The Role of Sin1 in Cell Survival

The role of Sin1 in cell survival

A thesis submitted the University of Manchester for the degree of Doctor of Philosophy In the Faculty of Life Sciences

2014

Blanca Paramo

Table of Contents

The role of Sin1 in cell survival ...... 1 Table of Contents ...... 2 List of Figures ...... 4 List of Tables ...... 5 Abstract ...... 6 Author’s Declaration ...... 7 Copyright statement ...... 7 Autobiographical statement ...... 8 Acknowledgements ...... 9 Abbreviations ...... 10 1. Introduction ...... 13 1.1 The mammalian target of rapamycin (mTOR) ...... 14 1.1.1 mTOR complexes ...... 14 1.1.2 Signalling via mTORC1 ...... 16 1.1.3 Signalling via mTORC2 ...... 19 1.2 The stress-activated protein kinase interacting protein Sin1 ...... 20 1.2.1 Cloning and description ...... 20 1.2.2 Characteristics ...... 21 1.2.3 Functions ...... 23 1.3 Programmed cell death ...... 27 1.3.1 Mechanisms of PCD ...... 27 1.3.2 Apoptosis ...... 27 1.3.3 Autophagic cell death ...... 29 1.3.4 Necroptosis ...... 31 Aims and objectives ...... 32 2. Materials and methods ...... 33 2.1 Materials ...... 33 2.2 Methods ...... 33 2.2.1 Cell culture ...... 33 2.2.2 Genotyping ...... 34 2.2.3 Sin1 deletion ...... 35 2.2.4 Treatments ...... 35 2.2.5 Preparation of cell lysates ...... 35 2.2.6 Bradford assay ...... 36 2.2.7 Akt kinase assay ...... 36 2.2.8 Immunoblotting ...... 37 2.2.9 Caspase 3 assay ...... 38 2.2.10 MTT assay ...... 38 2.2.11 LDH assay ...... 39 2.2.12 Cell counting and cell size measurement ...... 39 2.2.13 Cell proliferation assay ...... 39 2.2.14 β-galactosidase assay ...... 40 2.2.15 Immunofluorescence staining ...... 40 2.2.16 Quantitative Real time PCR ...... 41 2.2.17 Hoechst staining ...... 42 2.2.18 Cellular fractionation ...... 42 2.2.19 Microarrays ...... 42 2.2.20 Statistical analysis of microarray data ...... 43

2.2.21 Statistical analysis ...... 43 Results ...... 44 3. Sin1 in the survival of mitotic cells ...... 44 3.1 Methodology used to study the role of Sin1 in cell survival ...... 44 3.2 Sin1 can be conditionally inactivated in MEFs after 4OHT treatment ...... 45 3.3 The loss of Sin1 decreases Akt activity in response to mitogens in MEFs .. 47 3.4 mTOR kinase inhibition decreases pSer437 ...... 49 3.5 The loss of Sin1 decreases cell survival ...... 51 3.6 CreER activation affects MEFs proliferation ...... 56 3.7 Discussion ...... 58 4. Sin1 in neuronal survival ...... 61 4.1 Methodology to study the role of Sin1 in neuronal survival ...... 61 4.2 Conditional inactivation of Sin1 decreases Akt S473 phosphorylation in neurons ...... 62 4.3 Loss of Sin1 increases apoptotic neuronal death ...... 66 4.4 Autophagy is not increased in Sin1 ko neurons ...... 68 4.5 The loss of Sin1 does not increase necroptotic neuronal death ...... 70 4.5.1 The loss of Sin1 does not affect neuronal polarisation ...... 72 4.6 The loss of Sin1 does not affect Synaptophysin level ...... 74 4.7 Discussion ...... 76 5. Sin1 and gene expression in neurons ...... 80 5.1 Methodology used to study the role of Sin1 in gene expression ...... 80 5.2 Functional analysis of genes down-regulated in absence of Sin1 ...... 82 5.3 Array validation by RT-PCR ...... 87 5.3.1 Discussion ...... 90 Discussion ...... 93 6.1 Future directions ...... 96 References ...... 97 Appendix ...... 112 A List of genes ...... 112 B Primer efficiency ...... 117

Word count: 34,118

List of Figures

Figure 1.1 mTOR and the mTOR complexes...... 15 Figure 1.2 mTORC1 activation ...... 17 Figure 1.3 mTORC1 and mTORC2 function in cells...... 19 Figure 1.4 The stress-activated protein kinase-interacting protein Sin1 ...... 22 Figure 1.5 Role of Sin1 in Akt regulation...... 25 Figure 1.6 Morphological features of cell death programmes ...... 30 Figure 3.1 Strategy to generate a conditional Sin1 knockout mouse model ...... 45 Figure 3.2 Inactivation of Sin1 in MEFs after 4OHT treatment...... 46 Figure 3.3 The loss of Sin1 impairs Akt phosphorylation on Ser473 and decreases Akt activity after growth factor stimulation...... 49 Figure 3.4 mTOR kinase inhibition abolishes Akt Ser473 phosphorylation in control and Sin1-null MEFs...... 51 Figure 3.5 The loss of Sin1 impairs Akt phosphorylation on Ser473 in response to oxidative stress...... 52 Figure 3.6 The loss of Sin1 decreases cell survival in MEFs...... 53 Figure 3.7 The loss of Sin1 increases senescence...... 55 Figure 3.8 CreER activation affects the proliferation of MEFs...... 57 Figure 4.1 Strategy to generate conditional Sin1 knockout neurons ...... 62 Figure 4.2 Conditional inactivation of Sin1 decreases pS473 in neurons...... 63 Figure 4.3 The lack of Sin1 decreases neuronal survival and cell size ...... 65 Figure 4.4 The loss of Sin1 increases neuronal apoptosis ...... 67 Figure 4.5 Autophagy acts as a survival mechanism in neurons...... 69 Figure 4.6 The loss of Sin1 does not increase necroptotic neuronal death...... 71 Figure 4.7 The loss of Sin1 does not affect neuronal polarisation...... 73 Figure 4.8 The loss of Sin1 does not affect Synaptophysin expression ...... 75 Figure 5.1 pS473 Akt and Sin1 mRNA levels in cortical neurons at 12DIV ...... 81 Figure 5.2 Sin1 dependent gene expression in cortical neurons...... 82 Figure 5.3 Functional analysis enrichment of gene ontology terms...... 83 Figure 5.4 Protein classes affected by the loss of Sin1 in cortical neurons...... 85 Figure 5.5 Validation of microarray data by RT-PCR of selected genes...... 88 Figure 6.1 Sin1 maintains neuronal survival ...... 94

List of Tables

Table 1. Antibodies used for immunoblot and immunofluorescence or IP ...... 38 Table 2. RT-PCR primer sequences ...... 41 Table 3. Pathways affected by the loss of Sin1 in cortical neurons ...... 86 Table 4 Function of selected genes down-regulated in Sin1 ko neurons ...... 87 Table 5 Function of selected genes up-regulated in Sin1 ko neurons ...... 88 Table 6 Primer efficiency ...... 117

Abstract

The University of Manchester Blanca Paramo The role of Sin1 in cell survival A thesis for the degree of Doctor of Philosophy December 2014

Cancer and neurodegeneration are detrimental conditions associated with an inappropriate regulation of cell survival and cell death, causing compromised cells to evade death or excessive death of healthy neurons. The mammalian target of rapamycin complex 2 (mTORC2) has been implicated in the regulation of cell survival by phosphorylating the protein kinase Akt. This is dependent upon the scaffold protein Sin1, a core component of mTORC2. The requirement of Sin1 in cell survival, and in particular in neuronal survival, has not been established due to the early embryonic lethality of mice with a targeted deletion of the Sin1 gene. To circumvent this issue, a novel conditional mouse knockout model was established. The role of Sin1 in regulating cell survival was evaluated in fibroblasts and cortical neurons. The loss of Sin1 significantly affected the phosphorylation and activity of Akt in fibroblasts and caused a reduction in cell survival by potentially inducing premature senescence. In contrast, the loss of Sin1 caused an increase in caspase-independent cell death in cortical neurons. Gene-expression analysis of Sin1 knockout cortical neurons demonstrated an important down-regulation of transcription factors, cytoskeletal proteins and components of signalling pathways involved in neuronal survival, aiding to uncover the mechanism by which Sin1 promotes neuronal survival. Taken together, the results presented in this study show a key role of the scaffold protein Sin1 in regulating neuronal survival.

