R2A as the regulatory subunit indicates that the β-hairpin arm on the bottom face of PPP2R2A interacts with PP2A A subunit at the HEAT motifs 2-7, while the catalytic subunit binds to PP2A A at the other end[58, 80]. There is a putative substrate-binding groove on the top face of PPP2R2A[17].

It is generally believed that most binding of the PP2APPP2R2A (this will designate a specific PP2A trimer by the name of its specific B regulatory subunit) substrates appears to be solely with PPP2R2A (by opposition to binding through a A or C interaction)[80]. After binding to PPP2R2A, the substrates will be rapidly dephosphorylated by the catalytic C subunit and then released from the PP2A

! ! 11! holoenzyme, making it difficult to identify substrates for PPP2R2A because of the transient interaction. If there is a mutant of PPP2R2A that is still able to bind to the substrates but not to the PP2A core dimer, the interaction with the substrate could potentially be stabilized enough for it to get trapped, and therefore identifiable in a purification experiment. New PP2A substrates may be identified with the bound trapped substrates to these free PPP2R2A subunits.

1.4 PP2A-related tumor virus proteins 1.4.1 SV40 small T antigen Simian virus 40 (SV40) is the best characterized member of the Polyomaviridae family of small DNA tumor viruses[81]. Studies have reported that infection of SV40 in non-permissive host cells can contribute to cell transformation and tumor formation[82-85]. The SV40 genome is divided into two regions based on the timing of gene expression after SV40 infection; an Early Region (ER) and a Late Region (LR). In cells that are transformed by SV40 infection, only the ER is expressed and the expression of ER is sufficient to induce cell transformation. There are three proteins encoded by SV40 ER; the large T antigen (LT), small T antigen (ST) and 17kT antigen[86, 87]. SV40 LT functions to stimulate cell transformation through the inhibition of two tumor suppressor proteins, p53 and pRB[86-90]. SV40 ST, however, targets PP2A, which is the only cellular protein known to interact with SV40 ST except chaperones [45, 46].

The N-terminal region of SV40 ST shares sequence homology with the J domain of DnaJ from E. coli. The C-terminal region of SV40 ST consists of a Zinc-binding domain that interacts with the HEAT motifs 3-6 in PP2A A subunit, which overlap with the binding sites for PP2A B' subunits. After directly interacting with PP2A A subunit through the Zinc-binding domain, the J domain of SV40 ST mediates interaction with the PP2A C subunit[45]. It was reported that SV40 ST modulates the function of PP2A by two modes. Since the binding site of SV40 ST on the scaffolding A subunit overlaps with the B' subunits, binding of ST to the PP2A core dimer can

! ! 12! prevent the formation of PP2A holoenzymes with B' as the regulatory subunits, which alters the substrate specificity, localization and phosphatase activity of PP2A. In addition, the J domain of ST may directly interact with the substrate-binding region of the C subunit of PP2A, leading to the inhibition of the phosphatase activity of PP2A by competing with substrate for access to the active site[45]. Although SV40 ST affects the function of PP2A in these two ways, little is known about other possible functions of SV40 ST during infection.

1.4.2 Polyomavirus middle T antigen The Early Region of polyoma virus encodes three viral proteins: the small T antigen, middle T antigen (PyMT) and large T antigen, which have similar amino acid sequences. These three T antigens share a common amino-terminal sequence, and the small and middle T antigens share the central region. The carboxyl-terminal region of each antigen, however, is different[91]. In spite of the similar sequence, PyMT is the sole primary transforming protein of polyomavirus: Studies have reported that all of the polyoma virus non-transforming mutations alter the PyMT coding sequence. This demonstration was also confirmed by the observation that only the part of the early region that encoded PyMT was required for transformation[92-97]. This indicates that PyMT is tightly associated with the transforming properties of polyoma virus.

PyMT carries out its transforming function by associating with and modulating the activities of cellular proteins involved in control of cell proliferation[91]. These proteins include c-SRC, c-yes, PI 3-kinase, PP2A, etc.[47, 98-101]. Take c-SRC as an example. When expressed in host cells, PyMT interacts with c-SRC and leads to its dephosphorylation at Tyr52, which increases the tyrosine kinase activity of c-SRC, the cellular version of the v-src oncogene[102-105]. PP2A is another major interactor of PyMT. It has been revealed that the membrane-located PyMT binds to PP2A A and C subunits at its N terminus. There are strong indications that the association between PyMT and PP2A alters the substrate specificity and phosphatase activity of PP2A holoenzyme[91]. Although PyMT has been linked to the biology of PP2A for many

! ! 13! years, little is known about how PyMT regulates the function of PP2A.

1.4.3 Adenovirus E4orf4 protein E4orf4 is the product of human adenovirus early transcription region 4 open reading frame 4. It is a 114-residue protein that has no extensive sequence homology with any known proteins[106, 107]. E4orf4 is a multifunctional viral regulator, which is involved in the down regulation of virally modulated signal transduction, in the control of alternative splicing of late viral mRNAs, and in the induction of apoptosis in transformed cells[108-115]. General interest in E4orf4 emanates from the finding that when expressed in cells at high levels, E4orf4 exhibits tumor cell-specific, p53-independent toxicity in a variety of human cancer cell lines[106, 116-123]. This discovery of the tumor cell-specific killing ability of E4orf4 provides a new possibility for the design of anti-cancer drugs.

The major insight into the mechanism of how E4orf4 promotes cell killing comes from the finding that E4orf4 interacts with the tumor suppressor PP2A. E4orf4 binds to all members of the PP2A B55 subfamily of regulatory subunits but no other B subunits[111, 117]. Toxicity induced by E4orf4 is largely dependent on its ability to associate with the highly conserved PP2A B55 subunits. It is proposed that E4orf4 inhibits PP2A activity by binding to the putative substrate-binding groove of B55 and preventing access of substrates[17]. At high E4orf4 expression levels, this results in cell death through the failure to dephosphorylate substrates required for cell cycle progression[114, 124]. Two classes of E4orf4 mutants that are deficient in the process of cell death induction have been identified so far. Class I E4orf4 mutants fail to kill cancer cells and also loose the binding to B55, suggesting that interactions with PP2A are essential for the toxicity of E4orf4. Class II E4orf4 mutants, however, can still bind B55 but are deficient in cell killing, indicating that although PP2A binding is necessary for the induction of cell killing, it is not sufficient[117].

Although hyperphosphorylation of one of the PP2A substrates, p107 (a member of the

! ! 14! retinoblastoma gene family), has been identified following overexpression of E4orf4[17], which confirms the model for inhibition of PP2A activity by E4orf4, little is known about the influence of E4orf4 on other PP2A substrates. In addition, since the association with PP2A is not sufficient for E4orf4 to induce cell killing, it is necessary to detect other components required for E4orf4 toxicity.

1.5 Affinity purification and mass spectrometry It is becoming increasingly clear that cellular organization implicates the association of proteins into functional units known as "protein complexes"[125]. Proteins generally interact with each other and form complexes in a time- and space-dependent manner, which is critical for cells to carry out and maintain their normal functions. In the case of signaling molecules such as PPP family phosphatases, a protein complex provides functional activity by interacting with its specific substrates. At the same time, the specialized function of a protein complex itself can also be dependent on the post-translational modifications or conformational changes caused by interaction with other neighboring proteins[126-128]. Because of the important roles protein complexes and protein-protein interaction networks play in maintaining the function and organization of the living cells, their analysis is of great importance in biological research.

Different approaches have been applied to characterize protein complexes and, more generally, protein-protein interaction networks. Affinity purification coupled with mass spectrometry (AP-MS) has recently been regarded as an indispensible tool in proteomic analysis. Compared to other methods, AP-MS possesses several advantages. First, in contrast to yeast-two-hybrid and related methods, AP-MS can be performed in a near physiological context, especially when expression levels of the protein of interest is controlled such that it is similar to the level of the endogenous protein [129, 130]. Second, AP-MS also allows the detection of post-translational modifications, including phosphorylation, methylation, ubiquitinylation, etc. In addition, AP-MS does not necessitate prior knowledge of the interacting proteins (though it can only

! ! 15! capture proteins expressed in the cell analyzed and detects interactions occurring only under tested conditions). Although less sensitive and rapid than other approaches such as Y2H[131], LUMIER[132], etc., only femtomole levels of peptides are required for identification using AP-MS, and sequencing of single peptide can be accomplished within hundreds of milliseconds. Based on these advantages, AP-MS has increasingly become the choice for the discovery of biologically relevant protein-protein interactions[130].

The generic workflow (Fig. 2) of AP-MS most often begins with tagging of the protein of interest with an epitope that can be used for purification, which can be achieved either by transfecting a tagged gene into cells or by targeting the endogenous gene using homologous recombination or other strategies[133]. The recombinant protein expression system varies (for example, I use here a tetracycline-inducible promoter), but expression levels should preferably be at near endogenous level in order to prevent the drawbacks resulting from overexpression. It is more likely for the overexpressed proteins to get misfolded, which will result in their association with molecular chaperones. The overexpressed proteins are also often mislocalized and dysregulated, inducing abnormal interactions or post-translational modifications. Moreover, the balance between the overexpressed proteins and their cellular binding partners are disrupted, making it more difficult to identify the bona fide protein-protein interactions[129]. Once cells expressing the recombinant proteins of interest are generated and treated as desired (e.g. with a growth factor or an inhibitor), the tagged protein is purified from the cell lysate together with its binding partners. The extracted proteins, including the bait itself, its interactors as well as the contaminants, are then degraded enzymatically into peptides, usually by trypsin, producing peptides with C-terminally protonated amino acids, which provides an advantage in subsequent peptide sequencing[133]. The prepared sample will then be analyzed by MS. In general, the MS analysis involves two steps, peptide separation by reversed-phase liquid chromatography followed by tandem MS (MS/MS). In the first MS scan, the mass/charge ratio (m/z) of the intact peptide is measured. The n most

! ! 16!

Figure 2. Workflow of affinity purification coupled with mass spectrometry (AP-MS). (a) A protein of interest (bait) is fused with a tag and expressed in cells. Affinity purification is performed using beads with antibody specifically targeting the tag. The protein, together with its binding partners and some unspecific interacting proteins, is pulled down and digested into peptides enzymatically. The peptide mixture is then analyzed by liquid chromatography (reverse-phase HPLC) and mass spectrometry. (b) Peptides are first separated by LC, ionized by electrospray and then enter MS. In tandem MS (MS/MS) analysis, the MS1 survey scan of the masses of individual precursor ions is performed firstly. A precursor ion (in red) is selected for fragmentation based on its abundance in MS1. The fragmented ions are detected and analyzed later to generate a MS/MS spectrum. This spectrum can be used to search the database in order to identify the peptides and finally characterize the proteins.

! ! 17!

! ! a Bait

tag

Bait tag LC-MS/MS

Bead Bait tag ! Bait tag LC-MS/MS ! ! Bead !

! LC MS1 MS/MS ! b ! LC MS1 MS/MS

! ! ! ! ! ! ! ! ! ! ! !

! ! 18! abundant peptides (as defined by the intensity of their signal in the MS scan; n = 10 in this study) are then specifically selected and subjected for fragmentation by neutral molecules, yielding a MS/MS spectrum[130, 133]. After acquiring the raw spectra, database searching (e.g. using tools such as Mascot, SEQUEST, X!Tandem, Comet, etc.) is performed and the spectra matched with sequences in the database are scored to generate high confidence peptide identifications[134]. These can be further statistically evaluated (for example using tools such as PeptideProphet[135]), and the peptides assigned to their corresponding proteins (e.g. with ProteinProphet) to yield the list of high confidence proteins present in a sample.

Identifying the proteins present in an affinity-purified sample is only a first step. It is important to realize that each AP-MS experiment conducted on a modern mass spectrometer will yield hundreds if not a thousand protein identifications, among which only a relatively small percentage are interactors. The other identified proteins are contaminants, which associate with the affinity matrix used for purification, bind to the epitope tag itself, or just associate non-specifically to any expressed protein[136]. It is therefore primordial to identify which are the true interaction partners and which are the contaminants. Although a multitude of experimental and computational strategies have been devised to perform this assessment, a particularly effective one employs the discrimination of the quantitative abundance of a prey recovery across purifications of a bait versus negative control purifications. Statistical tools such as SAINT (Significance Analysis of INTeractome) use the spectral counts (the number of identified spectra matching to a protein) as input for each prey protein, and compare their distribution in the control samples to those in the bait purifications, putting a probability value for each interaction[137]. Factors such as the selection of appropriate negative controls, the number of biological replicates analyzed for interaction scoring, and even more technical details such as the randomization of the order of sample analysis are all important experimental factors to consider to ensure the best performance of the statistical tool, and a minimization of the false-positive rates. When performed well, results from AP-MS analysis can be

! ! 19! used to identify true protein-protein interactions (note that these will consist of both direct and indirect interactions) and help to construct the interaction network for the protein of interest.

1.6 Proximity-dependent biotin identification with BioID BioID is a newly developed approach that can be used to investigate protein-protein interactions in living cells in a manner complementary to the more standard AP-MS strategy described above, by inducing covalent labeling in vivo of the proteins located in the proximity of a bait[138, 139].

BioID causes proximity-dependent biotinylation of proteins that can be purified and then identified by mass spectrometry[139]. It functions by fusing a promiscuous E. coli biotin protein ligase, called BirA*, to the targeting protein. BirA* is a mutant (R118G) of BirA, which is a DNA-binding biotin protein detected in E. coli that not only serves to transcriptionally regulate the biotin synthetic operon but also to biotinylate a subunit of the acetyl-CoA carboxylase[140, 141]. It takes two steps for BirA to biotinylate proteins. First, the wild-type BirA generates biotinoyl-5'-AMP using biotin and ATP. BirA will hold this activated biotin molecule within the BirA active site until it is covalently attached to specific substrates in the second step. Although biotinylation is an ideal modification that can facilitate the isolation of labeled proteins, only a few carboxylases in mammalian cells can be biotinylated by wild-type BirA, which restricts its use in detecting protein-protein interactions (though it is possible to test pairwise interactions by fusion of the BirA recognition sequence to any protein). BirA*, however, displays a twofold lower affinity for biotinoyl-5'-AMP, resulting in promiscuous biotinylation for various proteins in a proximity-dependent manner[138, 139]. This makes BirA* an eligible biotin ligase for identification of previously unknown protein-protein interactions in cells. Essentially, one conducts a BioID experiment much in the same manner as an AP-MS experiment, and in fact, tools that were built for the analysis of AP-MS data can be repurposed for BioID analysis (Fig. 3). The bait of interest is fused to BirA* (instead

! ! 20!