Author’s Declaration

No portion of the work referred to in this thesis has been submitted in support of an application for another degree or qualification at this or any other university or institute of learning.

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Autobiographical statement

In 2008 I completed a degree in Biology at the Faculty of Life Sciences, UNAM Mexico and a Masters in Biochemistry in 2010 in the Faculty of Chemistry in the same University. In 2011, I started a PhD in Molecular and Cellular Neuroscience supervised by Drs Cathy Tournier and Alan Whitmarsh at the Faculty of Life Sciences, University of Manchester. During the past years I conducted research in neurobiology that was published in peer review journals and presented in international conferences. During my PhD, I gained technical experience in cellular and molecular biology.

Acknowledgements

I would like to thank my supervisors Drs Cathy Tournier and Alan Whitmarsh for all their support, help and excellent guidance in the development of this project. I also want to thank my advisor Dr Paul Shore for all his excellent advice towards my progression as student. I am also thankful to all the members of the Tournier and Whitmarsh labs, for their help. Finally I also want to acknowledge my sponsor in Mexico, the National Council of Science and Technology (CONACyT) and SEP.

Abbreviations

3MA 3-methyl adenine 4OHT 4-hydroxytamoxifen Akt RAC-alpha serine/threonine-protein kinase or protein kinase B AIF Apoptosis inducing factor BDNF Brain-derived neurotrophic factor BSA Bovine serum albumin cDNA complementary DNA Cre Cre recombinase CREB Ca2+/cAMP responsive element binding protein CreER Cre recombinase fused to the estrogen receptor CRIM Conserved region in the middle DEPTOR DEP domain-containing mTOR-interacting protein DIV Days in vitro DISC Death-inducing signalling complex DMEM Dulbecco’s Modified Eagle’s Medium DMSO Dimethyl sulfoxide EGF Epidermal Growth Factor EGFR Epidermal Growth Factor Receptor cFos FBJ Murine Osteosarcoma Viral Oncogene Homolog Foxo Forkhead box protein F Floxed allele GDP Guanosine diphosphate GO Gene ontology GSK3β Glycogen synthase kinase-3 β GTP Guanosine triphosphate

H2O2 Hydrogen peroxide HBSS Hank’s balanced salt solution IF Immunofluorescence ko knockout LC3 light chain 3 LDH lactate dehydrogenase loxP locus of X-over of P1 MAP2 Microtubule-associated protein 2 MEFs mouse embryonic fibroblasts

Nec1 Necrostatin 1 NMDA N-methyl-D-aspartate mTOR mammalian target of rapamycin mTORC mammalian target of rapamycin complex mTORC1 mTOR complex 1 mTORC2 mTOR complex 2 MTT 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide PARP1 Poly (ADP-ribose) polymerase 1 PBS Phosphate buffered saline PCD Programmed cell death PCR polymerase chain reaction PDK1 3-phosphoinositide-dependent protein kinase 1 PH pleckstrin domain PI3K phosphatidylinositol-3-kinase QVD N-(2-Quinolyl)-L-valyl-L-aspartyl-(2,6-difluorophenoxy) methylketone Raptor regulating associated protein of mTOR RBD Ras-binding domain Rictor rapamycin-insensitive companion of mTOR RIP1 Receptor-interacting protein 1 RIP3 Receptor-interacting protein 3 pS473 phosphorylated Akt on serine 473 pT308 phosphorylated Akt on threonine 308 RT Reverse transcriptase RT-PCR Real time-quantitative PCR SEM standard error of the mean Ser473 Akt serine residue 473 SGK1 serum-glucocorticoid kinase 1 S6K1 S6 kinase 1 Sin1 Mitogen-activated protein kinase associated protein 1 (Mapkap1) Sin1 stress-activated protein kinase-interacting protein-1 Thr308 Akt threonine residue 308 TLB Triton lysis buffer TNFα Tumour necrosis factor α TSC1 tumor suppressor protein tuberous sclerosis 1 TSC2 tumor suppressor protein tuberous sclerosis 2

WB Western blot wt wild-type zVAD carbobenzoxy-valyl-alanyl-aspartyl-[O-methyl]- fluoromethylketone Note on nomenclature: Sin1 is used instead of Mapkap1 when referring to gene/allele to avoid confusion, while Sin1 is used when referring to protein. Therefore, the official mouse genomics informatics, MGI standardized genetic nomenclature for mice is not followed.

MEFs generated from the straight knockout mouse model are referred to as Sin1 knockout or Sin1-/- MEFs while those generated using the conditional model established here are referred to as Sin1-null or Sin1-depleted MEFs. In the case of neurons and since this is the first study in which Sin1 is conditionally disrupted in vitro in mammalian cortical neurons, they are referred to as Sin1 knockout neurons or Sin1 ko neurons.

1. Introduction

The survival of cells depends on their ability to appropriately sense, integrate and respond to cues in the environment. Cells have evolved a plethora of mechanisms that allow them to rapidly and precisely respond to changes in nutrients, growth factors, hormones and various stresses. Failure to integrate and respond appropriately to all these different signals leads to the survival of compromised or damaged cells by evading cell death, or, on the contrary, the demise of healthy functional cells, leading to the onset of neurodegenerative or metabolic diseases and cancer (Fulda et al., 2010; Portt et al., 2011; Vander Heiden et al., 2011).

A general mechanism to integrate different stimuli involves the initial detection of a signal, followed by its transduction to various compartments within the cell, culminating in a unified cellular response. Signals are typically detected by receptors, usually embedded in the plasma membrane, whose activation causes the recruitment of signalling proteins that relay the signal to modify downstream effectors involved in cellular functions such as gene expression, metabolism or cytoskeleton organisation, among others (Taniguchi et al., 2006). Due to the high diversity of signals, the stimulation of different pathways usually converges on core signalling molecules that integrate this information and execute the appropriate cellular response. One of the central signalling pathways controlling cellular functions, including cell growth and survival, is the mammalian target of rapamycin (mTOR) pathway (Huang and Fingar; Cornu et al., 2013). mTOR controls cell survival by interacting with numerous downstream targets involved in the regulation of programmed cell death (PCD), including apoptosis, autophagy and necroptosis (Maiese et al., 2013; Porta et al., 2014). This highlights the relevance of the mTOR signalling pathway as a new therapeutic target in diseases where aberrant cell death has been implicated such as neurodegeneration and acute neurological conditions such as stroke (Maiese, 2014).

The variety and abundance of stimuli and signalling molecules provokes a question that has been the subject of study in cellular signalling for many years; how do signalling pathways integrate to accomplish a coherent and specific response to the diverse stimuli cells are exposed to? One of the mechanisms is by

restricting the localisation of components of signalling cascades to prevent their interaction with other proteins in a stimulus and time-dependent manner. Scaffold proteins are essential for this process as they ensure the specific transmission of the signals from the membrane to various compartments within the cell by assembling the components of the signalling pathway together (Zeke et al., 2009; Alexa et al., 2010). Scaffold proteins also contribute to the regulation of feedback loops that fine-tune the activation and inhibition of signalling pathways and contribute to integrating signals from multiple pathways (Good et al., 2011). The stress-activated protein kinase interacting protein-1 (Sin1) scaffold protein is important for mTOR signalling since it has been shown to be a critical component of the mTOR complex 2 (mTORC2) (Frias et al., 2006; Jacinto et al., 2006; Yang et al., 2006). mTORC2 controls cell survival by phosphorylating and activating Akt, a protein kinase known to promote cell survival, in part, by suppressing programmed cell death. Understanding the interplay between mTOR and Akt in cell survival under physiological conditions has been essential to gain a better insight about the deregulation underlying pathological conditions (Bove et al., 2011; Maiese et al., 2013; Polivka Jr and Janku, 2014).

1.1 The mammalian target of rapamycin (mTOR) mTOR signalling is activated by changes in the cellular environment to promote cellular growth and proliferation (Laplante and Sabatini, 2009). Consistent with its crucial role in regulating these processes, aberrant mTOR signalling has been implicated in various diseases including cancer, type 2 diabetes and neurodegeneration (Zoncu et al., 2011a; Johnson et al., 2013). Its critical role in regulating cell functions is also exemplified by its requirement for embryonic development, as its absence results in the death of mouse embryos at early stages of development (Gangloff et al., 2004; Murakami et al., 2004).

1.1.1 mTOR complexes mTOR is a serine/threonine protein kinase that forms two distinct complexes in cells, mTORC1 and mTORC2. mTOR belongs to the phosphatidylinositol-3 kinase-related kinase (PIKK) family and was originally identified as the target of the macrolide immunosuppressant rapamycin (Heitman et al., 1991; Sabatini et al., 1994). Human mTOR is 2549 amino acids in length with a molecular weight of 296 kDa. It contains repeats of the HEAT (huntingtin, elongation factor 3, a subunit

of protein phosphatase 2A and TOR) domain in the N-terminal region, known to be involved in mediating mTOR interaction with specific components (Kim et al., 2002a). The HEAT domain is followed by a FAT (FRAP (mTOR), ATM and TRAPP) domain that folds and interacts with an analogous carboxy-terminal FAT domain (FATC) in a manner so that the catalytic kinase domain is exposed (Yang et al., 2013). The FAT domain is also known to interact with inhibitory components such as DEPTOR (Peterson et al., 2009). An FKBP12-rapamycin binding (FRB) domain, known to be implicated in recruiting substrates (such as S6K) to the active site and thus involved in mediating the rapamycin inhibitory effects is found next (McMahon et al., 2002). The catalytic kinase domain (KD) precedes the FRB domain, and finally, a FAT carboxy-terminal domain (FATC), which function, as mentioned earlier, has to do with the folding and exposing of the catalytic domain (Fig.1.1) (Bosotti et al., 2000; Yang et al., 2013).

Figure 1.1 mTOR and the mTOR complexes. A) Human mTOR is a 2549 amino acids length serine/threonine kinase, which contains 20 repeats of the HEAT domain followed by a FAT domain, and an FRB domain. The FRB domain is followed by a kinase domain (KD) and a FATC domain. Rapamycin interacts with FKBP12 and binds to the FBR domain to inhibit mTOR B) mTOR is found in two distinct complexes in cells, mTORC1 and mTORC2. mTORC1’s unique subunits are Raptor and PRAS40, while mTORC2’s unique components are Sin1, Rictor and PROTOR. mLST8, mTOR kinase and DEPTOR are found in both complexes.

Apart from the mTOR kinase, the lethal with SEC13 protein 8 (mLST8), also called GβL, and the DEP domain-containing mTOR-interacting protein (DEPTOR) are also shared by both mTORC1 and mTORC2 complexes (Kim et al., 2003; Guertin et al., 2006; Peterson et al., 2009).

The unique components of mTORC1 are the regulatory-associated protein of mTOR (Raptor) and the 40 kDa Pro-rich Akt substrate (PRAS40), while mTORC2 components are Sin1, the rapamycin-insensitive companion of mTOR, Rictor, and the protein observed with Rictor (PROTOR) (Figure 1.1B) (Zoncu et al., 2011a).

1.1.2 Signalling via mTORC1 mTORC1 mediates the response of cells to changes in energy status and nutrients and regulates processes essential for growth and proliferation, including protein translation, lipid synthesis, ribosome and mitochondrial biogenesis, and mitochondrial metabolism (Laplante and Sabatini, 2009; Zoncu et al., 2011a).

As mTORC1 integrates diverse inputs about the metabolic status of cells to drive anabolic processes required for cell and organisms to growth, its activation is a complex, highly controlled process that has not been fully elucidated. A model has been proposed where mTORC1 activation requires its re-localisation to the lysosome, where it interacts with GTP-bound active Rag GTPases RAGA/B⋅GTP- RAGC/D⋅GDP (Fig. 1.2). This, in turn, is absolutely dependent on the levels of amino acids, as well as growth factor signalling. Under starvation conditions, mTORC1 localises to the cytoplasm, and the RAG GTPases are in a GDP-bound inactive state: RAGA/B⋅GDP-RAGA/B⋅GTP. The guanine-exchange factor (GEF) for RAGA/B⋅GDP is a pentameric complex known as Ragulator, localised to the membrane of lysosomes and, whose interaction with a vacuolar ATPase (v- ATPase) under the presence of amino acids, causes a conformational change that activates its GEF activity towards RAGA/B⋅GDP, activating it (Fig. 1.2). Active GTP-bound RAGA/B⋅GTP recruits mTORC1 to the lysosome (Sancak et al., 2008; Sancak et al., 2010; Zoncu et al., 2011d; Bar-Peled et al., 2012).

Figure 1.2 mTORC1 activation mTORC1 activation requires both amino acids and growth factor signalling to mediate its re-localisation to the lysosome and interaction with active GTP-bound RAGA/B GTPases. Amino acids activate a vacuolar ATPase (v-ATPase), which in turn causes a conformational change that promotes the guanine exchange (GEF) activity of Ragulator towards RAGA/B⋅GDP generating an active RAGA/B⋅GTP- RAGC/D⋅GDP complex that recruits mTORC1 to the lysosome. Growth factor signalling promotes the activation of the small GTPase Ras homologue enriched in brain (RHEB) active-GTP bound and mTORC1 becomes activated.

Once recruited to the lysosome, mTORC1 is activated by the small GTPase Ras homologue enriched in brain (RHEB,) protein bound to GTP (Fig.1.2,(Avruch et al., 2006). RHEB is kept inactive by the hamartin-tuberin complex, TSC1-TSC2, which is a GTPase activating protein (GAP) that hydrolyses the GTP bound to RHEB (Inoki et al., 2003b). Phosphorylation of TSC2 mediated by Akt inhibits its GAP activity (Inoki et al., 2002), thus allowing the activation of RHEB and consequently of mTORC1 (Bhaskar and Hay, 2007). Furthermore, the AMP-activated protein kinase (AMPK), which is regulated by changes in the AMP/ATP ratio, regulates mTORC1 activation. When the levels of ATP decrease, AMPK phosphorylates TSC2, augmenting its activity and thus leading to RHEB inhibition and suppression of mTORC1 activation (Inoki et al., 2003a). In addition, AMPK phosphorylates Raptor and promotes its binding to the 14-3-3 proteins, thereby preventing Raptor from binding to mTOR and thus leading to mTORC1 inhibition (Gwinn et al., 2008). mTORC1 is inhibited by rapamycin which forms a complex with FKBP12 that binds the FRB domain (Fig. 1.1A), thus disrupting the mTOR and Raptor interaction (Hara et al., 2002; Kim et al., 2002b). However, the rapamycin effect on mTOR activity appears to be selective since it does not inhibit the phosphorylation of all mTORC1 targets (Feldman et al., 2009; Thoreen et al., 2009).

Once activated mTORC1 promotes protein translation by phosphorylating eIF4- binding protein 1 (4E-BP1) and S6 kinase 1 (S6K1) (Hara et al., 1997; Ma and Blenis, 2009). When hypophosphorylated, 4E-BP binds the eukaryotic translation initiator factor eIF4E and represses translation initiation. After being phosphorylated by mTORC1, 4E-BP1 affinity for eIF4 decreases and dissociation occurs, allowing the proper interaction between the components of the mammalian ribosomal translation initiation complexes with the 5´ end of the mRNA, thereby promoting translation (Hay and Sonenberg, 2004b). Phosphorylation and activation of S6K1 also regulates the assembly and activation of the translation initiation complex. S6K1 phosphorylates the eukaryotic translation initiator factor eIF4B which is required for the interaction between the ribosome and the mRNA, and increases the activity of the helicase eIF4A (Holz et al., 2005; Laplante and Sabatini, 2009) (Figure 1.3). The role of mTOR in promoting anabolic processes that reflect the energetic status of the cell required to growth implicate the inhibition of catabolic processes such as autophagy. This is accomplished, at least in part, by phosphorylating and inhibiting the uncoordinated-51 (UNC-51)-like kinase 1 (ULK1). When dephosphorylated, ULK1 becomes active and phosphorylates Beclin-1 at the nascent autophagosome (Russell et al., 2013).

Figure 1.3 mTORC1 and mTORC2 function in cells. mTORC1 activation depends on the integration of different signals such as growth factors (GF) energy status (e.g. glucose levels), stress, amino acids and nutrient availability while mTORC2 activity depends on growth factors and the stimulation of their receptors. mTORC1 controls cell growth and protein translation by phosphorylating 4E-BP1 and S6K1, and inhibits autophagy by phosphorylating ULK1. mTORC2 phosphorylates Akt, SGK1 and PKC. Akt and SGK1 promote cell survival while PKC is involved in cytoskeletal organisation.