Figure 3. Model for application of BioID method. A protein of interest (bait) is fused with BirA* and expressed in cells. Biotin is added into cell culture and is utilized by BirA* to generate the biotin-AMP molecule. Then BirA* leads to the selective biotinylation of proteins proximate to bait, including bait itself. The proteins not close enough will not be biotinylated. After stringent cell lysis, proteins with biotinylation are affinity purified by streptavidin beads, which specifically target biotin. The pulled down proteins are then digested into peptides, which will be analyzed by LC-MS/MS. Figure adapted from Go., C.D., Gingras Lab.

! ! 21!

! ! ! ! ! ! ! !

BirA* BirA* Bait Bait BirA* Bait

Biotin Biotin-AMP

BirA*

Bait

LC-MS/MS Bead

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

! ! 22! of an affinity tag) and expressed in cells; the key difference is that biotin is now supplemented to the medium to mediate biotinylation of the neighboring proteins. Labeling with biotin in this system requires a fairly lengthy incubation time (24 hours in the original publication[139], though our laboratory has had success with labeling times as short as 4–6 hours; Gingras lab, unpublished). Because biotinylation is a covalent modification, lysis can be much harsher than in standard AP-MS as it is not require to preserve interactions: biotinylated proteins can be recovered on streptavidin affinity beads. Mass spectrometric identification and statistical analysis (e.g. with SAINT) can be performed in a manner similar to AP-MS to identify the high confidence interaction partners (or more accurately in this case, the proximal proteins).

Compared to other AP-MS methods, MS coupled with BioID bears several advantages in identifying protein-protein interactions. Since affinity purification can be carried out under extremely stringent conditions, an obvious benefit is that harsher wash conditions can be used to remove the contaminants that are usually detected during affinity purification. In addition, because of the covalent biotinylation, transient interactions may be identified using BioID. In theory, the binding partners that transiently interact with the protein of interest will get increasingly biotinylated over time, leading to more opportunities of identification with BioID. Finally, BioID is also applicable to detect the interactions carried out by insoluble proteins, which are always difficult for study using traditional methods[138]. This last point has been now demonstrated for several cellular compartments, including two histone proteins and three mediator complex subunits[142].

1.7 Quantitative mass spectrometry with the Data Independent Acquisition method SWATH In addition to characterizing protein-protein interactions, AP-MS is also eligible for the quantification of the interaction dynamics. In recent years, the DNA and RNA sequencing of healthy and cancerous tissues or cells have uncovered a great deal of

! ! 23! genetic variants, such as point mutations, splice variants and allelic variants, several of which could potentially alter interactions established by a protein. In order to better understand the protein-protein interaction changes associated with these sequence variants, several quantitative mass spectrometry approaches have been developed. Affinity Purification coupled to SWATH (Sequential Window Acquisition of all THeoretical spectra) is a newly developed quantitative proteomics method that is applicable to large-scale studies of protein-protein interaction changes [143].

Before the development of SWATH, quantification of protein-protein interactions was primarily accomplished by data-dependent acquisition (DDA) mass spectrometry or Selected/Multiple Reaction Monitoring (S/MRM). As described above, in DDA, peptides are selected for sequencing based on the relative abundance of their precursor ion signals in the survey scan, which means that only the most abundant peptides can get sequenced and identified, resulting in a loss of peptide information in the sample[144]. This issue can somewhat be circumvented when doing comparisons across only a few samples, for example by employing isotopic labeling approaches such as SILAC (Stable Isotope Labeling by Amino acids in Cell culture): in these cases, relative quantification can be obtained for each identified peptide in a given experiment. Other approaches that partially mitigate this problem exploit the LC-MS features of the MS1 peaks to re-extract quantitative information across a set of runs in a dataset even for features which were not observed in a given run, providing that they were identified in at least one of the runs within the set[145]. These methods, however, are not without their issues: SILAC only enables comparisons between a limited number of samples while MS1 extraction becomes error-prone as the complexity of the sample increases. One MS method that is not operating in the DDA manner is S/MRM, which has been referred as a targeted MS approach. S/MRM can monitor selected peptides at multiple time points, providing more accurate quantification and prevents missing values; it has been successfully coupled to affinity purification to study the dynamic of interactions centered on key scaffolding protein in the Epidermal Growth Factor receptor pathway[146, 147]. However, SRM requires

! ! 24! information about the fragmentation of the specific peptide as well as its retention time before analysis. This requires a certain level of investment in method development for each peptide. In addition, SRM asks for predetermining the specific peptides for analysis, which strongly limits its utility for large-scale proteomic analysis[143, 144].

SWATH belongs to another type of acquisition strategy called data-independent acquisition (DIA), in which all precursor ions are fragmented independently of their intensity. The entire useful mass range is scanned in SWATH with wide mass windows (in my case, 25 mass units through the 400-1200 m/z range) and all precursors in each window are fragmented, resulting in a LC-MS and LC-MS/MS map of all compounds. This map can then be used to quantify the proteins in the sample, independently of the abundance of the precursor ion/selection for fragmentation[143]. Therefore, AP-SWATH decreases the possibility of omitting peptides, making it appealing in characterizing protein-protein interaction changes. Data analysis of SWATH results is still in its infancy, however, and as will be described in more details in this thesis, the data I have generated have proven challenging for the tools that were already in existence[143], and prompted the development of new computational tools by our collaborators to better analyze this type of data (see Discussion).

1.8 Objectives of this project As mentioned above, PP2A is a tumor suppressor. The function and phosphatase activity of PP2A holoenzyme is influenced by several factors, such as mutations in PP2A subunits and the association of the enzyme with tumor virus proteins. It is hypothesized that mutations of PP2A subunits may cause significant protein-protein interaction changes in the PP2A interaction network, ultimately leading to alteration of key substrate phosphorylation, and cancer development. Therefore, the first purpose of this project is to apply AP-SWATH to quantitatively characterize the protein-protein interaction changes imparted by the mutations of PP2A subunits,

! ! 25! including mutations in PPP2R1A and PPP2CA, in order to illustrate how these mutations alter the normal function of PP2A. As for PPP2R2A, I plan to expand the landscape of its interactors in order to identify potential new substrates for this specific regulatory subunit. In addition, although it is known that PP2A is the target of several tumor virus proteins, how these proteins regulate PP2A is not completely understood. So this project also proposes to characterize the interactome of three PP2A-related tumor virus proteins, SV40 ST, PyMT and E4orf4. The characterization of the binding partners of these proteins may help reveal their PP2A-dependent as well as PP2A-independent functions. Furthermore, since PPP2R2A is the cellular target of E4orf4, the newly identified PPP2R2A substrates may also help illustrate the influence of E4orf4 on PP2A function. Overall, these combined studies will provide a deeper understanding of the role PP2A plays during carcinogenesis.

! ! 26!

CHAPTER 2 MATERIALS AND METHODS

2.1 Plasmids Plasmids constructed in this study are listed in Table 2. The coding sequence of human PPP2R1A (MGC786; accession number BC001537) was inserted into the EcoRI and NotI sites of pcDNA5/FRT/TO-FLAG[148]. Point mutations of PPP2R1A were generated by two-step PCR and also inserted into the EcoRI and NotI sites of pcDNA5/FRT/TO-FLAG. The coding sequences of human PPP2CA (MGC34900; BC031696) and rat PPP2R2A (MGC156605; BC128731) were cloned in frame in the EcoRI and NotI sites of pcDNA5/FRT/TO-FLAG. Point mutations of PPP2CA and PPP2R2A were generated by Orgis Lab and Branton Lab respectively, and were cloned by PCR into pcDNA5/FRT/TO-FLAG using the same multiple cloning sites. Wild-type PPP2R2A and all PPP2R2A mutants were also inserted into the AscI and NotI sites of pcDNA5/FRT/TO-BirA*-FLAG[149]. Polyomavirus PyMT (GeneBank accession number J02289) and adenovirus E4orf4 (GeneBank accession number KF268310) were cloned in frame in the EcoRI and XhoI sites of pcDNA5/FRT/TO-FLAG. Mutations of E4orf4 were generated by Branton Lab and were inserted into pcDNA5/FRT/TO-FLAG between EcoRI and XhoI, except that the mutation L54A was cloned in frame in the EcoRI and EcoRV sites as this mutation created an internal XhoI site. Triple-FLAG constructs of SV40 ST (GeneBank accession number FJ208848) were generated via gateway cloning into pDESTpcDNA5/FRT/TO-3FLAG[149]. Sequences corresponding to the amino acids 1-362 and 553-583 of SV40 ST were also cloned into pDESTpcDNA5/FRT/TO-3FLAG via gateway cloning. The three constructs used for immunoprecipitation and western blot validation were generated as follows: PPP2CA and ANKLE2, which were inserted into pDESTpcDNA5/FRT/TO-3HA (M Goudreault; unpublished) via gateway cloning, and PPP2R2A, which was cloned in frame into the EcoRI and NotI sites of pcDNA5-GFP (M Goudrealt; unpublished). All the inserted coding sequences and mutations were verified by sequencing.

! ! 27!

Table 2. Plasmids used in this study Openfreezer ID Name Ref. V6798 pcDNA5/FRT/TO-FLAG-PPP2R1A V9033 pcDNA5/FRT/TO-FLAG-PPP2R1A-Q372L V9034 pcDNA5/FRT/TO-FLAG-PPP2R1A-C329F V9035 pcDNA5/FRT/TO-FLAG-PPP2R1A-R183W V9036 pcDNA5/FRT/TO-FLAG-PPP2R1A-P179R V9037 pcDNA5/FRT/TO-FLAG-PPP2R1A-S256F V9038 pcDNA5/FRT/TO-FLAG-PPP2R1A-R183Q V9039 pcDNA5/FRT/TO-FLAG-PPP2R1A-R258H V9040 pcDNA5/FRT/TO-FLAG-PPP2R1A-W257C V9071 pcDNA5/FRT/TO-FLAG-PPP2CA V9072 pcDNA5/FRT/TO-FLAG-PPP2CA-T304A V9073 pcDNA5/FRT/TO-FLAG-PPP2CA-T304D V9074 pcDNA5/FRT/TO-FLAG-PPP2CA-Y307E V9075 pcDNA5/FRT/TO-FLAG-PPP2CA-Y307F V9076 pcDNA5/FRT/TO-FLAG-PPP2CA-L309Δ V9077 pcDNA5/FRT/TO-FLAG-PPP2CA-L309A V9078 pcDNA5/FRT/TO-FLAG-PPP2CA-T304A/Y307F V9079 pcDNA5/FRT/TO-FLAG-PPP2CA-T304D/Y307E V9080 pcDNA5/FRT/TO-FLAG-PPP2CA-R268E V9081 pcDNA5/FRT/TO-FLAG-PPP2CA-R268E/T304D V9082 pcDNA5/FRT/TO-FLAG-PPP2CA-R268E/T304A/Y307F V9346 pcDNA5/FRT/TO-FLAG-PPP2R2A V9347 pcDNA5/FRT/TO-FLAG-PPP2R2A-V154E V9348 pcDNA5/FRT/TO-FLAG-PPP2R2A-V154R V9349 pcDNA5/FRT/TO-FLAG-PPP2R2A-R257E V9385 pcDNA5/FRT/TO-FLAG-PPP2R2A-E190K V9386 pcDNA5/FRT/TO-FLAG-PPP2R2A-C239L V9387 pcDNA5/FRT/TO-FLAG-PPP2R2A-E190K/V154E V9388 pcDNA5/FRT/TO-FLAG-PPP2R2A-C239L/V154E V9604 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A V9605 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A-V154E V9606 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A-V154R V9607 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A-R257E V9608 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A-E190K V9609 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A-C239L V9610 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A-E190K/V154E V9611 pcDNA5/FRT/TO-BirA*-FLAG-PPP2R2A-C239L/V154E V8953 pDESTpcDNA5/FRT/TO-3FLAG-SV40 ST V8954 pDESTpcDNA5/FRT/TO-3FLAG-SV40 ST-Mutant V9243 pcDNA5/FRT/TO-FLAG-PyMT V9241 pcDNA5/FRT/TO-FLAG-E4orf4

! ! 28!

V9242 pcDNA5/FRT/TO-FLAG-E4orf4-R81A/F84A V9597 pcDNA5/FRT/TO-FLAG-E4orf4-L54A V9598 pcDNA5/FRT/TO-FLAG-E4orf4-K88A V9599 pcDNA5/FRT/TO-FLAG-E4orf4-D99A V8922 pcDNA5-GFP-PPP2R2A V8925 pDESTpcDNA5/FRT/TO-3HA-PPP2CA V9612 pDESTpcDNA5/FRT/TO-3HA-ANKLE2 V4071 pcDNA5/FRT/TO-FLAG [148] V9595 pcDNA5/FRT/TO-BirA*-FLAG [149] V4978 pDESTpcDNA5/FRT/TO-3FLAG [149] V4131 pcDNA5-GFP M Goudreault V8055 pDESTpcDNA5/FRT/TO-3HA M Goudreault

! ! 29!

2.2 Cell lines, culture, transfection and collection Stable cell lines for AP-MS analysis were generated as Flp-In 293 T-REx cell (Invitrogen) pools as follows: (1) Day one, seed low passage Flp-In 293 T-REx cells into a 6-well plate at about 50% confluency for transfection the next day. (2) Day two, transfect the seeded Flp-In 293 T-REx cells with 200ng of constructed plasmids (pcDNA5/FRT/TO-FLAG-protein, pDESTpcDNA5/FRT/TO-3FLAG-protein, or pcDNA5/FRT/TO-BirA*-FLAG-protein) and 2,000ng of the Flp recombinase vector pOG44 per well of a 6-well plate. jetPRIME (Polyplus) is used for transfection according to the manufacturer’s instruction. (3) After 24 hours' transfection, passage cells into a 10cm plate with complete medium (DMEM with 10% FBS/FCS and 100units/ml of penicillin/streptomycin). (4) Day four, replace the medium with selection medium (complete medium supplemented with 200µg/ml hygromycin). Selection medium is replaced every 2-3 days until non-transfected cells die and isolated clones are visible (this process takes approximately 13-15 days). (5) Passage the cells from the 10cm plate into a 15cm plate using fresh selection medium. (6) When the new 15cm plate reaches 75-80% confluence, split this plate for freezing down (four tubes with 1ml cells in each tube) and for preparing biological replicates.