1.1.3 Signalling via mTORC2

Signalling mediated by mTORC2 is less understood compared to mTORC1. This is because mTORC2 was described later than mTORC1, but also due to the lack of a specific mTORC2 inhibitor. mTORC2 was initially found to be insensitive to rapamycin (Jacinto et al., 2004; Sarbassov et al., 2004). However, further studies demonstrated that this is not entirely true. It was shown that prolonged incubation of certain cell types with rapamycin interferes with the ability of mTOR to interact with Rictor and Sin1, leading to mTORC2 inhibition (Frias et al., 2006; Sarbassov et al., 2006). How mTORC2 is activated is still not well understood. In particular, very little is known about upstream regulators of mTORC2. Interestingly, unlike mTORC1, mTORC2 activation is insensitive to nutrient availability but requires growth factor stimulation (Cybulski and Hall, 2009). There is evidence that

mTORC2 activation requires its interaction with ribosomes following phosphatidylinositol 3 kinase (PI3K) activation (Zinzalla et al., 2011) .

Knockdown of mTORC2 components by RNAi in cells causes a defect in actin fibre organisation; hence it has been proposed that mTORC2 controls actin cytoskeleton assembly (Jacinto et al., 2004; Sarbassov et al., 2004; Yang et al., 2006). However, mouse embryonic fibroblasts (MEFs) derived from Rictor or mLST8 knockout embryos do not show any defects in actin organisation (Guertin et al., 2006; Shiota et al., 2006). Rictor knockout MEFs display decreased proliferation (Shiota et al., 2006), while knockdown of Sin1 increases the sensitivity of cells to toxic stimulus (Yang et al., 2006). Consistently, Sin1 knockout MEFs are more prone to stress-induced apoptosis (Jacinto et al., 2006). Further evidence of a link between mTORC2 and cell survival came from the identification of mTORC2 as the kinase responsible for phosphorylating the hydrophobic motif found in some members of the AGC family of protein kinases including protein kinase C, Akt and serum-glucocorticoid kinase 1 (SGK1) (Sarbassov et al., 2004; Sarbassov et al., 2005; Garcia-Martinez and Alessi, 2008) (Figure 1.3).

1.2 The stress-activated protein kinase interacting protein Sin1

1.2.1 Cloning and description

The mTORC2 component Sin1 was first described as a Ras-interacting protein (Colicelli et al., 1991). Later studies showed that it also interacted with members of the mitogen-activated protein kinase (MAPK) family of proteins and with the interferon receptor in immune cells (Wang and Roberts, 2004; Cheng et al., 2005; Schroder et al., 2005; Wang and Roberts, 2005c; Makino et al., 2006). However, its more prominent role seems to be related to the mTORC2 signalling pathway (Oh and Jacinto, 2011).

Sin1 was first identified as the product of a human cDNA (JC130) that was able to suppress the heat shock sensitivity response caused by constitutively activated Ras in Saccharomyces cerevisiae (Colicelli et al., 1991). Later on, a two-hybrid screen using the constitutively activated mammalian Ras isoform identified a Ras- interacting protein in the slime mold Dictyostelium discoideum (Lee et al., 1997). This new protein, named RIP3, had sequence homology to Sin1 and was found to be important for Dictyostelium chemotaxis (Lee et al., 1999). Using the same

approach, Sin1 was identified as a new Sty1/Spc1 mitogen-activated protein kinase-interacting protein in the fission yeast Schizosaccharomyces pombe. Alignment of the JC130 human cDNA, the Sin1 sequence from yeast and a cDNA sequence from chicken showed that the new Sty1/Spc1-interacting protein was conserved in eukaryotes. In yeast, Sin1 undergoes phosphorylation in response to stress stimuli, independently of the Sty1/Spc1 complex (Wilkinson et al., 1999). Subsequently, a screening of cDNAs conducted to analyse the expression of genes involved in hindbrain development in chick embryos described a clone with a high degree of homology to the human JC130. This cDNA was expressed during hindbrain development and corresponded to the chicken homologue of Sin1 (Christiansen et al., 2001).

1.2.2 Characteristics

Human Sin1 is a 522 amino acid protein with a domain known as conserved region in the middle (CRIM). Sin1 also possesses a pleckstrin domain (PH), which mediates its interaction with membranes (Schroder et al., 2004; Wang and Roberts, 2005a; Schroder et al., 2007), and a Ras binding domain (RBD) (Schroder et al., 2007). In addition, there is a potential nuclear localisation signal and a PEST motif that is associated with rapid protein turnover (Schroder et al., 2004; Wang and Roberts, 2004, 2005a).

Human Sin1 is the product of a single gene that can be alternatively spliced giving rise to different isoforms that vary in size (Figure 1.4). Four isoforms have been found to be expressed at the protein level (Sin1, Sin1α, Sin1β and Sin1δ). Sin1α comprises the first 323 amino acids and lacks the carboxy-terminal sequence, Sin1β lacks a region between amino acids Q322 to S356 (Schroder et al., 2004; Cheng et al., 2005) and Sin1δ lacks the first 192 N-terminal amino acids (Frias et al., 2006). Four additional isoforms have been detected, but only at the mRNA level (Loewith et al., 2002; Schroder et al., 2004; Frias et al., 2006).

Figure 1.4 The stress-activated protein kinase-interacting protein Sin1 A) Schematic representation of Sin1 gene showing the 11 coding exons with the corresponding regions that codify for the different domains of the protein. Numbers below each exon indicate size (base pairs). B) Human Sin1 is a 522 amino acids length protein that contains a potential nuclear localisation signal (NLS), a conserved region in the middle domain (CRIM) that contains a potential PEST motif, a Ras binding domain (RBD), and pleckstrin domain (PH). Alternative splicing of the gene gives rise to different isoforms. Sin1 is the full-length isoform (522 aa), Sin1α lacks the C-terminal domain (exon 7A, stop codon), Sin1β lacks amino acids Q322 to S356 (exon 6 to 8, no exon 7) while Sin1δ lacks the N- terminal region (no exon 1). Sin1, Sin1α and Sin1β interact with mTOR to form three distinct complexes. Two of them, indicated with an asterisk, are insulin- sensitive (Frias et al., 2006; Schroder et al., 2007).

Sin1, Sin1α and Sin1 β interact with mTOR to form three distinct mTORC2 complexes (Frias et al., 2006). Interestingly, these different complexes phosphorylate Akt on Ser473 in an insulin-dependent manner when Sin1 or Sin1β form part of the complex. Sin1δ lacks the N-terminal region of 192 amino acids and does not interact with mTOR, suggesting that this region is necessary for Sin1 recruitment to mTORC2 (Frias et al., 2006). These studies suggest that the selective interaction of mTORC2 with distinct Sin1 isoforms is physiologically relevant.

1.2.3 Functions

1.2.3.1 Akt regulation

The identification of Sin1 and mTORC2 as upstream activators of Akt was a major breakthrough in cell signalling considering that Akt, identified more than 25 years ago, was known to be a major regulator of cell proliferation and survival (Jacinto et al., 2004; Sarbassov et al., 2004; Woodgett, 2005; Polak and Hall, 2006; Toker, 2008).

Akt is a serine/threonine kinase that possesses hydrophobic and turn motifs (HM and TM, respectively) in the carboxy-terminal region of the protein, as well as a domain known as the activation loop, close to the catalytic domain (Hanada et al., 2004). After growth factor stimulation, the activation of PI3K generates phosphatidylinositol 3’ phosphate, which recruits Akt to the plasma membrane via its PH domain where it is phosphorylated by 3-phosphoinositide-dependent protein kinase 1 (PDK1) at threonine 308 (Thr308) in the activation loop and by mTORC2 at serine 473 (Ser473) in the hydrophobic domain (Alessi and Cohen, 1998). mTORC2 was found to be the long-sought kinase for this hydrophobic domain since phosphorylation of Ser473 was decreased or lost in cells where Rictor or Sin1 were down-regulated (Sarbassov et al., 2005; Yang et al., 2006) and in cells derived from Sin1, Rictor and mLST8 knockout mice (Guertin et al., 2006; Jacinto et al., 2006; Shiota et al., 2006). Additionally, knockdown of Rictor caused a decrease on Thr308 phosphorylation (Sarbassov et al., 2005) supporting a model in which the phosphorylation of both residues is coordinated, that is, phosphorylation at Ser473 facilitates the phosphorylation of Thr308 by PDK1 (Scheid et al., 2002; Yang et al., 2002). However, analysis of embryos and MEFs derived from Sin1, mLST8 and Rictor knockout mice revealed that Thr308 phosphorylation was only slightly affected by the loss of Ser473 phosphorylation (Guertin et al., 2006; Jacinto et al., 2006; Shiota et al., 2006; Yang et al., 2006). A possible explanation for this apparent discrepancy may be related to partial gene dysfunction, compensatory mechanisms and differences in cell types. For example, decreased phosphorylation of Akt on Thr308 was observed in human transformed cell lines after Rictor knockdown, while mouse embryos and MEFs were employed to examine the effect of Sin1, mLST8 and Rictor gene deletion.