For anti-FLAG AP-MS analysis, two 15cm plates were used for each biological replicate. For BioID analysis, a single 15cm plate was used for each biological replicate. Cells were induced to express the FLAG or BirA*-FLAG tagged protein of interest and collected following the procedure below: (1) Cells in complete medium was grown to about 65% confluency (in 15 cm plates) and induced with 1µg/ml tetracycline for 24 hours (note that for BioID experiments, biotin is added at a concentration of 50µM alongside the tetracycline). (2) After 24 hours' induction, cells should reach to about 90% confluency. These cells are collected by removing medium from the plate, washing the plate with 10ml PBS, adding 1ml ice-cold PBS, and scraping cells from the plate using a silicon cake spatula. Cells are transferred into a 15ml falcon tube (pre-weighted) and kept on ice. (3) Cells are pelleted by centrifugation (500g, 5min at 4°C), the PBS is aspired and the falcon tube is

! ! 30! transferred on dry ice for 5min. (4) The falcon tube with cells in it is weighed to calculate the weight of the cells and transferred to -80°C for storage.

Transiently transfected HEK293T cells are prepared and collected as follows: (1) Day one, low passage HEK293T cells are seeded into a 6-well plate with complete medium at about 50% confluency for transfection the next day. (2) Day two, the seeded cells are transfected with constructed plasmids (the amount of each plasmid is variable, from 300ng to 1,000ng, but the total amount should be no more than 1,000ng). jetPRIME (Polyplus) is used for transfection according to the manufacturer’s instruction. (3) After 24 hours' transfection, cells (about 90% confluent) are collected by removing medium from the 6-well plate, washing the cells with 1ml PBS, adding 200µl PBS, and scraping cells from the plate using a silicon cake spatula. Cells are transferred into a 1.5ml Eppendorf tube and kept on ice. (3) Cells are pelleted by centrifugation (1,500rpm, 5min at 4°C). PBS is aspirated and the tube is transferred on dry ice for 5min. (4) The tube is transferred to -80°C for storage. These transient transfected HEK293T and HeLa cells are used for IP-WB and immunofluorescence.

2.3 Affinity purification 2.3.1 Anti-FLAG affinity purification The cell pellet is first lysed by passive lysis assisted by a freeze-thaw process. (1) Lysis buffer (TAP) is made of: 50mM Hepes-KOH pH 8.0, 100mM KCl, 2mM EDTA, 0.1% NP40 and 10% glycerol, supplemented with 1mM PMSF, 1mM DTT and 1X protease inhibitor cocktail (Sigma-Aldrich). Note that NP40, PMSF, DTT and protease inhibitor are added freshly. (2) The frozen cell pellet is re-suspended in ice-cold lysis buffer at a 1:4 pellet weight:volume ratio. The lysate is transferred into a 1.5ml Eppendorf tube. (3) One freeze-thaw cycle is performed by incubating the tube on dry ice for 5min, transferring it into a 37°C water bath with agitation until only a small amount of ice remains and then transferring the tube back on ice. (4) Cell debris is removed from the sample by centrifugation (140,000rpm, 20min at 4°C). (5)

! ! 31!

After centrifugation, 20µl supernatant is taken out as pre-IP sample to test protein expression. All the remaining supernatant is transferred into a fresh 1.5 Eppendorf tube.

During centrifugation, the anti-FLAG M2 magnetic beads are prepared (M8823, Sigma-Aldrich). (1) 25µl of 50% slurry is used for each sample. The total amount of slurry needed is calculated and then taken out into a fresh 1.5 tube. (2) The beads are washed with cell lysis buffer: re-suspend the beads in 1ml cell lysis buffer, magnetize the beads for 1min and aspirate the supernatant, remove the beads from the magnet. Repeat the cycle for three times. (3) Following the last wash, the beads are re-suspended in enough lysis buffer to generate a 50% slurry. 25µl this slurry is distributed into clarified lysate sample.

The sample is incubated at 4°C for 2 hours with gentle agitation on a nutator. After incubation, he tubes are taken out and slightly centrifuged at 4°C, 6,000rpm for 30s. The samples are magnetized and a 20µl aliquot of the post-IP lysate is taken for WB analysis to check the efficiency of this affinity purification. The remaining sample is aspirate and the beads are transferred with 1ml lysis buffer into a new tube. Then the beads are washed once with 1ml lysis buffer, followed by once with 20mM Tris-HCl pH 8.0 2mM CaCl2. For each of these washes, the sample is demagnetized, the beads are re-suspended by pipetting up and down five times in the wash buffer, the beads are magnetized again for 1min and then the supernatant is removed. Note that the washing steps should be done as quickly as possible. After the last wash, the tubes are put on ice, the beads fall to the bottom of the tube, and most of the liquid on the tube wall is removed. 2.5µl Tris-HCl (in HPLC H2O, pH 8.0) is added into each tube to help move all the beads down to the bottom of the tube.

Trypsin digestion of the protein sample is performed on bead. 500ng trypsin (T6567, Sigma-Aldrich) is added to the mixture and the sample is incubated at 37°C on a rotator overnight. The next morning, the sample is magnetized for 1min and the

! ! 32! supernatant is transferred into a fresh tube, an additional 500ng trypsin is added and the sample is incubated at 37°C on a rotator for another 4 hours. Following the second trypsin digestion, formic acid is added to the sample to a final concentration of 2% (from 50% formic acid stock solution). The sample can then be stored at -20°C or directly analyzed by MS. Half of the sample is used per MS analysis.

2.3.2 Streptavidin affinity purification The cell pellet is also lysed by passive lysis assisted by a freeze-thaw process. (1) Lysis buffer (RIPA) is made of: 1% Triton X-100, 50mM Tris-HCl pH 7.5, 150mM NaCl, 1mM EDTA, 1mM EGTA, 0.1% SDS, 100µl Mammalian Protease Inhibitor (per 50ml RIPA) and 0.5% Sodium Deoxycholate (5ml 5% stock to 45ml RIPA). Note that Mammalian Protease Inhibitor and Sodium Deoxycholate are added freshly. (2) Ice-cold lysis buffer is added at a 1:10 pellet weight:volume ratio to the cell pellet. Remember that 1µl benzonase is added into each sample and the sample is lysed on a nutator at 4°C until the cell pellet is re-suspended. (2) The lysate is sonicated on ice (30% amplitude, three times of 10sec burst with 3sec rest between each burst). (4) Cell debris is removed from the sample by centrifugation (20,817g, 30min at 4°C). (5) After centrifugation, 50µl supernatant is taken out as pre-IP sample to test protein expression and the efficiency of biotinylation. All the remaining supernatant is transferred into a fresh 1.5ml Eppendorf tube.

During centrifugation, the Streptavidin-Sepharose beads (GE Cat#17-5113-03) are prepared. (1) 30µl of 50% slurry is used for each sample. The total amount of slurry needed is calculated and taken out into a fresh 1.5 tube. (2) The beads are washed with cell lysis buffer (without PI or sodium deoxycholate): the beads are re-suspended in 1ml cell lysis buffer, pelleted for 1min at 400g, and the supernatant is aspirated (be careful not to remove the beads). The cycle is repeated for three times. (3) Following the last wash, the beads are re-suspended in enough lysis buffer to generate a 50% slurry. 30µl this slurry is distributed into clarified lysate sample.

! ! 33!

The sample is incubated at 4°C for 3 hours with gentle agitation on a nutator. After incubation, the tubes are taken out and slightly centrifuged at 4°C, 400g for 1min. A 50µl aliquot of the post-IP lysate is taken out for flow through analysis. The remaining sample is aspirated and the beads are transferred with 1ml lysis buffer (without PI or sodium deoxycholate) into a new tube. Then the beads are washed once with 1ml lysis buffer (without PI or sodium deoxycholate), twice with 1ml TAP buffer, and followed by three times with 50mM ammonium bicarbonate pH 8.0 (ABC). For each of these washes, the beads are re-suspended by pipetting up and down five times in the wash buffer, pelleted for at 400g, 4°C for 1min, and then the supernatant is removed. Note that the supernatant should be removed carefully and the washing steps should be done as quickly as possible. After the last wash, the supernatant is removed as much as possible with a pipette.

Trypsin digestion of the protein sample is also performed on bead. 1µg trypsin (T6567, Sigma-Aldrich) is added to the mixture with 30µl ABC buffer, and the sample is incubated at 37°C on a rotator overnight. The next morning, an additional 500ng trypsin is added and the sample is incubated at 37°C on a rotator for another 2 hours. Following the second trypsin digestion, the beads are pelleted at 400g for 2min and the supernatant is transferred to a fresh Eppendorf tube. The beads are then washed twice with 30µl HPLC H2O, which is added into the former supernatant. The pooled supernatant is centrifuged at 16,100g for 10min, the supernatant is transferred into a new tube, and formic acid is added to the sample to a final concentration of 2% (from 50% formic acid stock solution). The sample is then vacuumized to dryness using a Speed vac. The sample is re-suspended in 12µl 15% formic acid and can then be stored at -20°C or directly analyzed by MS. 6µl of the sample is used per MS analysis.

2.4 Immunoprecipitation-Western Blot Immunoprecipitation from stably-transfected HEK293 cells or transiently-transfected 293Ts were performed at 4°C, using anti-FLAG affinity purification described in

! ! 34!

2.3.1 with a few of modifications. First, add 200µl cell lysis buffer into each cell pellet to re-suspend it regardless of its weight. Second, after the last wash, add 50µl ddH2O and 10µl 6× Sample Buffer into the beads, and boil the beads at 95°C for 5min. Remove the supernatant into a new tube as the IP sample. Pre-IP and flow through samples are just boiled with sample buffer.

The used primary antibodies are listed as follows: mouse anti-FLAG (Sigma-Aldrich, AF3165), mouse anti-GFP (Roche, 11814460001), mouse anti-HA (Santa Cruz, SC-3792), rabbit anti-PPP2R5A (Bethyl Laboratories, A300-967A), goat anti-PPFIA1 (Santa Cruz, Sc54039) and rabbit anti-TIPRL (AC Gingras and N Sonenberg; unpublished). Secondary antibodies for immunoblotting are donkey anti-mouse IgG (GE Healthcare, NA931), donkey anti-rabbit IgG (GE Healthcare, CA95017-556L), and donkey anti-goat IgG (Jackson ImmunoResearch Laboratories Inc, 705-035-147), all conjugated to horseradish peroxidase.

2.5 Mass spectrometry 2.5.1 MS/MS For data dependent acquisition (DDA) LC-MS/MS, affinity purified and digested samples were analyzed by nano-HPLC (High-Pressure Liquid Chromatography) coupled with MS. The amount of affinity purified material used for analysis was equivalent to one 90% confluent 15cm plate for FLAG-proteins/3xFLAG-proteins and half of a 90% confluent 15cm plate for BirA*-FLAG-proteins. Nano-spray emitters were generated from fused silica capillary tubing, with 75µm internal diameter, 360µm outer diameter and 5-8µm tip opening, using a laser puller (Sutter Instrument Co., model P-2000, with parameters set as follows; heat = 280, FIL = 0, VEL = 18, DEL = 200). Nano-spray emitters were packed with C18 reversed-phase material (Reprosil-Pur 120 C18-AQ, 3µm) re-suspended in methanol using a pressure injection cell. The column was equilibrated in 6µl of 0.1% formic acid in water and connected to a NanoLC-Ultra 2D plus system (ABSciex, Eksigent) coupled to an LTQ Velos or ELITE Orbitrap (Thermo Electron) equipped with a nano-spray ion

! ! 35! source (Proxeon Biosystems). The HPLC program delivered an acetonitrile gradient over 145min (buffer B is 0.1% formic acid in acetonitrile and buffer A is 0.1% formic acid in water): the samples was loaded at 400nl/min with 2% buffer B for 20min, flow rate was reduced to 200nl/min and the peptides were eluted from the column using a linear gradient from 2 to 35% buffer B for 95.5min, the column was washed with a gradient from 35 to 80% buffer B for 5min and 80% buffer B for 6.5min, and finally equilibrated with 2% buffer B for 18min. The LTQ Orbitrap Velos or ELITE was operated with Xcalibur 2.0 with the following parameters: one centroid MS (mass range 400-2000 Da) followed by MS/MS on the 10 most abundant parent ions. Other general parameters were listed as follows: activation type = CID, isolation width = 1m/z, normalized collision energy = 35, activation Q = 0.25, activation time = 10ms. The minimum threshold = 500, the repeat count = 1, repeat duration = 30s, exclusion size list = 500, exclusion duration = 30s, exclusion mass width (by mass) = low 0.6 and high 1.2 (modified from[149, 150]).

2.5.2 SWATH Data independent acquisition (DIA) or SWATH, affinity purified and digested samples were analyzed on AB Sciex 5600 TripleTOF in two phases: DDA followed by SWATH acquisition, with the same gradient conditions and equal amounts of sample analyzed (the amount of material used for DDA or DIA was equivalent to half of a 90% confluent 15cm plate). In DDA, the sample was analyzed on 5600 TripleTOF using a Nanoflex cHiPLC system with a chip column. The empty nano-spray emitter was generated with 20µm ID and 10µm tip (New Objective). The HPLC ran the following ratios of buffer B to buffer A: 2-35% buffer B for 85min, 40-60% buffer B for 5min, 60-90% buffer B for 5min, hold buffer B at 90% for 8min and return to 2% B at 105min. The DDA parameters for acquisition were 1 MS1 scan (250ms; mass range 400-1250Da) followed by 10 MS/MS scans (100ms each). Candidate ions that have a charge state 2-5 and counts over a minimum threshold of 200 counts/s were isolated using a window of 0.7amu. Previous analyzed candidate ions were dynamically excluded for 20s. In SWATH, a 50ms MS1 scan followed by

! ! 36!

32×25Da isolation windows that covered the mass range of 400-1250Da (total cycle time 3.25s) (an overlap of 1Da between SWATH windows was preselected). The collision energy for each window was set independently as defined by CE = 0.06×m/z+4, where m/z is the center of the each window, with a spread of 15eV performed linearly across the accumulation time (modified from [143]).