The phosphorylation of Akt on both residues was originally proposed to be required for full catalytic activity (Alessi and Cohen, 1998). However, the phosphorylation of only a specific subset of Akt substrates was found to be affected by the loss of Ser473 phosphorylation. This included Foxo1/3, but not GSK3β or TSC2 (Guertin et al., 2006; Jacinto et al., 2006; Shiota et al., 2006). These findings suggest that Akt phosphorylation on both, Thr308 and Ser473, influences its specificity rather than being required for full activation (Oh and Jacinto, 2011), although it is not yet possible to completely rule out that an alternative kinase compensate for the loss of Akt activity. In addition, it has been proposed that mTORC2 phosphorylates Akt on a turn motif (TM), independently of growth factor stimulation. This phosphorylation is thought to occur co- translationally and is important to stabilise Akt by preventing their degradation (Facchinetti et al., 2008; Ikenoue et al., 2008).

Akt has been placed upstream of mTORC1 through its ability to phosphorylate and inactivate TSC2 and downstream of mTORC2, since it is directly phosphorylated by this complex. Further characterisation of the interplay between Akt and mTOR signalling has shown that Akt regulation is a cell-context and temporal-dependent event, with Sin1 playing a key role (Xie and Proud, 2013).

Initially, growth factor stimulation activates mTORC1 via Akt activation through TSC2 inhibition. After prolonged growth factor stimulation, the activation of mTORC1 causes S6K1 to phosphorylate Sin1 at Thr86 and Thr398, leading to its dissociation from Rictor and mTOR, thereby inactivating mTORC2 and decreasing Akt Ser473 phosphorylation (Liu et al., 2014a). MEFs expressing Sin1 mutants unable to be phosphorylated by S6K1 showed persistent mTORC2 activation and Ser473 phosphorylation, and were slightly more resistant to apoptoic stimuli (Liu et al., 2013a; Liu et al., 2014a). This mechanism of controlling mTORC2 activation via mTORC1/S6K1 targeting of Sin1 could be important in keeping Akt phosphorylation on Ser473 transient, since hyperactivation of this kinase is known to be related to hyperproliferation and cancer (Testa and Tsichlis, 2005; Davies, 2011). This suggests that S6K1 acts to suppress mTORC2 (Fig. 1.5A). However, Akt regulation by S6K1-mediated Sin1 phosphorylation seems to be cell-specific, taking place in epithelium-derived transformed HeLa cells and fibroblasts.

Figure 1.5 Role of Sin1 in Akt regulation. A) Growth factor stimulation causes Akt phosphorylation on both residues. Akt activates mTORC1 via Rheb by phosphorylating and inhibiting TSC2. mTORC1 activates S6K1 leading to the phosphorylation of Sin1 on T86 and T398, causing its dissociation from mTOR and Rictor and mTORC2 disintegration. B) Insulin activates PI3K and PDK1 causing the rapid phosphorylation of Akt on Thr308. Akt in turn phosphorylates Sin1 on Thr86, activating mTORC2. Akt phosphorylated on Thr308 can phosphorylate GSK3β and TSC2. Active mTORC2 phosphorylates Akt on Ser473. Akt phosphorylated on both residues is required to phosphorylate Foxo1/3.

Indeed, Akt can also phosphorylate Sin1 on Thr86 after insulin stimulation in adipocytes, but prior to Akt being phosphorylated on Ser473 (Humphrey et al., 2013). Similar to Sin1, GSK3β and TSC2 have been found to be phosphorylated by Akt prior to mTORC2 activation (Humphrey et al., 2013). Insulin, a key anabolic hormone required for metabolic homeostasis, exerts a wide range of biological functions through the canonical PI3K/mTOR pathway via activation of receptors belonging to the tyrosine kinase family (Taniguchi et al., 2006). Unlike S6K1, Akt- mediated Sin1 phosphorylation on Thr86 in response to insulin leads to mTORC2 activation and the subsequent phosphorylation of Akt on Ser473 (Fig. 1.5B). These studies suggest that Sin1 phosphorylation on Thr86 is stimuli- and cell-type specific, i.e. Akt in response to insulin in adipose tissue (metabolic function) versus S6K1 in epithelial cells (cancer transformation). More importantly, the kinase

responsible for the post-translational modification of Sin1 defines whether Sin1 phosphorylation on Thr86 has a positive or negative effect on mTORC2 activity with evidence that S6K1 inhibits, while Akt promotes mTORC2 signalling. The functional significance of these regulatory feedback loops on the kinetics of Akt activity remains to be established.

1.2.3.2 Cell survival

Sin1 ko MEFs derived from the straight mouse model are more sensitive to stress- induced cell death, directly implicating Sin1 in cell survival (Jacinto et al., 2006). This is consistent with the survival role of the mTORC2/Akt pathway (Datta et al., 1999; Bhaskar and Hay, 2007). mTOR regulates cell survival by controlling key components involved in the activation of different cell death programmes including apoptosis, autophagy and necroptosis (Maiese, 2014). Akt promotes, cell survival via transcription dependent- and independent- mechanisms. Akt phosphorylates members of the Foxo family of transcription factors (Foxo1 and 3a) (Brunet et al., 1999; Brunet et al., 2001). This causes their association with 14-3-3 proteins and retention in the cytoplasm, thus inhibiting the expression of genes involved in apoptosis, such as Bim, PUMA and Fas ligand (Zhang et al., 2011). Alternatively, Akt can directly inhibit the pro-apoptotic function of proteins such as Bad and caspase-9, upon direct phosphorylation (Datta et al., 1997; Vivanco and Sawyers, 2002).

Studies conducted so far have greatly advanced our understanding of the complex biochemical and molecular regulation of mTORC2 signalling. In contrast, the mechanism underlying the role of mTORC2 in cell survival remains largely uncharacterised, beyond the knowledge that mTORC2 activates Akt and the fact that Akt promotes survival by blocking the expression of pro-death molecules (Datta et al., 1999; Song et al., 2005; Manning and Cantley, 2007).

Since the maintenance of cell survival is directly related to the inhibition or activation of cell death programmes depending on the conditions (Portt et al., 2011; Kole et al., 2013), and due to the described requirement of mTOR and Akt in regulating those programmes (Datta et al., 1999; Maiese et al., 2013), the next section comprises an overview of the most-well studied and characterised mechanisms of programmed cell death.

1.3 Programmed cell death

Damaged cells must be eliminated in order to prevent the spread of genetic defects and to ensure that harmful or dysfunctional cells do not compromise the normal functioning of tissues. This occurs through organised programmed cell death (PCD) mechanisms that often require de novo protein synthesis, as opposed to necrosis, an accidental unorganised cellular explosion (Van Cruchten and Van den Broeck, 2002; Taylor et al., 2008; Hernandez et al., 2012; Nikoletopoulou et al., 2013).

1.3.1 Mechanisms of PCD

PCD includes apoptosis, the best well characterised and studied form of PCD, autophagy, a "self-eating" type of cell destruction, and regulated necrosis or necroptosis (Galluzzi et al., 2012). This classification is based on well-established morphological features and biochemical traits. Nonetheless, a high degree of crosstalk between these distinct cell death mechanisms has been observed. For instance, cell death can be initiated through one pathway but shifts to another if the first one is defective or inhibited (Kroemer and Levine, 2008). Accordingly, it has been proposed that the morphological features characteristic of apoptosis and necrosis result from the activation of various biochemical components shared by these death programmes to adapt to environmental changes as cell death progresses (Zeiss, 2003).

1.3.2 Apoptosis

Apoptosis has been described as a cell suicide programme since it is an active organised process. Apoptosis has been classified into two different forms: extrinsic apoptosis, mediated by the activation of death receptors localised at the plasma membrane and intrinsic apoptosis when the mitochondria release the death signal in response to stress or injury (Hotchkiss et al., 2009; Wyllie, 2010). The term was first introduced by Kerr et al. in 1972 to describe a process in which structural changes took place in two phases. The first phase corresponds to nuclear and cytoplasmic condensation associated with membrane blebbing and the formation of apoptotic bodies. During the second phase, apoptotic bodies are engulfed and digested in phagosomes (Kerr et al., 1972). Biochemically, these features result from the activation of cysteine proteases (known as caspases) and DNA-

degrading endonucleases, and the translocation and exposure of phosphatidylserine to the cell surface which acts as a phagocytosis marker (Hengartner, 2000). Intrinsic and extrinsic apoptosis occur in, at least, three steps: initiation, integration and execution. Initiation depends on the nature of the stimuli. Integration corresponds to the commitment to die and is mainly irreversible. In this step, caspases and mitochondrial proteins combine the information to ensuring that the final step, execution, takes place. Execution constitutes the step where the well-characterised morphological features are affected and hence can be observed, such as nuclear condensation and cell shrinkage. Since these morphological features are displayed by most cells dying by any form of apoptosis, the execution step constitutes a homogeneous stage (Kroemer et al., 1997).

The intrinsic or mitochondrial apoptotic pathway is activated by UV radiation, anticancer drugs and growth factor withdrawal, among other stress stimuli. It involves changes in the balance and interaction between anti-apoptotic (Bcl2, Bcl- xL) and pro-apoptotic (Bax, Bak, Bim, Bid, PUMA and Bad) members of the Bcl-2 family that ultimately affect mitochondrial permeabilisation (Youle and Strasser, 2008; Shamas-Din et al., 2011). For example, a change in the mitochondrial membrane potential associated with the insertion of Bax and Bak heterodimers into the mitochondrial membrane cause the release of cytochrome c (Kroemer, 2007). In the cytoplasm, cytochrome c interacts with Apaf-1 (adapter protein apoptotic protease- activating factor-1) and dATP to form a complex known as, the apoptosome, which recruits and activates the initiator pro-caspase 9 (Bratton et al., 2001). Under normal conditions, caspases are expressed in cells as inactive precursors or pro-enzymes (termed pro-caspases). They become activated in response to stress upon proteolytic cleavage at aspartic acid residues by other caspases. Once activated, cleaved caspases cleave other pro-caspases downstream, amplifying the signal (Li et al., 1997; Riedl and Salvesen, 2007). For example, caspase 9 cleaves and activates pro-caspase 3. Activation of caspase 3, the prototypical executioner caspase, establishes the commitment of cells to die. Caspase 3 has a number of substrates, some of them directly involved in producing morphological apoptotic changes (Fischer et al., 2003). Intrinsic apoptosis can also occur in a caspase-independent manner where proteins located in the intermembrane mitochondrial space, such as apoptosis inducing factor (AIF), Omi and endonuclease G, are released and translocate to the nucleus where they degrade DNA (Bröker et al., 2005).

The extrinsic pathway involves the activation of cell surface receptors after the binding of specific ligands, such as tumour necrosis factor (TNF) or Fas ligand (Ashkenazi and Dixit, 1998). Ligand binding recruits adaptor proteins to form the so-called death-inducing signalling complex (DISC), required for caspase 8 and caspase 3 activation (Guicciardi and Gores, 2009; Kantari and Walczak, 2011).

Both, the intrinsic (caspase-dependent or independent) and the extrinsic pathways culminate with the activation of executioner proteins. Caspases, or alternative proteases in the case of caspase-independent apoptosis, cleave the inhibitor of caspase-activated DNase (ICAD) leading to DNA laddering and chromatin changes (Nagata, 2000; Leist and Jäättelä, 2001). Caspases also cleave lamins leading to nuclear shrinkage and cytoskeletal proteins causing changes in morphology, as well as cytosolic remodelling (Rao et al., 1996; Buendia et al., 1999). Finally, another key feature of apoptosis, blebbing, occurs as a consequence of the activation of the small GTPase Rho and the downstream kinase PAK2 (Leverrier and Ridley, 2001).

1.3.3 Autophagic cell death

Autophagy plays a major role in cell survival under conditions of starvation by degrading toxic protein aggregates and damaged organelles. Consequently, the role of autophagy in executing cell death has been a matter of controversy (Das et al., 2012; Denton et al., 2012). The idea of an autophagic cell death programme comes from morphological studies where features characteristic of autophagy were observed in dying cells (Schweichel and Merker, 1973). However, the evidence supporting an autophagic cell death mechanism remains mostly correlative and the causative role of autophagy in cell demise has not been conclusively established (Levine and Yuan, 2005; Munoz-Pinedo and Martin, 2014). Furthermore, it is unclear whether autophagy kills cells by selective elimination of essential survival factors or by massive degradation of the entire cellular content (Denton et al., 2012). Overall, the signalling mechanisms involved in controlling autophagic cell death are only partially characterised (Liu et al., 2013c).

Like apoptosis, autophagy can be divided into distinct phases: initiation, vesicular nucleation, elongation and fusion (Yang and Klionsky, 2010). The initiation phase

is negatively regulated by mTORC1 under normal conditions (Dunlop and Tee, 2014). During this phase, double-membrane vesicles called autophagosomes are formed to surround and engulf portions of the cytoplasm/organelles to be degraded. During vesicle nucleation, a class III PI3K is activated after its interaction with a protein complex to which Beclin 1 is recruited. The following phase, elongation, involves the complete formation of the autophagosome. This process encompasses the lipid conjugation of phosphatidylethanolamine to LC3, transforming soluble LC3-I to membrane-bound LC3-II. The ubiquitin-binding protein p62 (also known as sequestome SQSTM1) binds to protein aggregates and is recruited by its interaction with LC3-II to the autophagosome, thus its degradation depends on autophagy activation (Bjorkoy et al., 2005). Finally, mature autophagosomes fuse with lysosomes to form autolysosomes, where degradation of the content takes place (Maiuri et al., 2007; Boya et al., 2013). Therefore, inhibition of class III PI3K using 3MA to block autophagosome formation, monitoring LC3-I conversion to LC3-II or p62 degradation by immunoblot, constitute some extensively used approaches to detect and monitor autophagy (Klionsky et al., 2012).

Figure 1.6 Morphological features of cell death programmes A) Apoptotic cells display cytoplasm shrinkage, nuclear condensation, membrane blebbing and formation of apoptotic bodies. B) Autophagic cell death involves the formation of autophagosomes (containing proteins and organelles) and autolysosomes, endocytosis, LC3-I lipidation and p62 degradation. C) In necroptotic cell death, cytoplasmic volume increases due to swelling, organelles are also swollen and damaged, while plasma membrane rupture and vacuolisation are observed (Puyal et al., 2013; Tan et al., 2014).

1.3.4 Necroptosis

Programmed necrosis or necroptosis was initially described as a type of cell death observed in caspase-deficient cells after death-receptor domain-induced apoptosis (Laster et al., 1988; Matsumura et al., 2000; Galluzzi et al., 2011). Since then, necroptosis has been reported in certain tissues during development (Wu et al., 2012) and as an important mechanism of cell loss during ischemic conditions (Degterev et al., 2005; Christofferson and Yuan, 2010). In addition, necroptotic cell death caused by TNFα and caspase inhibition in HT22 murine hippocampal cells has been shown to be blocked by inhibitors of mTOR/Akt signalling (Liu et al., 2014c).

Morphologically, necroptotic cells display an increase in cell volume, swollen organelles, translucent cytoplasm, plasma membrane rupture and, in contrast to apoptosis, no major nuclear modifications (Vandenabeele et al., 2010). The molecular mechanism behind necroptosis was described after the discovery of inhibitors of the receptor-interacting protein 1 (RIP1) kinase, known as necrostatins. These inhibitors effectively suppress the caspase-independent TNFα-induced cell death (Degterev et al., 2005; Degterev et al., 2008). Necroptosis initiation in the TNFα-activated pathway, the most widely characterised so far, occurs after receptor trimerisation, internalisation, and formation of the DISC complex where RIP1 and its homologue RIP3 bind and activate caspase 8 (Micheau and Tschopp, 2003). However, under conditions of caspase inhibition, RIP1 and RIP3 interdependent phosphorylation initiates necroptosis by forming a complex called the necrosome (Declercq et al., 2009). This leads to the execution phase where the increase in calcium concentration and calpain activation leads to the loss of mitochondrial membrane potential and an increase in ROS production (Vanden Berghe et al., 2014), causing damage to membranes and contributing to the release of lysosomal hydrolases, culminating in cell lysis (Golstein and Kroemer, 2007). Mitochondrial damage caused by the loss of membrane potential halts ATP production and also results in AIF release and translocation to the nucleus causing DNA cleavage. This contributes to the activation of the poly (ADP-ribose) polymerase 1 (PARP1), in an attempt to repair DNA. However, PARP1 overactivation consumes NAD+, further depleting ATP and compromising the ability of cells to survive or activate apoptosis (Leist et al., 1997; Golstein and Kroemer, 2007; Vandenabeele et al., 2010).