2.6 Data analysis and visualization 2.6.1 DDA data search All raw files generated by MS analysis were saved in our local interaction proteomics LIMS, ProHits[151]. Samples analyzed on the LTQ Orbitrap Velos or Elite were first converted to mzXML files using ProteoWizard 3.0.4468[152] and then the files were analyzed using the iProphet pipeline[153] as follows. The database used for search was the human and adenovirus sequences in the RefSeq protein database (version 57; released on April 18th 2013). The database consisted of forward and reverse sequences (labeled "gi|9999" or "DECOY"); in total, 72,226 entries were searched. Spectra were analyzed separately using Mascot (2.3.02; Matrix Science) and Comet [2012.01 rev.3[154]] for trypsin specificity with up to two missed cleavages, deamidation (Asn or Gln) or oxidation (Met) as variable modifications, double, triple and quadruple charged ions allowed, mass tolerance of the parent ion at 12 parts permillion (ppm), and the fragment bin tolerance at 0.6 amu. The resulting Comet and Mascot results were individually processed by PeptideProphet[155] and combined into a final iProphet output using the Trans-Proteomic Pipeline (TPP; Linux version, v0.0 Development trunk rev 0, Build 201303061711). TPP options were as follows: general options were -p0.05 -x20 -PPM-d"DECOY", iProphet options were -ipPRIME, and PeptideProphet options were -OpdP. All proteins with a minimal iProphet probability of 0.05 were parsed to the relational module of ProHits. For analysis with SAINT, only proteins with an iProphet protein probability of >0.95 were considered. This corresponds to an estimated false discovery rate (FDR) of about 0.5% (modified from [149]).

! ! 37!

Samples analyzed on AB Sciex 5600 TripleTOF were searched against the RefSeq protein database (version 53; released on May 7th 2012). Spectra were analyzed using Mascot (2.3.02; Matrix Science) for trypsin specificity with one missed cleavages, deamidation (Asn or Gln), oxidation (Met) or phosphorylation (Ser, Thr or Tyr) as variable modifications, double and triple charged ions allowed, mass tolerance of the parent ion at 40 ppm, and the MS/MS tolerance at 0.15Da. PPP2CA samples analyzed on AB Sciex 5600 TripleTOF were also analyzed using the iProphet pipeline described as above with several changes: mass tolerance of the parent ion was set as 40 parts permillion (ppm), the fragment bin tolerance was 0.15amu, and PeptideProphet options were -OpPAEd.

2.6.2 SAINT analysis SAINT is a statistical tool that calculates the probability of true interaction using spectral counting (semi-supervised clustering, using a number of negative control runs)[156]. SAINT analysis of PPP2R2A, PyMT, SV40 ST and E4orf4 was performed using two biological replicates per bait (negative control, wild-type and mutants). Twelve negative control experiments (ten FLAG-alone samples and two 3FLAG-alone samples) were compressed to four “virtual” controls using the four highest spectral counts for SV40 ST, PyMT, E4orf4 and FLAG-PPP2R2A. Sixteen negative control experiments (ten FLAG-alone, two 3FLAG-alone samples, two BirA*-FLAG-alone and two BirA*-FLAG-GFP samples) were compressed to four “virtual” controls using the four highest spectral counts for BirA*-FLAG-PPP2R2A. Eight negative control experiments (all FLAG-alone samples) were compressed to four "virtual" controls using the four highest spectral counts for PPP2CA. For all the SAINT analysis, SAINTexpress version exp3.3[156] was used. SAINT probabilities computed independently for each biological replicate were averaged (AvgP) and reported as the final SAINT score. Proteins with a calculated FDR of ≤1% were considered true positive interactions.

The dot plot was generated with the "Dotplot and Heatmap Generator" implemented

! ! 38! within ProHits using the SAINTexpress file[157]. Parameters were set as follows: primary FDR cutoff = 0.01, secondary FDR cutoff = 0.05, and Maximum spectral count = 50. Hierarchical clustering was performed using Pearson correlation and average linkage. Clustering options: distance metric was Canberra and clustering type was Ward's.

2.6.3 SWATH data analysis The SWATH analysis pipeline (Fig. 4) is the same as that described in [143]. First, raw data generated by each DDA run was searched using ProteinPilot (AB Sciex Beta 4.1.46, revision 460) to create a result file that was subsequently used for library generation. The data was searched against the human complement of the UniProt release 8.8 database (with 40,476 sequences) at ProteinPilot's standard "rapid search" parameter space including common modifications as part of the search using Paragon search engine (v.4.0.0.0). The result files generated by ProteinPilot were used to create a specific library of precursor masses and fragment ions for subsequent SWATH analysis. The library was generated by extracting matched peptide IDs and the matched ions from the original input spectra, and then filtering the matched spectra to produce a list of parent masses, fragment masses and intensities for SWATH processing.

SWATH quantification was attempted for all proteins (with FDR below 1%) in the library files from ProteinPilot search using the software PeakView SWATH Processing Micro App (AB Sciex). Up to 15 peptides were automatically selected from the library for each of the protein. 3 fragmented ions were then automatically selected for each peptide at a peptide confidence of 0.99 and a FDR or 0.01%. The XIC extraction window was of 10 minutes with a tolerance of 0.015 Da. After calculating the peak areas, normalization was performed using the most likely ratio (MLR) method. Normalization was first carried out between the two biological replicates of the same sample, following the normalization between different pair of samples. Data after normalization were then used for fold-change determination

! ! 39!

Figure 4. AP-SWATH data analysis pipeline. Each sample is processed separately for DDA and SWATH on AB Sciex 5600 TripleTOF. The reference spectral library built from all DDA runs is used to retrieve quantitative information from each of the SWATH runs. A series of tools are used to analyze the SWATH data: match SWATH spectra to the reference library generated by DDA files; extract quantitative information from SWATH spectra; normalize the transitions, peptides and proteins using most likely ratio (MLR) normalization method; and determine the fold-change differences between samples and the confidence of the fold change. Figure modified from[143].

! ! 40!

! !

Affinity Purification Sample half half

DDA SWATH

Reference SWATH Spectral Library Spectra

Peak-group Integration

Area Normalization

Reproducibility Metrics

Fold-change Calculation

Visualization

! ! ! ! ! !

! ! 41! firstly over the negative controls and then over the wild-type samples. Only those proteins having a positive fold change over negative controls were displayed.

The dot plot was generated with the "Fold Change Viewer" implemented within ProHits using the data from the file called "Figure 2" after SWATH analysis. Fold change results and confidence results were reconstructed into two separate files. Ascending sorting was performed for fold change data and no clustering was performed. Unlike the current tool implemented within ProHits, the color scheme used was red to blue to clearly show the detailed fold changes.

! ! 42!

CHAPTER 3 RESULTS

3.1 Protein-protein interaction changes imparted by PPP2R1A mutations Since the majority of the cancer-associated mutations of PPP2R1A reported in the COSMIC database are located in the subunit B binding region and that B subunits play an important role in specifying the substrate specificity and localization of PP2A holoenzyme, I first wished to analyze those mutations that may affect the interaction with B subunits. Based on the frequency of identification in COSMIC, six mutations, P179R, R183W, R183Q, S256F, R258H, W257C (mutation positions are shown in Table 3), were selected for analysis to characterize the resulting protein-protein interaction changes. In addition, another two mutations, C329F and Q372L, were also included to characterize the changes in protein-protein interactions imparted by mutations outside the subunit B binding region, if any. These two mutants are also not predicted to affect interaction with the catalytic subunit, and it is not clear whether they are involved in mediating any of the physical interactions with PP2A partners.

These eight PPP2R1A mutants as well as wild-type PPP2R1A were fused with a FLAG tag at their N-terminus into the vector pcDNA5/FRT/TO-FLAG and expressed in HEK293 T-REx cells using the Flp-InTM T-RExTM System (see Materials and Methods for details). A cell line expressing a negative control (HEK293 T-REx cells transfected with the empty vector pcDNA5/FRT/TO-FLAG) was also generated in parallel. Expression was induced by incubating cells with tetracycline for 24 hours, and the relative expression of the mutated proteins was monitored by immunoblotting with an anti-FLAG antibody. Western blot showed that all the PPP2R1A mutants and wild-type PPP2R1A were successfully expressed in HEK293 T-REx cells at similar amounts (Appendix fig. 1).

Anti-FLAG affinity purification was then performed in biological duplicates for each cell line, and the resulting purified proteins prepared for mass spectrometric analysis. Each sample was analyzed in the mass spectrometer twice: once, in standard

! ! 43!

Table 3. Mutations of PPP2R1A No. Amino acid change Coding sequence change 1 p. Q372L c. 1115 A-T 2 p. C329F c. 986 G-T 3 p. R183W c. 547 C-T 4 p. P179R c. 536 C-G 5 P. S256F c. 767 C-T 6 p. R183Q c. 548 G-A 7 p. R258H c. 773 G-A 8 p. W257C c. 771 G-T

! ! 44! data-dependent acquisition mode (DDA), and once in the data-independent acquisition (DIA) mode SWATH. The DDA data was used to identify the proteins (peptides) present in each of my samples, and to generate a reference library to interrogate the SWATH data and retrieve quantitative information using the software tool PeakView that returns area intensities. A statistical tool implemented by our SCIEX collaborators in Matlab was then employed as described previously[143] to normalize the dataset and determine fold change differences for the various mutants in relation to the wild type protein PPP2R1A. Statistically-significant modulated interactions were then displayed in a dot plot format that simultaneously depicts the magnitude of the fold change (color scale) and the confidence on this measurement (edge intensity). Only those proteins having a positive fold change over negative controls were displayed.

The dot-plot (Fig. 5) shows the interaction changes for the eight PPP2R1A mutants relative to wild-type PPP2R1A. It suggests global interactome changes caused by these PPP2R1A mutations. Two of the eight mutants, Q372L and C329F, have an interaction pattern very similar to wild-type PPP2R1A, showing little interaction changes. The other six mutants, however, all result in both increased and decreased interactions. One obvious observation is that interactions with the B and B' class of regulatory subunits are decreased or abrogated, including PPP2R2A, PPP2R2D, PPP2R5A, PPP2R5C, and PPP2R5E. By contrast, there is no major interaction change for the PP2A C subunit, PPP2CA.

These results are consistent with the mutation sites on PPP2R1A: With all the six mutations located in the subunit B binding region of PPP2R1A, it is reasonable that they will only displace regulatory B subunits but not catalytic C subunits. As for Q372L and C329F, since they are both outside the subunit B and C binding region, such mutations are proposed to have no significant influence on protein-protein interactions for PPP2R1A.

! ! 45!

Figure 5. Dot-plot representation of protein-protein interaction changes for eight PPP2R1A mutations relative to wild-type PPP2R1A. Color of the circle indicates the fold change of protein-protein interactions as per the color scale. Border of the circle represents the confidence of each calculated interaction change. Specific interactors are noted as PP2A C subunit, PP2A B55, B56 subunits or known PP2A-interacting proteins. (AP-SWATH data)

! ! 46!

! ! ! Q372L C329F R183W P179R S256F R183Q R258H W257C Q372L C329F R183W P179R S256F R183Q R258H W257C

PPP2R2A PPIB

ARHGEF2 HSPA1A

CDCA4 CIRBP

FAM122A CCT2

ARPP19 HSPA8

TBC1D4 RPL38

PPP2R5A PRMT5

PPP2R5C CMBL

PPP2R2D CANX

PPFIA1 PPP2R1A

PPP2R5E RAB11B

C11orf96 CNP

FECH CCDC6

PPP2CA TIPRL

SNRPD3 RAB6A

PPP2R5D CTPS1

RPS14 GAPDH

PPME1 PDCD2

PPP4C VAT1

STK38 CYP4X1

ANKLE2 IDH3B

Confidence PP2A C subunit PP2A B55 subunits Fold change PP2A B56 subunits Fold change (log10) known PP2A-interacting proteins

-1.5 1.5 Confidence

0 1 ! ! !

! ! 47!

Previous studies have shown that mutations of PPP2R1A such as P179A, R183A, and W257A are involved in causing loss of interactions with different PP2A B subunit family members. It was shown that P179A and R183A result in about 50-90% loss of interaction with PP2A B subunits, and W257A completely abolish such interactions. In addition, the mutation sites P179, R183 and W257 are in the binding sites for PPP2R5C[9, 43, 54, 55]. This suggests that mutations in all of these residues may influence interactions with regulatory B subunits. The results I got agree with these studies, showing that P179R, R183W and W257C lead to decreased interactions with different PP2A B subunit family members, and the loss of interactions with PPP2R5C were successfully confirmed.

However, my results also clearly reveal that interaction changes for B subunits from different families are not the same. PP2A B subunits (PPP2R2 family) have decreased interactions with all of the mutants except Q372L and C329F, but some of these mutants do not significantly displace PP2A B' subunits. This is consistent with the structural differences between the members of different B families. Another interesting observation of the interaction changes for PP2A B subunits is that B subunits from the same family display different patterns of interaction changes for all the PPP2R1A mutants, suggesting that divergent binding sites of B subunits on PPP2R1A may exist. For example, interactions with PPP2R5D are not significantly changed, while interactions with the other three B' subunits are decreased by different mutations of PPP2R1A. To my knowledge, this is the first evidence of a differential binding mode for members of the same regulatory subunits. This data provides opportunities to not only compare the interaction changes between different families of PP2A B subunits, but also within the same B subunit family.

Apart from PP2A B and C subunits, my results show that interactions for the PPP2R1A mutants with some known PP2A-interacting proteins are either strengthened (e.g. R183W and R183Q with PP2A inhibitor TIPRL) or weakened (e.g. R183W, P179R, S256F, R183Q and W257C with PPFIA1[158] and ARHGEF2[159]).

! ! 48!

In addition, I also detected several other proteins that are not known to function in conjunction with PP2A, that bear changed interactions with PPP2R1A mutants. It is interesting that some of the proteins have interaction patterns similar with one or more of the PP2A B subunits. For instance, CDCA4, FAM122A, ARPP19 and TBC1D4 show decreased interaction similar to PPP2R2A and PPP2R2D, and PPFIA1 and ARHGEF2 share an interaction pattern with PPP2R5A. This gives us a chance to classify these interactors into different categories that each typically shows the interaction pattern of one PP2A B subunit, which provides the opportunity to further associate the functions of these proteins with PP2A.

3.2 Validation of selected interaction changes for PPP2R1A mutations After SWATH analysis, interaction changes for five selected proteins, namely PPP2CA, PPP2R2A, PPP2R5A, PPFIA1 and TIPRL, were then validated by immunoprecipitation coupled to immunoblotting. PPP2CA and PPP2R2A were transiently co-transfected into HEK293T cells together with FLAG-tagged PPP2R1A (wild-type and eight mutants). For PPP2R5A, PPFIA1 and TIPRL, HEK293 T-REx cells stably expressing the wild-type scaffolding subunit as well as its eight mutants were used for immunoprecipitation. After protein expression, anti-FLAG affinity purifications were performed and association of the selected proteins was detected by Western blot. The patterns of interactions detected by immunoprecipitation/Western (Fig. 6) matches that of the AP-SWATH.