Aims and objectives

Since its discovery, the mTORC2 signalling pathway has been characterised in detail due to its role in phosphorylating Akt, one of the key regulators of cell survival. Sin1 is an essential component of mTORC2 and is required for Akt phosphorylation. However, the requirement of Sin1 in regulating cell survival and function, in particular in neurons, has not been conclusively established, in part due to the early embryonic lethality caused by Sin1 disruption in mice. To circumvent this problem, a conditional knockout mouse model was generated using the CreER /loxP system. Using this model the overall aim of this project was to uncover the role of Sin1 in cell survival.

The specific objectives are:

• To generate and validate conditions to specifically supress Sin1 expression in a time and cell-specific manner using two cellular models: primary mouse embryonic fibroblasts and mouse embryonic cortical neurons.

• To use this model to investigate the role of Sin1 in regulating the survival of primary MEFs.

• To use this model to investigate the role of Sin1 in cortical neurons by:

o Elucidating the role of Sin1 in regulating the survival of neurons.

o Analysing the mechanism underlying the requirement of Sin1 in neuronal survival.

o Evaluating the requirement of Sin1 in neuronal development through the analysis of changes in neuronal polarisation and axon growth.

o Analysing the programme of gene expression regulated by Sin1.

2. Materials and methods

2.1 Materials

The Sin1 loxP/loxP mouse (Sin1F/F) was generated by Eun Jun Lee in our group by homologous recombination methods (Lee, 2010). The CreER mouse (Hayashi and McMahon, 2002) was obtained from Jackson Laboratories and a double Sin1F/F;CreER transgenic strain was obtained and maintained in the male line. Direct PCR Lysis Reagent was from Viagentech. Culture media Dulbecco’s Modified Eagle’s Medium (DMEM), Neurobasal medium, B27 Supplement and B27 Minus AOX were from Gibco. All the other culture reagents as well as 4- hydroxytamoxifen (4OHT), (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), 3-methyl adenine (3MA), necrostatin-1, N-(2-Quinolyl)-L-valyl-L- aspartyl-(2,6-difluorophenoxy) methylketone (Q-VD-OPH), crystal violet, α-tubulin FITC, β-actin and MAP2 antibodies were from Sigma. Taq DNA polymerase, and TaqPCR core kit were purchased from Qiagen. The KAPA mouse genotyping kit was from KAPA Biosystems. All primers used for genotyping and qRT-PCR were from Eurogentec. carbobenzoxy-valyl-alanyl-aspartyl-[O-methyl]- fluoromethylketone (zVAD-FMKZ) was from R&D systems. Caspase substrate was purchased from EnzoLife Sciences. The Power SYBR Green RNA-to-CT 1- Step Kit was obtained from Applied Biosystems. TRIzol and DNA-free kit were from Ambion.

2.2 Methods

2.2.1 Cell culture

All animals employed in this study were hosted in a pathogen-free facility at the University of Manchester. All animal procedures were carried out under license according with the UK Home Office Animals (Scientific Procedures) Act (1986) and institutional guidelines. Time-mated pregnant females were killed by neck dislocation in accordance with Schedule 1.

2.2.1.1 Mouse embryonic cortical neurons

Mouse embryonic cortical neurons were generated from 16-18 day-old Sin1F/F, Sin1F/F;CreER and Sin1+/+;CreER embryos. After extraction from placenta, embryos were decapitated and the brain separated from the rest of the head. Cortices were dissected out, meninges removed and tissue dissociated mechanically in Neurobasal medium containing 2% (v/v) B27, 0.5 mM glutamine and 0.5% penicillin/streptomycin. Neurons were plated on poly-D-lysine pre-coated 6, 12 or 24-well plates (0.5x105 cells/cm2 or 0.25x105 cells/cm2 for immunocytochemistry), and were maintained in a humidified atmosphere containing 95% air, 5% CO2. Embryos were genotyped due to heterozygosity in CreER expression. After 7 days in vitro (DIV), neurons were fed by replacing half the media with fresh Neurobasal media.

2.2.1.2 Mouse embryonic fibroblast

MEFs were generated from 13.5 day-old Sin1F/F, Sin1F/F;CreER, Sin1+/+;CreER or Sin1+/F;CreER embryos. After separation of each embryo from the placenta, the head and internal organs were removed, tissue was rinsed twice with HBSS, and incubated with 1% trypsin overnight at 4°C. The next day, tissue was incubated with 1% fresh trypsin for 15 min at 37°C, after which it was homogenised by pipetting to allow disaggregation. Dissociated cells were plated in T75 cm2 flasks in DMEM supplemented with 10% fetal bovine serum (FBS), 1% penicillin/streptomycin and 2 mM glutamine until the culture reached confluence. After cultures reached confluence, MEFs were rinsed twice with HBSS and incubated with 1% trypsin for 5 min at 37°C. Cells were resuspended in DMEM 10% FBS to inactive trypsin, spun, resuspended again in freezing media, and kept in liquid nitrogen. All experiments were performed using MEFs at passage 2-4.

2.2.2 Genotyping

DNA isolation was performed using the Direct PCR Lysis Reagent or the KAPA mouse genotyping kit. Mouse embryo tails or adult ear clippings were incubated in 100 µl of lysis reagent and proteinase K (20 µg/ml) at 55°C overnight. Proteinase K was inactivated by incubating the samples at 85°C for 1 h. When the KAPA mouse genotyping kit was used, samples were incubated at 75°C for 10 min and then at 95°C for 5 min. Samples were spun at 16000g for 2 min and 1-2 µl of the

supernatant were used to perform the PCR reaction. Sin1 PCR was performed with the Taq DNA polymerase and Taq PCR core kit using the following primers: forward 5’-CTAGTAGGCCCATGAG3-’, reverse 5’-GGGGGTTATGCGCAGC-3’, the product was then run in a 2.5% agarose gel and visualised by UV light. The CreER PCR was performed with both the Taq DNA polymerase and Taq PCR core kit and with the KAPA Fast Genotyping mix using the following primers: forward 5’-CGGTCGATGCAACGAGTGATGAGG-3’, reverse 5’- CCAGAGACGGAAATCCATCGCTCG-3’, the product was run in a 2% agarose gel and visualised by UV light.

2.2.3 Sin1 deletion

To supress Sin1 expression, CreER MEFs and cortical neurons were mock- treated (vehicle only) or treated with different concentrations of 4OHT. For most of the experiments, MEFs were treated one day after plating for 24 h with 500 nM 4OHT and used 72 h after the initial treatment, while neurons were treated on the same day they were plated with 100 nM 4OHT.

2.2.4 Treatments

To study the role of Sin1 in cell growth and proliferation after Sin1 deletion, MEFs were serum-deprived for 12 h. Cells were rinsed three times with HBSS and then incubated in DMEM containing 1% penicillin/streptomycin and 2 mM glutamine. 12 h after, cells were re-stimulated for 5, 10 or 15 min by adding 10% serum.

To induce neuronal death, neurons were treated with 100 µM glutamate for 30 min, after which, the media was removed and the original media previously removed was added back. Cell death was analysed 24 h after. Inhibitors zVAD, QVD (20 µM) and Necrostatin (5 µM) were added on day 12, or on day 7 and then again on day 11, while 3MA was added only on day 12. Cell death was evaluated after 14 DIV.

2.2.5 Preparation of cell lysates

Growth media was aspirated and cells were rinsed to remove cell debris 3x with Krebs-Ringer HEPES buffered-saline medium containing: 125 mM NaCl, 5 mM

KCl, 5 mM MgSO4, 1.25 mM CaCl2, 50 mM HEPES at pH 7.4, and lysed for 5

minutes in different amounts of Triton lysis buffer (TLB) containing: 20 mM Tris pH 7.4, 137 mM NaCl, 2 mM EDTA pH 7.4, 1% Triton X-100, 25 mM β- glycerophosphate, 1 mM Na3Va4, 10% glycerol, 1 mM phenylmethylsulpholnyl fluoride (PMSF), 10 µg/ml aprotinin and 10 µg/ml leupeptin. Cells were scraped and transferred to 1.5 ml eppendorf tubes to be spun at 16000g for 20 min. The supernatant was collected in a new eppendorf tube and used immediately or kept at -80°C. For caspase assays, cells were rinsed two times in PBS and caspase lysis buffer containing 20 mM HEPES, 100 mM NaCl, 10 mM dithiothreitol (DTT), 0.1% CHAPS and 10% (w/v) sucrose was used to collect the cells. Cells in caspase lysis buffer were incubated on ice for 30 min, spun at 16000g for 10 min and the supernatant was collected to perform the assay.