Significance: PPP2CA is the catalytic subunit of PP2A. PPP2R2A and PPP2R5A are both PP2A regulatory subunits. PPFIA1 interacts with PPP2R5C, PPP2R5D and other PPP2R5 subunits under different conditions[160, 161]. It was recently defined by our collaborator Stéphane Angers as a bridge between PP2A and a kinesin, Kif7, implicated in Hedgehog signaling[158]. Mutational activation of Hedgehog signaling pathway has been linked to several developmental disorders and many human cancers, such as basal cell carcinoma[162-166], and it would be important to better understand the function of PP2A in Hedgehog-driven cancers. TIPRL is a

! ! 49!

Figure 6. Validation of selected protein-protein interaction changes imparted by mutations of PPP2R1A.

For each experiment, anti-FLAG immunoprecipitation was performed, either on the stable cell lines expressing the scaffolding subunit mutants (b–d) or following transient co-transfection (a). (a) FLAG tagged PPP2R1A mutants were transiently co-expressed with

3HA-PPP2CA and GFP-PPP2R2A in HEK293T cells. Mouse anti-FLAG, mouse anti-GFP, mouse-anti HA primary antibodies and anti-Mouse HRP secondary antibody were used respectively. (b, c, d) Rabbit anti-PPP2R5A, goat anti-PPFIA1, rabbit anti-TIPRL and anti-rabbit HRP, anti-goat HRP secondary antibodies were used respectively. In all

IPs, negative control was performed using FLAG tag alone as the bait.

! ! 50!

! ! ! ! ! ! ! ! ! ! ! ! ! !

! ! 51! ubiquitously expressed PP2A inhibitory protein that specifically targets the catalytic C subunit of PP2A, as well as that of the related phosphatases PP4 and PP6. When binding to PP2A C subunit, it restrains the activity of PP2A in the ATM/ATR-regulated DNA damage and repair pathway[167-169]: it is intriguing that here, I am seeing an increase in association between this protein and some of the mutants in the scaffolding subunits of PP2A. The functional consequences of this differential association are not known at present.

The verified interactions of PP2A B and C subunits with the scaffolding A subunit mutants confirm that mutations within the subunit B binding region of PPP2R1A may disrupt the normal function of PP2A holoenzyme by displacing specific B subunits but not C subunit. In addition, the decreased interaction with PPFIA1 suggests that mutations of PPP2R1A also influence PP2A function and activity by preventing the association with PP2A interacting proteins, which may result from the displacing of specific B subunits that serve as the binding partners for these PP2A interacting proteins. Meanwhile, alteration of PP2A function and activity may also be achieved by the recruitment of specific PP2A inhibitors like TIPRL. My results from both SWATH analysis and immunoprecipitation followed by Western blot verification strongly indicate that by changing the protein-protein interactions, in particular decreasing the binding to the B subunits, these PPP2R1A mutations will alter the phosphorylation landscape of the cell. Since many phosphorylation events are thought to act as “pro-growth” and “pro-proliferation”, this unbalance may lead to a significant change in cell growth and cell division.

3.3 Protein-protein interaction changes imparted by PPP2CA mutations Through collaboration with E. Ogris (Vienna), I have obtained eleven PPP2CA point mutations (mutation positions are shown in Table 4, 5), which were analyzed using AP-SWATH to characterize the resulting protein-protein interaction changes in PP2A interaction network. Apart from the mutation R268E, most of the mutants are meant to mimic or abrogate a post-translational modification. Asp and Glu are expected to

! ! 52!

Table 4. Mutations of PPP2CA No. Amino acid change Coding sequence change 1 p. T304A c. [910 A-G][912 C-A] 2 p. T304D c. [910 A-G][911 C-A] 3 p. Y307E c. [919 T-G][921 C-A] 4 p. Y307F c. [920 A-T] 5 p. L309Δ c. 925,926,927 deletion 6 p. L309A c. [925 C-G][926 T-C][927 G-A] 7 p. T304A/Y307F c. [910 A-G][912 C-A][920 A-T] 8 p. T304D/Y307E c. [910 A-G][911 C-A][919 T-G][921 C-A] 9 p. R268E c. [802 C-G][803 G-A][804 T-G] 10 p. R268E/T304D c. [802 C-G][803 G-A][804 T-G][910 A-G] [911 C-A] 11 p. R268E/T304A/Y307F c. [802 C-G][803 G-A][804 T-G][910 A-G] [920 A-T]

Table 5. Schematic representation of the various C subunit mutations Mutation Amino acid change WT 262 APNYCYRCGNQAAI 275...301 TRRTPDYFL 309 T304A 262 APNYCYRCGNQAAI 275...301 TRRAPDYFL 309 T304D 262 APNYCYRCGNQAAI 275...301 TRRDPDYFL 309 Y307E 262 APNYCYRCGNQAAI 275...301 TRRTPDEFL 309 Y307F 262 APNYCYRCGNQAAI 275...301 TRRTPDFFL 309 L309Δ 262 APNYCYRCGNQAAI 275...301 TRRTPDYF 308 L309A 262 APNYCYRCGNQAAI 275...301 TRRTPDYFA309 R268E 262 APNYCYECGNQAAI 275...301 TRRTPDYFL 309 Residues of the β12-β13 loop (262-275) and the C-terminal tail (301-309) of PPP2CA are indicated. The amino acid changes made for each mutant are shown in bold types.

! ! 53! mimic phosphorylation at Thr304 and Tyr307, while Ala and Phe are used in order to prevent phosphorylation at these two sites. In addition, carboxymethylation is prevented either by deletion of the last leucine or by leucine substitution by alanine.

As with the analysis of PPP2R1A cancer-associated mutations showed above, all these eleven PPP2CA mutants as well as wild-type PPP2CA were fused with a N-terminal FLAG tag and expressed in HEK293 T-REx cells alongside a negative control. Expression was also induced by incubating cells with tetracycline for 24 hours, and the relative expression of the mutated proteins was monitored by immunoblotting with an anti-FLAG antibody. Western blot showed that all the PPP2CA mutants and wild-type PPP2CA were expressed at similar amounts in HEK293 T-REx cells (Appendix fig. 2).

Anti-FLAG affinity purification was then performed followed by SWATH analysis. Given the current limitations in the number of samples to be analyzed simultaneously by the statistical tools, the eleven PPP2CA mutants were divided into two groups for analysis, each of them compared to the same wild type samples. Previous studies by the Ogris group had already been performed for the five PPP2CA mutants, T304D, T304A/Y307F, R268E, R268E/T304D and R268E/T304A/Y307F, to check their association with PP2A B subunits and the resulting morphological phenotypes when overexpressed in NIH3T3 cells. Therefore, they were classified into the first group for SWATH analysis. All the other six mutants were included in the second group. As with the analysis of PPP2R1A, only those proteins having a positive fold change over negative controls were displayed.

The dot-plots (Fig. 7) show the interaction changes for the eleven PPP2CA mutants relative to wild-type PPP2CA. My results suggest global interactome changes imparted by different PPP2CA mutations. For the first five PPP2CA mutants, including T304D, T304A/Y307F, R268E, R268E/T304D and R268E/T304A/Y307F, little interaction changes were detected with scaffolding A subunits. However,

! ! 54!

Figure 7. Dot-plots representation of protein-protein interaction changes for eleven PPP2CA mutations relative to wild-type PPP2CA. Color of the circle indicates the fold change of protein-protein interactions as per the color scale. Border of the circle represents the confidence of each calculated interaction change. Specific interactors are noted as PP2A A subunit, PP2A B subunits or known PP2A-interacting proteins. All eleven mutations are divided into two classes for analysis: (a) Mutations T304D, T304A/Y307F, R268E, R268E/T304D and R268E/T304A/Y307F; (b) Mutations T304A, Y307E, Y307F, L309Δ, L309A and T304D/Y307E. Same biological replicate samples of wild-type PPP2CA and negative control were used. But reference library was generated respectively in the two SWATH analyses. (AP-SWATH data)

! ! 55! a T304D T304A/Y307F R268E R268E/T304D R268E/T304A/Y307F T304D T304A/Y307F R268E R268E/T304D R268E/T304A/Y307F

FOXC1 PPP2R1A

ARPP19 PPFIA3

ENSA KRT8

CRTC3 DDX3X

UNG CPSF6

PPP2R2D HNRNPA1

TTC33 TUBB

GRB10 CCDC6

SERTAD4 PPP2R5D

TBC1D4 PPP4R1

SMU1 KRT19

PPP2R2A PRDX3

FAM122A HNRNPK

ARHGEF2 RIOK1

GIGYF2 PPP4C

KRT18 TUBB4B

CAMSAP3 PDCD5

PPP2R5E MST4

RAVER1 ANKLE2

PPP2R1B STRN3

NOC4L PPME1

CCAR2 IGBP1

NOP14 RPS3A

PPFIA1 NUDT21

RBM14 PPP2R3B

MYCBP PPP2R3A

NHSL1 TIPRL

Confidence PP2A A subunits

Fold change PP2A B subunits known PP2A-interacting proteins Fold change (log10)

-1.5 1.5 Confidence

0 1

! ! 56!

! ! ! ! b T304A Y307E Y307F L309A T304D/Y307E

PPP2R5A

PPFIA3

PLEKHA5

PPP2R5E

ARHGEF2 PP2A B subunits PPP2R5D known PP2A-interacting proteins PPFIA1

PPME1 Confidence TIPRL Fold change PDCD2

IGBP1

ANKLE2 Fold change (log10)

CCT4 -1.5 1.5 ST13 Confidence HIST1H1C

PPP4C 0 1

! ! ! ! ! ! ! ! ! ! ! ! ! !

! ! 57! decreased interactions were identified for members from three regulatory subunit families: PP2A B, B' and B''. STRN3, which belongs to PP2A B''', showed almost no interaction change for these five PPP2CA mutants.

Unlike PPP2R1A mutations that cause different interaction changes for B subunits from the same family, different members of the same regulatory family display similar patterns of interaction alterations for these five PPP2CA mutants. Apart from PP2A subunits, several known PP2A interacting proteins were also marked in the dot-plot to illustrate interaction changes caused by PPP2CA mutations.

Significance: As mentioned above in 3.2, PPFIA1 functions in conjunction with PP2A in the regulation of Hedgehog signaling pathway, and TIPRL is a specific inhibitory protein of PP2A C subunit. PPFIA3 is a paralog of PPFIA1. ENSA specifically inhibits PP2A when phosphorylated at Ser-67 during mitosis. It interacts with PPP2R2D and inhibits its activity, leading to inactivation of PP2A holoenzyme. This is an essential condition to keep cyclin-B1-CDK1 activity high during M phase, which will result in the dysregulation of cell cycle[170-174]. ARPP19 is a paralog of ENSA. As mentioned in introduction, PPME1 is essential for the demethylation of the C-terminal L309 of PP2A catalytic subunit, which plays an important role in interacting with PP2A A and B subunits.

For the second group of PPP2CA mutants, including T304A, Y307E, Y307F, L309Δ, L309A and T304D/Y307E, interaction changes were only detected for three PP2A regulatory subunits, PPP2R5A, PPP2R5D, and PPP2R5E. However, alterations in the interaction with PPFIA1, PPFIA3, PPME1 and TIPRL were also detected. Another interesting observation is that these six PPP2CA mutants cause significant increased interactions, although all with proteins that have no known function related to PP2A so far.

Because of the current limitations in the number of samples to be analyzed

! ! 58! simultaneously by SWATH analytical approach, there is little overlap of the detected protein-protein interactions for the first and second groups of PPP2CA mutants, making it difficult to compare the resulting interaction changes across all the mutants. Therefore, SAINT analysis was also performed using the data dependent acquisition only to characterize the interactome for all PPP2CA mutants as well as wild-type PPP2CA. The dot-plot (Appendix fig. 3) shows some interesting interaction changes for PP2A-interacting proteins. Corresponding to the decreased interaction with PP2A B' subunits, point mutations T304A, T304D, Y307E, Y307F, L309Δ and L309A lose their interaction with PPFIA1, PPFIA3 and ARHGEF2, which associate with PP2A holoenzyme via PP2A B' subunits. Only T304A and T304D have increased interaction with TIPRL, suggesting the important role of Thr304 in recruiting TIPRL. LCMT1, which catalyzes carboxymethylation at Leu309, has a significant increased interaction with L309Δ but not with L309A. PPME1, which functions in reverse with LCMT1, interacts more with both L309Δ and L309A.

As mentioned in the introduction, I was particularly interested in characterizing the interactions changes due to mutation of arginine 268 to a glutamic acid, as this mutation was found by our collaborator Egon Ogris to induce striking cell volume increases. Among the characterized interaction changes, it is really interesting to note the dissociation of ANKLE2 by all three mutants bearing this substitution, R268E, R268E/T304D and R268E/T304A/Y307F. The importance of studying ANKLE2 will be introduced in the next session. I also detected increased association with two of the mutants, R268E and R268E/T304A/Y307F, and two proteins, IK and SMU1. While I have not been able to validate these changes in interactions by immunoblotting so far, these are potentially important: in fact, only the two mutants with the strongest phenotype, R268E and R268E/T304A/Y307F exhibited this increase, while the R268E/T304D mutant displayed no fold change in association of IK (also known as RED) and SMU1 in comparison to the wild type. While IK and SMU1 are not well studied, these proteins are known to associate with one another[175] (also in the Gygi dataset available in BioGRID), and associate with the spliceosome[175], and were

! ! 59! identified to play an important role in viral splicing [176]. Recent data also suggest that SMU1 participates in the regulation of replication checkpoint[177] and that IK is a spindle pole associated protein that interacts with MAD1 and is required for the spindle assembly checkpoint[178]. These two papers provide intriguing hypotheses for checkpoint deregulation in the large cells resulting from the overexpression of the R268E constructs.

3.4 Validation of the interaction between ANKLE2 and PPP2CA mutants ANKLE2 was first demonstrated to physically associate with the catalytic C and scaffolding A subunits of PP2A in a large scale study of the PP2A interactome[179]. Unpublished work from our laboratory using ANKLE2 as a bait detected high amounts (based on spectral counts) of both the A and C subunits, but not of any PP2A regulatory B subunit, suggesting that ANKLE2 associates in an unusual complex with PP2A (McBroom-Cerajewski, Mullin and Lin, unpublished).

In order to validate the identified interaction changes for ANKLE2, I fused ANKLE2 to a N-terminal triple HA tag and transiently co-transfected it into HEK293T cells with FLAG-tagged PPP2CA mutants. Anti-FLAG immunoprecipitation was then performed and Western blotting performed to monitor the association of ANKLE2 with the mutants. The pattern of interactions detected by immunoprecipitation followed by Western blotting (Fig. 8) matches that of the AP-SWATH, with only R268E, R268E/T304D and R268E/T304A/Y307F losing their interaction with ANKLE2.

Significance: According to the data from Ogris' lab, expression of PPP2CA R268E in NIH3T3 cells induced a massive increase in cell volume and the formation of large, irregularly shaped nuclei. Expression of R268E/T304A/Y307F exhibited even stronger cell cycle and morphological phenotypes. However, the NIH3T3 cells expressing R268E/T304D only showed little alterations in cell morphology and cell volume[78]. Interestingly, my AP-SWATH results indicate that all mutants containing

! ! 60!

Figure 8. Validation of interaction changes for ANKLE2 imparted by mutations of PPP2CA. FLAG tagged PPP2CA mutants were transiently co-expressed with 3HA-ANKLE2 in HEK293T cells. Anti-FLAG immunoprecipitation was then performed. Mouse anti-FLAG, mouse-anti HA primary antibodies and anti-Mouse HRP secondary antibody were used respectively.

! ! 61!

! ! ! ! ! ! ! ! ! ! !

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

! ! 62! the R268 mutation lose their interaction with ANKLE2. ANKLE2 (also called Lem4) functions in control of postmitotic nuclear envelope (NE) formation. It coordinates the regulation of BAF (barrier-to-autointegration factor) dephosphorylation by interacting with and inhibiting VRK-1, a kinase that phosphorylates BAF during mitosis and meiosis, and by supporting PP2A for dephosphorylating BAF. This results in the binding of BAF to the chromosome and finally facilitating NE reassembly[180, 181]. Based on this demonstration, it is reasonable to predict that the R268 site plays an important role in maintaining the normal size and shape of cell nuclei through the interaction with ANKLE2. Further study of R268E mutation may help explain the irregularly shaped nuclei and the largely increased cell volume in the morphological phenotypes.

3.5 Interacting proteins of PPP2R2A I have obtained seven PPP2R2A point mutations (mutation positions are shown in Table 6) through collaboration with P. Branton (McGill). All the mutations sites are located in the subunit A binding region on PPP2R2A. Previous work done by the Branton laboratory suggested that all the single mutations are incapable of stably binding to either PP2A A or C subunits, and the double mutations are assumed to prevent even transient interactions.

In order to see whether these free PPP2R2A mutants are capable of recruiting more PP2A substrates, the expanded landscape of their interactors was first characterized by AP-MS. Just as what had been done to PPP2R1A and PPP2CA, all the seven PPP2R2A mutants and wild-type PPP2R2A were fused with a N-terminal FLAG tag and expressed in HEK293 T-REx cells alongside negative controls. Anti-FLAG affinity purification was performed and then followed by MS analysis. However, here, I only performed standard data dependent acquisition, and used the statistical tool SAINT to assess the high confidence interactions by comparing the spectral count data across my two biological replicates to those across my negative controls.

! ! 63!

Table 6. Mutations of PPP2R2A No. Amino acid change Coding sequence change 1 p. V154E c. [461 T-A] 2 p. V154R c. [460 G-C][461 T-G] 3 p. R257E c. [769 A-G][770 G-A] 4 p. E190K c. [568 G-A] 5 p. C239L c. [715 T-C][716 G-T] 6 p. E190K/V154E c. [461 T-A][568 G-A] 7 p. C239L/V154E c. [461 T-A][715 T-C][716 G-T]

! ! 64!

Analysis was first performed towards three of the mutants, V154E, V154R and R257E. As expected, the MS results (Fig. 9) show that wild type PPP2R2A readily recovered the catalytic and scaffolding subunits of PP2A, and also several previously reported (HDAC5[182], ENSA, ARPP19[170, 174]) or putative new interaction partners.

Also as expected, all three mutants of PPP2R2A resulted in loss of association with both A and C subunits. Our hope was that by preventing this association, we may stabilize some transient interactions between the mutant proteins and putative substrates. However, our results were in general fairly disappointing, and only two new interaction partners were detected with high confidence with mutations of Valine 154, namely the E3 ubiquitin ligases UBR5 and TRIM32. Furthermore, while a few interactions (including with TBC1D4, HDAC5, SERTAD4 and CDCA4) are maintained in the Val154 mutants, most of the other interactions observed with the wild type were lost in these mutants. The Arg257Glu mutant did not recover any confident interaction. While I still do not know the exact cause of this lack of interacting partners, it is possible that this might result from the low expression level of these FLAG tagged proteins in HEK293 T-REx cells in comparison to the wild type proteins (Appendix fig. 4). Efforts to increase the expression of the mutant proteins by attempting to prevent proteasomal degradation (based on the observation of the interaction with E3 ligases) were not successful (data not shown), and this approach was put aside.

Because we have noticed that different fusion tags sometimes lead to stabilization of protein levels (perhaps through partial inactivation of a protein), efforts were then made to characterize the interactors of these PPP2R2A mutants using BioID, which encodes a much larger protein tag. All the mutants were fused with a BirA*-FLAG tag at its N-terminus. After protein expression, streptavidin affinity purification was performed and following the same MS analysis. The problem of protein expression was solved this time with all the mutants showing a similar expression level compared

! ! 65!

Figure 9. Characterization of the interacting proteins of wild-type PPP2R2A and PPP2R2A mutants. Bona fide interacting partners were identified using anti-FLAG AP coupled with MS. Circle shading indicates the number of interactor spectra detected as per the color scale. Circle size indicates the number of interactor spectra detected in one bait, relative to the greatest number of spectra detected in any of the baits (i.e. for a prey with 20 and 10 spectra detected, both circles will be shaded light grey but one will be twice as large as the other). Border of the circle represents different FDR thresholds. Specific interactors are noted as PP2A A/C subunit and known PP2A-interacting proteins. (AP-MS data)

! ! 66!

! ! ! WT R257E V154E V154R WT R257E V154E V154R ● ●

ARHGAP21 TTC33 ● ● ● ● PPP1CA LRCH2 ● ● ● ● MPHOSPH9 ENSA ● ● ●

SIK3 SMU1 ● ● ● ● ● ● RAB11FIP5 WDR61 ● ● ● ● CCDC6 UBR5 ● ● ● ● ● PTPDC1 PPP2R1A ● ● ● MAST4 XPNPEP3 ● ● ECSIT SHOC2 ● ● ● ● ● GRB10 TBC1D4 ● ● ● ● TSEN34 PPP2CA ● ● ● ● ● PPP1R13L DOCK7 ● ● ● ● PLEKHA6 TRIM32 ● ● ● PPME1 CDCA4 ● ● ● ● PPP2R1B HDAC5 ● ● ● ● ● ● UNG E1B ● ● ● FAM122A SIK2 ● ● ● ● ● CRTC3 SERTAD4 ● ● ● FAM122B IER5 ● ● ● ● ● ARPP19 NF1 ● ●

FBXL16 ● ●

Spectral Count PP2A A subunit PP2A C subunit 0 50

known PP2A interactor

● ● Relative abundance

! ! 67! to wild-type PPP2R2A (Appendix fig. 5).

However, there was still not much interesting information coming out (Fig. 10). It was confirmed by MS analysis that only wild-type PPP2R2A interacts with PP2A A and C subunits, though already this dataset is far less rich than that of the standard FLAG purification experiment. However, the major discovery for the seven PPP2R2A mutants was that they mainly interact with chaperonin containing TCP1 complex subunits and with components of the HSP90 machinery, and particularly with the HSP90 co-chaperone NUDC[183]. The association with these chaperones strongly suggested the instability of PPP2R2A mutants when expressed in HEK293 T-REx cells. Based on these two MS analyses, it might not be appropriate to study the interactome of PPP2R2A mutants using the currently available mass spectrometry-based systems. Other methods will be needed if one wants to pursue the study of these PPP2R2A mutations.

3.6 Interacting proteins of PP2A-related tumor virus proteins 3.6.1 SV40 small T antigen interacting proteins In order to characterize the interactome of SV40 ST, both wild-type ST and a C-terminal truncated mutant that loses its Zinc-binding domain were fused with a triple FLAG tag and used for AP-MS analysis as described above (Data dependent acquisition, and SAINT analysis).

The dot-plot (Fig. 11) shows the binding partners for the wild-type SV40 ST and the ST mutant. This analysis demonstrated that wild-type SV40 ST binds predominantly to PP2A scaffolding A subunits, PPP2R1A and PPP2R1B. Previous studies assume that ST can form a stable complex only with the PP2A core dimer and not with the holoenzyme. My data partially support this assumption since no interaction was detected between ST and any of the PP2A regulatory B subunits. In contrast, the ST mutant gains strong interactions with heat shock proteins, including heat shock protein 70 family members and BAG family molecular chaperone regulators, with a

! ! 68!

Figure 10. Characterization of the interacting proteins of wild-type PPP2R2A and PPP2R2A mutants using BioID. Bona fide interacting partners were identified using BioID coupled with MS. Circle shading indicates the number of interactor spectra detected as per the color scale. Circle size indicates the number of interactor spectra detected in one bait, relative to the greatest number of spectra detected in any of the baits. Border of the circle represents different FDR thresholds. Specific interactors are noted as PP2A A/C subunits and chaperonin containing TCP1 complex subunits. (AP-MS data)

! ! 69!

! ! ! ! V154E L WT R257E V154E V154R C239 C239L ● ● ● ● ● ● ● CCT2 ● ● ● ● ● ● ● ● ● CCT8 ● ● ● ● ● ● ● CCT5 ● ● ● ● ● ● ● ● CCT7 ● ● ● ● ● ● ● ● ● TCP1 ● ● ● ● ● ● ● CCT4 ● ● ● ● ● ● ● ● ● CCT3 ● PPP2CB PP2A A subunit ● ● ● ● ● ● ● ● NUDC PP2A C subunit ● ● ● ● ● ● ● ● E1B chaperonin containing TCP1 complex subunit ● ● ● ● ● ● CDCA4 ● ● ● ● ● ● ● SERTAD4 ●

● ● Spectral Count ● ● ● ● RBM7 ● ● ● ● ● ● ● ● ● NUDCD3 ● ● ● ● ● ● PPP2R1A ● ● ● TTC33 ● UBE2J1 ● RAB11FIP5 ● ● Relative abundance PPP2R1B ● ! ! ! ! ! ! ! ! ! ! !

! ! 70!

Figure 11. Characterization of the interacting proteins of wild-type SV40 ST and ST mutant. Circle shading indicates the number of interactor spectra detected as per the color scale. Circle size indicates the number of interactor spectra detected in one bait, relative to the greatest number of spectra detected in any of the baits. Border of the circle represents different FDR thresholds. Specific interactors are noted as PP2A A/B subunits, heat shock protein 70 family and BAG family molecular chaperone regulator. (AP-MS data)

! ! 71!

Mutant WT ● PPP2R1B ● GLB1 ● CTSA ● SPATA20 ● HTRA2 ● HSPA8 ● ● HSPA1B ● ●

HSPA9 ● ● ● HSPA1L ● GRPEL1 ●

PPP2R1A ● ●

HSPA4 ● ●

BAG2 ● PP2A A subunit ●

● heat shock protein 70 family HSPH1

● BAG family molecular chaperone regulator HSPA4L ●

● Spectral Count HSPA6 ● ●

STUB1 ● 0 50

● HSPA2 ● ● ● HYOU1 ● BAG5 ● ● Relative abundance

! ! 72! total loss of its binding to PP2A subunits. The association with these heat shock proteins may result from the sequence homology between the ST N-terminal J domain and DnaJ protein from E. coli. DnaJ protein functions as part of the HSP70 chaperone. The J domain is known to stimulate the ATPase activity of HSP70 proteins, modulating HSP70 family chaperone activity[184, 185]. Although not much interesting information was revealed from the MS analysis, at least it showed that SV40 ST only binds to PP2A A subunits, which partially confirms the model that ST interacts with PP2A by displacing B subunits.

3.6.2 Polyomavirus middle T antigen interacting proteins In order to identify the interactors of PyMT, FLAG-tagged PyMT was expressed in HEK293 T-REx cells, followed by AP-MS analysis. The MS results (Fig. 12), however, indicated that at least in this expression system PyMT interacts predominantly with heat shock protein 70 family members, such as HSPA1B, HSPA6, HSPA2, etc. Other major interactors of PyMT are also protein folding machinery components, including BAG and DnaJ families of molecular chaperones. Even the association with PP2A subunits was not detected by MS. This result strongly suggests that PyMT is not stable when expressed in HEK293 T-REx cells, or that the tag affects this function. As with MS analysis for PPP2R2A, it might not be proper to study the interactome of PyMT using the established AP-MS system in our lab. Other methods will be needed to further the study of PyMT interactome.

3.6.3 E4orf4 interacting proteins Through collaboration with P. Branton, I have obtained four mutations of E4orf4; one Class I mutation and three Class II mutations (mutation positions are shown in Table 7). Previous work done by the Branton laboratory suggested that the Class I mutation lost its interaction with PP2A subunits, however, the three Class II mutations still kept the interactions with PP2A.

AP-MS analysis (DDA, SAINT) was first performed for wild-type E4orf4 and the

! ! 73!

Figure 12. Characterization of the interacting proteins of PyMT. Bona fide interacting partners were identified by SAINT. Spectral count information is displayed with FDR ≤ 0.01. Specific interactors are noted as heat shock protein 70 family, DNAJ heat shock protein 40 family and BAG family molecular chaperone regulator. (AP-MS data)

! ! 74! PyMT PyMT ● ● ERGIC2 LPHN2 ● ● SLC27A2 CAND2 ● ● ESYT2 B3GNT1 ● ● NCSTN DHX32 ● ● CHP1 SLC27A3 ● ● EFNB2 NDUFS2 ● ● DGKE HSPA2 ● ● ILVBL DNAJA2 ● ● USP11 DNAJB1 ● ● TMX1 FKBP8 ● ● OCLN DNAJC3 ● ● NDUFB10 ● ● ACSL3 ● ● NDUFS3 ATP2B1 ● ● C2orf47 GOLPH3 ● ● ALDH3A2 GRAMD1A ● ● FDFT1 TRIM32 ● ● NDUFAF4 BA ● ● TMX3 BAG2 ● ● LMBR1 ATP2A2 ● ● ITGB1 HSPA6 ● ● NRP1 DNAJC7 ● ● MOSPD2 HSPA1B ● ● DNAJC16 HSP ● ● SPTLC1 HSPA1L ● THEM6

Spectral Count heat shock protein 70 family DNAJ heat shock protein 40 family 0 BAG family molecular chaperone regulator

● ● Relative abundance

! ! 75!

Table 7. Mutations of E4orf4 No. Amino acid change Coding sequence change 1 p. R81A/F84A c. [241 C-G][242 G-C][250 T-G][251 T-C] [252 T-A] 2 p. L54A c. [160 T-G][161 T-C][162 G-T][163 A-C] 3 p. K88A c. [262 A-G][263 A-C] 4 p. D99A c. [296 A-C]

! ! 76! class I mutant R81A/F84A, expressed stably in the Flp-In T-REx HEK293 cell system as FLAG fusions. According to the MS results (Fig. 13), only wild-type E4orf4 interacts with PP2A A and B55 subunits, which is consistent with the previous demonstration that class I mutants cause the loss of interaction with B55. Interestingly, in addition to subunits of PP2AB55 holoenzymes, I found association with the other major cellular serine/threonine phosphatase, protein phosphatase 1 (PP1) with E4orf4. Several PP1 regulatory subunits were also identified as E4orf4 interactors, notably members of the ASPP family, TP53BP2, PPP1R13L, PPP1R13B[186]. Interestingly, the R81A/F84A mutant partially maintained the interactions with PP1 and the ASPP family proteins.

Both the PP2A and ASPP-PP1 phosphatases are major regulators of the Hippo signaling pathway, which controls expression of cell growth/survival genes. Thus the results suggest that interactions with both the PP2AB55 and ASPP-PP1 phosphatases may be essential to cause a fatal inhibition of Hippo signaling and thus cell death. This effect may also account for the cancer cell specificity of E4orf4 as many human tumors rely on the Hippo pathway for their enhanced proliferation[187, 188].

The three class II E4orf4 mutants were then added into AP-MS analysis together with wild-type E4orf4 and R81A/F84A. According to the AP-MS results (Fig. 14), the class II mutants still interact with PP2A subunits, including PPP2R1A, PPP2R1B, PPP2CA, PPP2R2A, PPP2R2C and PPP2R2D. The results support the demonstration that unlike class I mutants, class II E4orf4 mutants can still bind B55. Because of the low expression of L54A and K88A in HEK293T-REx cells (data not shown), not much interesting interaction results were detected for these two mutants, though they still clearly associated with PP2A components as expected. Class I mutant R81A/F84A and class II mutant D99A interact with these ASPP-PPA subunits at similar amounts, suggesting that the association with ASPP-PP1 complex does not differ between different mutation classes, and that it is likely that class II mutants perturb something else than ASPP-PP1 interaction. While my results did not highlight

! ! 77!

Figure 13. Characterization of the interacting proteins of wild-type E4orf4 and the class I E4orf4 mutant. Bona fide interacting partners were identified by SAINT. Circle shading indicates the number of interactor spectra detected as per the color scale. Circle size indicates the number of interactor spectra detected in one bait, relative to the greatest number of spectra detected in any of the baits. Border of the circle represents different FDR thresholds. Specific interactors are noted as PP2A A/B/C subunits, PP1 catalytic and regulatory subunits. (AP-MS data)

! ! 78! R81AF84A WT R81AF84A WT ● ● ● SIK3 SAPCD2 ● ● ● CNNM4 PPP1R13B ● ● ● CNNM2 ● ●

DNPEP PPP2R2D ● ● ●

BCOR GIGYF2 ● ● ●

CNNM3 RAVER1 ● ● ●

CRTC2 TNRC6B ● ● ● ANKRD17 RNF214 ● ● ●

CRTC3 SHROOM3 ● ● ●

PPP2R1B EIF4E2 ● ● ● TBKBP1 DCAF7 ● ● ● ● PHLDB2 SDCCAG3 ● ● ● FCHSD1 PNMA1 ● ● ● SYDE1 RASSF7 ● ● ● KSR1 PPP1CA ● ● TBK1 RAI14 ● ● NCOR2 PPP2CA ● ● RSPH3 UACA ● ● PPP2R2C TRIOBP ● ● TANC2 SPECC1L ● ● GPBP1 PPP1R12B ● ● AUTS2 SPECC1 ● ● SEC16A PTPN13 ● ● SHKBP1 NUAK1 ● ● FBXO7 E1B ● ●

ZNF629 SF3A3 ● ● ●

PLEKHA6 PPP1R12C ● ● ● ZKSCAN4 ● ● PTPN14 PNMA2 ● ● ● MAP3K3 CALU ● ● ●

CCDC6 PPP1CB ● ● ● ● RNF187 PARD3 ● ● ● PRKCI ● ● ● MAST2 PPP1R13L ● ● ● KCTD3 ● ● CCDC120 PPP2CB ● ● PHLDB1 PPP2R1A ● ● ● ● RASSF8 PPP2R2A ●

Spectral Count PP2A A subunits PP2A C subunits 0 PP2A B subunits PP1 catalytic subunits PP1 regulatory subunits PP1 regulatory subunits; ASPP family protein ● ● Relative abundance

! ! 79!

Figure 14. Characterization of the interacting proteins of wild-type E4orf4, class I mutant and class II mutants. Bona fide interacting partners were identified by SAINT. Circle shading indicates the number of interactor spectra detected as per the color scale. Circle size indicates the number of interactor spectra detected in one bait, relative to the greatest number of spectra detected in any of the baits. Border of the circle represents different FDR thresholds. Specific interactors are noted as PP2A A/B/C subunits, PP1 catalytic and regulatory subunits. (AP-MS data)

! ! 80! R81AF84A D99A WT K88A L54A R81AF84A D99A WT K88A L54A ● ● ● ● ● TP53BP2 ● BCOR ● ● ● ● ● PPP1R13B ● NCOR2 ● ● ● ● ● SAPCD2 ● TANC2 ● ● ● ● ● CCDC85C ● ANKRD17 ● ● ● ● ● PARD3 ● FCHSD1 ● ● ● ● ● ● PPP2CA ● AUTS2 ● ● ● ● ● ● PPP2R1A ● MAST2 ● ● ● ● ● ● PPP2R2A ● KSR1 ● ● ● ● ● ● PPP1R13L ● PTP4A1 ● ● ● ● ● ● ● ● ● PPP2R2D ● GIGYF2 ● ● ● ● ● ● ● ● ● PPP2R1B ● TNRC6B ● ● ● ● ● ● ● ● ● USP15 PPP1CA ● ● ● ● ● ● MRPS24 DCAF7 ● ● ● ● ● POLR1B SEC16A ● ● ● ● ● NOP56 CRTC3 ● ● ● ● ● MRPS9 DNPEP ● ● ● ● POLR1A CNNM3 ● ● ● ● ● NUAK1 CNNM4 ● ● ● ● ● SPECC1L CNNM2 ● ● ● ● UACA RNF187 ● ● ● ● PPP1R12B RICTOR ● ● ● ● SPECC1 PALLD ● ● ● ● ● ● E1B ● ALDH16A1 ● ● ● ● PPP1R12C ● ROPN1L ● ● ● ● TRIOBP ● GPBP1 ● ● ● ● ● ● PRKCI ZNF703 ● ● ● ● ● ● PNMA1 CRTC2 ● ● ● ● ● ● ● ● MPP5 SIK3 ● ● ● ● ● ● ● RASSF8 PPP2R2C ● ● ● ● ● ● SDCCAG3 USP9Y ● ● ● ● ● ● RASSF7 SF3A3 ● ● ● ● ● ● ● ● SHROOM3 PNMA2 ● ● ● ● ● CCDC120 PPP1CB ● ● ● ● ● ● ● PLEKHA6 TCOF1 ● ● ● ● ● ● PHLDB1 DDX5 ● ● ● ● ● ● ● ● SHKBP1 CCDC6 ● ● ● ● ● ● ● PHLDB2 ● MRPS27 ● ● ● ● PTPN14 ● PTP4A2 ● ● ● ● ● CNNM1 ● RSPH3 ● ● ● ● ● ● SYDE1 FNIP1 ● ● TBK1

Spectral Count PP2A A subunits PP2A C subunits 0 50 PP2A B subunits PP1 catalytic subunits PP1 regulatory subunits PP1 regulatory subunits; ASPP family protein ● ● Relative abundance

! ! 81! any loss of interaction specific to class II mutants, they did reveal several interactions which were decreased or abolished in both class I and class II mutants, such as the interactions with CCDC120, PLEKHA6, PHLDB1, etc. Those should be investigated to further understand the mechanism of killing via E4orf4.

! ! 82!

CHAPTER 4 FUTURE DIRECTIONS AND DISCUSSION

4.1 Significance of the work This study was focused on figuring out the function and activity changes of PP2A holoenzyme caused by PP2A subunit point mutations and PP2A-related tumor virus proteins. In this study, eight point mutations of PP2A scaffolding subunit PPP2R1A and eleven point mutations of catalytic subunit PPP2CA were analyzed by AP-SWATH. Significant protein-protein interaction changes in the normal PP2A interaction network imparted by these PP2A mutations were identified. It is revealed that PPP2R1A mutations might lead to changes in PP2A function and activity by displacing specific PP2A B subunits, by preventing the association with PP2A regulatory proteins, and by recruiting PP2A inhibitory proteins. Mutations of PPP2CA C-terminal tail that change its post-translational modifications also result in alterations in the interaction with specific B subunits and some known PP2A-interacting proteins. It is the first insight into the detailed interaction changes in the PP2A interaction network caused by PP2A A and C subunit mutations. These results provide us with an opportunity to understand the formation of different PP2A holoenzymes and the consequences of PP2A somatic mutations detected in cancers.

The second part of this study characterized the interactomes of three PP2A-related tumor virus proteins. The detected interactors of SV40 ST and E4orf4 confirm the previous demonstration of these two viral oncoproteins: SV40 disrupts the function of PP2A by displacing PP2A B subunits; E4orf4 class I mutations lose the interactions with PP2A subunits but the class II mutations keep such interactions. In addition, I also discovered that E4orf4 interacts with ASPP-PP1 complex subunits, revealing its possible involvement in the regulation of Hippo signaling pathway. These new findings give us a chance to better understand the PP2A-dependent and PP2A-independent functions of these PP2A-related tumor virus proteins. When combining these two parts together, this study deepens our understanding of PP2A as a tumor suppressor.

! ! 83!

4.2 Discussion In the characterization of protein-protein interaction changes caused by PPP2R1A mutations, one of the most important findings is that subunits from different regulatory B families have different interaction patterns with the eight PPP2R1A mutants. This discovery is consistent with the sequential and structural differences between PP2A B subunits from different families. Although the PP2A B subunit families are functional related, which means that they can all interact with PP2A core dimer and can specify the substrate specificity and localization of different PP2A holoenzymes, the amino acid sequences of B, B', B'' and B''' subunits show little homology to each other. Therefore, no common motif that mediates the interaction between PP2A core dimer and B subunits has been discovered[189]. It is quite interesting that the common PP2A A and C subunits can interact with the highly diverse regulatory B subunits. Different amino acid residues from the subunit B-binding region in PPP2R1A may play a role in binding to different B subunits. This may explain the diversity of interaction change patterns for B subunits caused by different point mutations of PPP2R1A. According to the AP-SWATH results, however, even B subunits from the same regulatory family have different interaction patterns with the eight PPP2R1A mutants, which would provide a new layer of complexity in PP2A holoenzyme assembly and regulation. Although members from the same B family have high similarity in their sequence (e.g. the B family members are 80–90% identical and the B' family members are 70% identical to each other), their level of expression varies by tissue type. For instance, it is demonstrated that PPP2R5A and PPP2R5C are highly expressed in heart and skeletal muscles and PPP2R5B has a high expression level in brain[189]. The specified localization of PP2A holoenzymes may result from the different expression level of PP2A B subunits in various tissue types and the different interaction patterns of PP2A with these B subunits. In a word, the interaction mechanism of PP2A core dimer and B subunits is very complicated and does not have a uniform model. More details should be identified for the interaction between PP2A core dimer and B subunits in order to understand the formation of different PP2A holoenzymes.

! ! 84!

Unlike the direct interaction between PPP2R1A and the B subunits, the association of most other interactors to PPP2R1A must be bridged by some specific B subunits. For instance, PPFIA1 binds to PP2A holoenzyme through its interaction with PPP2R5 subunits. Since point mutations of PPP2R1A lead to the dissociation of PPP2R5 subunits from PP2A core dimer, PPFIA1 is also expected to be displaced from the PP2A holoenzyme, which is what my results confirm. This may also explain the decreased interaction for some of other the PP2A interacting proteins. As for the increased interactions, one possible explanation is that along with the dissociation of specific B subunits, the binding surface of some PP2A interactors may get wider on the PP2A core dimer, resulting in an easier recruitment of such interactors. Other possible mechanisms may also exist, including the conformational change of PP2A core dimer that stabilizes the binding of these PP2A interactors, or the assistance of some cofactors that help dock the interactors onto PP2A core dimer.

As mentioned above in 3.3, an interesting observation of the SWATH analysis for the PPP2CA mutants is that only the mutants with the mutation R268E lose their interaction with ANKLE2, which is involved in the regulation of nuclear envelope formation post mitosis. Since it is revealed that the overexpression of R268E and R268E/T304A/Y307F mutants can lead to a massive increase in cell volume and the formation of large, irregularly shaped nuclei, it is reasonable to relate these phenotypes to the association with ANKLE2. The previous studies of these PPP2CA mutants were performed in NIH3T3 cells. Because our laboratory has been mostly using HeLa cells for immunofluorescence and RNA interference studies, I aimed to reproduce these results in a HeLa cell line: wild-type PPP2CA as well as three PPP2CA mutants, R268E, T304A/Y307F and R268E/T304A/Y307F, were transiently transfected into HeLa cells and expressed for 72 hours. Immunofluorescence was then performed. Anti-FLAG, lamin A antibodies, as well as DAPI and phalloidin, were used for staining in order to compare the size and shape of the nucleus and the cell itself. I was expecting, based on the NIH3T3 data from the Ogris lab that overexpression of R268E and R268E/T304A/Y307F would result in large and

! ! 85! irregularly shaped nuclei and also an increase in cell volume in HeLa. However, according to the immunofluorescence images (Fig. 15), no obvious morphological phenotypes were identified. HeLa cells expressing PPP2CA mutants or wild-type PP2A had normal nuclei. Meanwhile, there was no visible difference between the cell sizes. Further work is needed to figure out whether the proposed phenotype can be achieved by making changes to the experimental conditions, namely monitoring the expression levels obtained here and testing different cell types.

Limitations of the current SWATH approach Although the SWATH analysis of PPP2R1A and PPP2CA mutants identified many significant protein-protein interaction changes imparted by these point mutations, there are still some limitations of the current computational and statistical tools for SWATH analysis. The first limitation of current DIA data analysis strategy is the generation of reference library. The same amount of sample has to go through DDA analysis first in order to generate the reference library for matching the spectra in the SWATH runs, which takes a lot of time and half of the sample. Although it is possible to obtain the library independently, there are differences in the fragmentation patterns and retention time between different experiments, resulting in problems to match the spectra from SWATH. Another limitation is the assessment of the confidence of the matched ion peaks. The current analysis strategy of DIA data relies on the techniques developed for targeted MS approaches like M/SRM. Although the peak matching method for M/SRM analysis has been well developed, it is not extensively evaluated for DIA data. It is also problematic that the scoring system of DIA analysis has not incorporated the information generated by MS1 scan. Because of the wide isolation window of SWATH, a lot of peptides may appear in the same window and share their fragmented ions. The interference will affect the analysis of SWATH data if the accurate MS1 information is not taken into account for scoring. The negative influence of these limitations intensifies when the complexity of the sample and the size of the library increase[190, 191]. Another big problem of my SWATH analysis is that the analytical method is very sensitive to global changes in

! ! 86!

Figure 15. Immunofluorescence of Hela cells expressing wild-type PPP2CA and PPP2CA mutants. Hela cells were transiently transfected for 72 hours and then stained by anti-FLAG (a), anti-Lamin A (b) antibodies as well as DAPI and phalloidin. DAPI was used for detecting the size and shape of the nucleus, and phalloidin for showing the size of the whole cell. Anti-FLAG antibody (a) detected the expression and localization of FLAG-PPP2CA, and anti-Lamin A antibody (b) showed the nuclear lamina. Scale bar in both (a) and (b) are 20 um.

! ! 87!

! ! ! ! ! ! ! ! ! ! !

! ! 88!

! ! ! ! ! ! ! ! ! b

! ! ! ! ! ! ! ! ! !

! ! 89! the intensity of the signal across biological replicates. In my analysis of some PPP2R1A and PPP2CA mutants, one set of samples had a lower abundance than the other set. This had the consequences of increasing the number of false-negatives in the analysis (meaning that besides the proteins which I have found modulated, there are likely many other proteins that are modulated in their interactions but have not scored positive in the statistical analysis). Although this problem can be solved by carefully repeating the experiments to avoid the problems of intensity difference between samples, more robust statistical tools are needed for SWATH analysis. Recently, two new analytical tools for processing DIA data, named DIA-Umpire[190] and MSPLIT-DIA[191], have been developed for sensitive peptide and protein identification and more consistent quantification across different samples. The increased sensitivity and reproducibility make them better tools for analyzing DIA data. In order to solve the intensity problem occurred in my SWATH analysis and to get more information from my samples, my DIA files should be reanalyzed using the newly developed DIA analytical methods. Hopefully, even more interesting protein-protein interaction changes will be identified and a deeper understanding of the consequences of these PP2A point mutations will be achieved. These methods should also overcome the issue I ran into with the PPP2CA dataset, namely T304A, T304D, Y307E, Y307F, L309Δ, L309A, T304A/Y307F, T304D/Y307E, R268E, R268E/T304D and R268E/T304A/Y307F.

Although AP-MS is a widely used method for detecting protein-protein interactions, it is not suitable for all proteins. As in this study, the AP-MS analysis of PPP2R2A, PyMT and some of the E4orf4 mutants fail to provide much interesting interactome information. These proteins were expressed at low levels in the Flp-In T-REx system, which may partially explain the few interactors detected in the MS analysis. But the expression level is not the only determining factor that influences the AP-MS results. PPP2R2A and PyMT, when expressed in HEK293 T-REx cells, both predominantly interact with the molecular chaperones. The expressed rat PPP2R2A and polyomavirus middle T antigen are not stable in the Flp-In T-REx system used in our

! ! 90! lab. For the BirA* tagged PPP2R2A mutants, although the expression level is similar to wild-type PPP2R2A, the majority of the detected interactors are chaperonin containing TCP1 complex subunits. In order to characterize the interactome of these proteins, other methods are likely to be Y2H, chemical cross-linking, proximity ligation assay, etc.

4.3 Future directions With the development of the new DIA data analyzing tools DIA-Umpire and MSPLIT-DIA, the first step of the future plan is to analyze the PPP2R1A and PPP2CA SWATH files again in order to see whether new protein-protein interaction changes can be identified. Hopefully, new interaction changes of interest will be revealed, including those of other PP2A regulatory B subunits, PP2A-interacting proteins, and PP2A inhibitors. If necessary, some of the interesting interaction changes will be validated by immunoprecipitation/Western just as what has been done for PPP2R1A and PPP2CA.

The characterization of protein-protein interaction changes caused by point mutations of PP2A will be expanded in the future. This study will not be confined in the scaffolding A subunit and catalytic C subunit. Mutations of various PP2A regulatory B subunits will also be included. Since the interaction between PP2A substrate and B subunit may be transient, it is feasible to apply BioID to the study of PP2A B subunits mutations. This activity will be expanded during the timeframe of this project to ~50 mutant phosphatase alleles.

In order to better understand the structural and conformational changes of PP2A holoenzyme caused by PP2A mutations and to relate the change to the alterations of protein-protein interactions, a structure-based interaction network will be built. In fact, ELASPIC (Ensemble Learning Approach for Stability Prediction of Interface and Core mutations), a tool developed by the Kim Lab has been launched online for the analysis of protein mutations. With the structural analysis, each mutation will be

! ! 91! scored by mapping it to the structure of the protein and by determining its interaction potential. As a result, those mutations that have a high potential in modulating protein-protein interactions may be discovered.

One long term goals of studying the tumor suppressor PP2A is trying to discover some new pharmacological compounds that may regulate the function of PP2A to serve as a therapy to cancer. As modulated protein-protein interactions are identified in the AP-SWATH analysis of PP2A subunits, the detected interactors will be screened against pharmacological compound databases to see whether they are the targets of any known drugs. If the interactor and its related drug are identified, the drug will be tested to see its effects on the protein-protein interaction. The successful testing of drug NVP-AUY922 (a potent HSP90 inhibitor currently undergoing a clinical trail) on influencing the interaction between CDK4 and CDC37/HSP90[143] is a good example of this kind of study. It will help accelerate the process of finding new drugs that modulate protein-protein interactions, which enables us to promote the study of therapeutic modulation of protein-protein interactions. Hopefully at the end, this study will expand the arsenal of anti-cancer agents.

Efforts will also be made to analyze the influences of PPP2CA mutation R268E on the phosphorylation state of BAF. As mentioned above in 3.4, PPP2CA mutants containing mutation R268E lose their interaction with ANKLE2. ANKLE2 coordinates the regulation of BAF dephosphorylation by interacting with and inhibiting VRK-1 and by supporting PP2A for dephosphorylating BAF. This study will be performed using two methods: Overexpress PPP2CA R268E mutants in HEK293T cells and perform RNAi analysis of wild-type PPP2CA and ANKLE2 in stably transfected HEK293 T-REx cells. The phosphorylation state of BAF will be checked by Western blot. If dephosphorylation of BAF is achieved by PP2A through its interaction with ANKLE2 as hypothesized, an increase amount of phosphorylated BAF will be detected in WB.

! ! 92!

APPENDIX

figure 1. Expression of FLAG tagged wild-type PPP2R1A and PPP2R1A mutants in HEK293 T-REx cells. HEK293 T-REx cell lines expressing FLAG tagged wild-type PPP2R1A, eight PPP2R1A mutants and negative control FLAG-alone were grown and harvested for WB. Mouse anti-FLAG primary antibody and anti-mouse HRP secondary antibody were used.

! ! 93!

FLAG-PPP2R1A WT Q372L C329F R183W P179R S256F R183Q R258H W257C ctrl

! ! 94!

figure 2. Expression of FLAG tagged wild-type PPP2CA and PPP2CA mutants in HEK293 T-REx cells. HEK293 T-REx cell lines expressing FLAG tagged wild-type PPP2CA, eleven PPP2R1A mutants and negative control FLAG-alone were grown and harvested for WB. Mouse anti-FLAG primary antibody and anti-mouse HRP secondary antibody were used.

! ! 95!

FLAG-PPP2CA WT T304D T304A/Y307F R268E R268E/T304D R268E/T304A/Y307F T304A Y307E Y307F L309A T304D/Y307E ctrl

! ! 96!

figure 3. Characterization of the interacting proteins of FLAG tagged wild-type PPP2CA and PPP2CA mutants. Bona fide interacting partners were identified by SAINT. Circle shading indicates the number of interactor spectra detected as per the color scale (only proteins with spectral count no less than 10 are showed). Circle size indicates the number of interactor spectra detected in one bait, relative to the greatest number of spectra detected in any of the baits. Border of the circle represents different FDR thresholds. Specific interactors are noted as PP2A A/B subunits and known PP2A-interacting proteins. (AP-MS data)

! ! 97! Y307F Y307F A/ A/ Y307E Y307E Y307F Y307F A/ D/ A/ D/ R268E/T304 R268E T304 Y307F T304A WT T304D L309A R268E/T304D T304 Y307E R268E/T304 R268E T304 Y307F T304A WT T304D L309A R268E/T304D T304 Y307E ● ● ● ● ● ● ● ● ● ● ● ● ● PPP2R1A PRKD2 ● ● ● ● ● ● ● ● ● ● ● ● ● PPP2R2A ● NOC4L ● ● ● ● ● ● ● ● ● ● ● ● ● IGBP1 NOP14 ● ● ● ● ● ● ● ● ● ● ● ● ● PPME1 WDR81 ● ● ● ● ● ● ● ● ● ● ANKLE2 ARHGAP21 ● ● ● ● ● ● ● ● ● ● ● PPP2R5D ● NCAPD3 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● CCDC6 ● OTUD4 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● FECH ● PPP2R2C ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● CCT2 ● XRN2 ● ● ● ● ● ● ● ● ● ● ● ● ● ● PPP2R1B ● SERTAD4 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● PPP2R2D ● IER5 ● ● ● ● ● ● ● ● ● ● ● PPP4R1 ● NDUFAF1 ● ● ● ● ● ● ● ● ● ● PPP2R5C KRT18 ● ● ● ● ● ● ● ● ● ● ● ● ● ● PPFIA1 ● FOXC1 ● ● ● AXIN1 GRB10 ● ● ● ● ● ● ● ● SOGA1 TSEN34 ● ● ● ● ● ● ● PPFIBP1 KIAA1967 ● ● ● ● ● ● ● NHSL1 KRT19 ● ● ● ● ● ● ● ● PPP2R5B SMU1 ● ● ● ● ● ● ● ● ● SGOL1 IK ● ● ● ● ● ● LIMD1 HDAC5 ● ● ● ● ● ● ● ● PPP2R3A LRCH2 ● ● ● ● ● ● ● ● ● ● ● FGFR1OP FBXL16 ● ● ● ● ● ● ● ● ● ● ● ● STK24 RAVER1 ● ● ● ● ● ● ● CEP350 SLAIN2 ● ● ● ● ● ● ● ● ● ● CARHSP1 CDCA4 ● ● ● ● ● ● ● ● MOB4 SIK2 ● ● ● ● ● ● ● ● ● ● ● ● ● PPP4C ECSIT ● ● ● ● ● ● ● ● ● TBCCD1 ● VBP1 ● ● ● ● ● ● ● ● ● PPP2R3B PFDN2 ● ● ● ● ● ● ● ● ● CTTNBP2NL ● PFDN1 ● ● ● ● ● ● ● ● ● ● ● FAM40A ● ● RAB11FIP5 ● ● ● ● ● ● ● ● ● ● ● ● ● STRN ● PLEKHA6 ● ● ● ● ● ● ● ● ● ● ● ● ● ● STRN4 ● FAM122B ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● STRN3 WDR61 ● ● ● ● ● ● ● PDCD2 TTC33 ● ● ● ● ● ● ● LCMT1 UNG ● ● ● ● ● ● ● ● ● ● PPP2R4 ● DOCK7 ● ● ● ● ● ● ● ● PLEKHA5 ● CRTC3 ● ● ● ● ● ● ● ● ● ● ● PPFIA3 TBC1D4 ● ● ● ● ● ● ● ● ● ● ● ● ● PPP2R5E ARPP19 ● ● ● ● ● ● ● ● ● ● ● ● ● ● PPP2R5A FAM122A ● ● ● ● ● ● ● ● ● ● MAST2 ENSA ● ● ● ● ● ● ● ● ● ● ● ● PPP1R13L CAMSAP3 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● PKP2 KRT8 ● ● ● ● ● ● ● ● ● ● ● MAST4 ARHGEF2 ● ● ● ● ● ● ● ● ● ● ● IGFBP5 TIPRL ●

Spectral Count PP2A A subunits PP2A B subunits 10 50 known PP2A-interacting proteins

● ● Relative abundance

! ! 98!

figure 4. Expression of FLAG tagged wild-type PPP2R2A and PPP2R2A mutants in HEK293 T-REx cells. HEK293 T-REx cell lines expressing FLAG tagged wild-type PPP2R2A, three PPP2R2A mutants (V154E, V154R and R257E) and negative control FLAG-alone were grown and harvested for WB. Mouse anti-FLAG primary antibody and anti-mouse HRP secondary antibody were used.

! ! 99!

FLAG-PPP2R2A l_BR1 l_BR2 T_BR1 T_BR2 r r t t c c W W V154E_BR1 V154E_BR2 V154R_BR1 V154R_BR2 R257E_BR1 R257E_BR2

ctrl: FLAG-alone BR1: replicate 1 BR2: replicate 2

Expression of the Balpha baits in the two replicates for anti-FLAG IP. Pre-IP samples were taken before adding beads. Western blot was then performed using mouse anti-FLAG primary antibody.

! ! 100!

figure 5. Expression of BirA*-FLAG tagged wild-type PPP2R2A and PPP2R2A mutants in HEK293 T-REx cells. HEK293 T-REx cell lines expressing BirA*-FLAG tagged wild-type PPP2R2A, seven PPP2R2A mutants and three negative controls, FLAG-alone, BirA*-FLAG-alone and BirA*-FLAG-GFP-alone were grown and harvested for WB. Mouse anti-FLAG primary antibody and anti-mouse HRP secondary antibody were used. Arrows are used to indicate detected proteins. Unspecific bands in lane 3 are also indicated.

! ! 101!

BirA*-FLAG-PPP2R2A FLAG-alone BirA*-FLAG BirA*-FLAG-GFP WT V154E V154R R257E E190K C239L E190K/V154E C239L/V154E

BirA*-FLAG-PPP2R2A

BirA*-FLAG-GFP

unspecific bands

BirA*-FLAG

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