2.2.6 Bradford assay

Protein concentration in cell lysates was determined using the Bradford reagent. Samples were diluted 1:2 times in water and 200 µl of Bradford reagent was added to each diluted sample. Reactions were allowed to proceed for 5 min and the optical density at 595 nm was measured in a spectrophotometer. Protein concentration was calculated using bovine serum albumin (BSA) as standard.

2.2.7 Akt kinase assay

Akt from cell lysates in TLB was immunoprecipitated with 0.3 µg/µl of Akt antibody and 25 µl of protein A-sepharose beads for 3 h at 4°C. The immunoprecipitates were washed once with TLB and twice with kinase buffer containing: 25 mM

HEPES pH 7.4, 25 mM β-glycerophosphate, 25 mM MgCl2, 2 mM DTT and 0.1%

Na3VO4. Immunoprecipitates were incubated with kinase buffer plus 50 µM ATP, 1 µ Ci [32ϒP]-ATP and 1 µg of substrate peptide (RPRAATF from GSK3β residues 4- 10, (Alessi et al., 1996a). The kinase reaction was carried out at 30°C for 30 minutes, the samples were spun 0.5 min at 4000rpm and the supernatant was transferred to a new eppendorf tube, the reaction was stopped using 10% trichloroacetic acid and spotted onto 3 cm2 P81 filter papers. The radioactivity in the filter papers was measured by a liquid scintillation counter after washing the papers three times with 0.75% phosphoric acid and acetone and allowing them to dry.

2.2.8 Immunoblotting

Proteins in TLB cell lysates were resolved by SDS polyacrylamide gel electrophoresis (SDS-PAGE). Equal amounts of protein were incubated in Laemmli buffer and boiled for 5 min to denature proteins. Samples were briefly spun and loaded onto different percentage polyacrylamide gels depending on the size of the protein to be resolved. 6, 10 and 12% polyacrylamide resolving gels were prepared by mixing Tris-HCl pH 8.8, APS, TEMED, and Protogel. Samples were electrophoresed at 150V for 1.5 h in buffer containing 25 mM Tris HCl, 192 mM glycine and 0.01 (w/v) SDS. After resolving by electrophoresis, proteins in gels were electrotransferred to polyvinylidene difluoride (PVDF) membranes by semidry transfer in buffer containing 25 mM Tris-HCl, 192 mM glycine and 20% methanol (v/v) at 12V for 2 h. Membranes were incubated 1 h at room temperature in blocking solution (5% skimmed milk diluted in Tris-buffered saline-Tween (TBST) containing 50 mM Tris-HCl, 150 mM NaCl, and 0.1% Tween-20 (v/v)), followed by overnight incubation at 4°C with primary antibodies diluted 1:1000 in blocking solution. Membranes were then washed two times for 10 min in TBST and incubated with the secondary antibody diluted 1:10000 in blocking solution for 1 h at room temperature. Afterwards membranes were washed 4x for 10 min in TBST and developed using enhanced chemiluminescent reagent (ECL) according to manufacturers’ instructions (Amersham). Antibodies used are shown in Table 1:

Table 1. Antibodies used for immunoblot and immunofluorescence or IP Antibody Manufacturer Dilution Used for Catalog N. Species Actin Sigma 1:5000 WB A2228 Ms Akt Cell signalling 1:1000 WB 9272 Rb Akt Millipore 0.3 µg/µl IP 07-416 Rb p16 Santa Cruz 1:1000 WB sc-1207 Rb p21 Santa Cruz 1:1000 WB sc-397 Rb p53 Novocastra 1:1000 WB CM5 Rb pAkt S473 Cell signalling 1:1000 WB 9271 Rb pAkt T308 Cell signalling 1:1000 WB 9275 Rb Sin1 Covlab 1:1000 WB Clone 113 Rb Sin1 Millipore 1:1000 WB 07-2276 Rb Erk1 Santa Cruz 1:1000 WB 292838 Rb Erk2 Santa Cruz 1:1000 WB 292838 Rb pErk1/2 Cell Signaling 1:1000 WB 9101 Rb p62 MBL 1:1000 WB PM045 Rb pGSK3β S9 Cell Signaling 1:1000 WB 9336 Rb pFOXO S253 Millipore 1:500 WB 06-953 Rb LC3 MBL 1:1000 WB PM036 Rb Tau-1 Millipore 1:1000 IF MAB3420 Ms MAP2 Sigma 1:1000 IF M9942 Ms αTubulin FITC Sigma 1:1000 IF F2168 Ms Synaptophysin Millipore 1:1000 IF/WB MAB5258 Ms AIF Santa Cruz 1:1000 WB sc-13116 Ms VDAC Cell Signaling 1:1000 WB 4866 Rb Lamin B Santa Cruz 1:1000 WB sc-6216 Goat Caspase 3 Cell signalling 1:1000 WB 9662 Rb Bim Calbiochem 1:1000 WB 202000 Rb IF:immunofluorescence;; IP:immunoprecipitation; Rb:rabbit, Ms:mouse; WB:Western blot

2.2.9 Caspase 3 assay

Equal amounts of protein obtained from cells lysed in caspase buffer were incubated with 200 µM DEVD-AMC caspase 3 fluorogenic substrate for 1 h at 37°C. Active caspase 3 cleaves the AMC from the substrate yielding fluorescence, which was measured using λ 380/460 nm excitation/emission in a spectrophotometer.

2.2.10 MTT assay

Cell survival was evaluated by MTT assay. After treatments, cells were incubated with MTT 0.5 µg/µl for 3 h (MEFs) or 30 min (neurons) at 37°C. Afterwards, the medium was aspirated and DMSO was used to dissolve the crystals. Each

condition was transferred to a 96-well plate and absorbance was read at 570 nm in triplicate.

2.2.11 LDH assay

LDH release to the extracellular media occurs after cell lysis and it is used to assess cell death. LDH activity was evaluated in Neurobasal media obtained from neurons maintained in culture for 14 days. Briefly, 50 µl of media in triplicate per condition were transferred to a 96-well white plate and equilibrated for 30 min at RT. 50 µl of reconstituted LDH substrate mix prepared according to the manufacturer's instructions were added to each well and incubated in the dark for 10 min at RT. The reaction was stopped by adding 25 µl of Stop Solution and the fluorescence was read using excitation/emmission wavelengths at 560/590 nm. Cell-free Neurobasal media was used to account for background reading and the media collected from wild type neurons incubated with 0.05% Triton 100-X for 5 min was used as positive controls and considered as 100% cell death. Results are expressed as mean ±SEM relative to this positive control.

2.2.12 Cell counting and cell size measurement

Neurons were plated on 12-well plates and after 14 DIV, bright field micrographs were taken using an inverted microscope and a 3CCD camera. Images were processed to obtain the cell number and measure cell size using Image J. A total of at least 150 cells per condition were counted/measured. Results obtained from 4 independent experiments are expressed as the average percentage ±SEM relative to control.

2.2.13 Cell proliferation assay

Crystal violet can be used as a proliferation assay to determine the relative number of cells in culture. The dye stains the cell membrane and upon solubilisation, the optical density of the dye can be measured in a spectrophotometer giving a quantitative measure of the relative number of cells. MEFs were plated at 50% confluence in 75 cm2 flasks and treated with vehicle or 4OHT to induce gene deletion. 4OHT was removed 24 h after by replacing the growing media. 72 h after initial 4OHT treatment, MEFs were incubated in 0.1% trypsin solution in HBSS for 5 min at 37°C. Trypsinisation was stopped by adding

growth medium and 20x104 cells were plated on 12-well plates. Cells were collected every other day for 10 days, washed with PBS and fixed in 4% paraformaldehyde. The fixed cells were stained with 0.1% crystal violet for 30 min at RT. Then, plates were washed three times with distilled water and allowed to dry. The dye was extracted using 10% acetic acid. Each condition was measured in duplicate in a 96-well plate. Absorbance was measured at 595 nm in a spectrometer.

2.2.14 β-galactosidase assay

MEFs were plated using the same procedure as that for the crystal violet staining and collected every other day. β-galactosidase staining was performed using a kit according to the manufacturer’s instructions (Cell signalling). Briefly, cells were rinsed twice with PBS and fixed using a fixative solution. X-gal, staining solution, solution A and B were mixed and the pH was adjusted to 6. Cells were incubated in this solution overnight and then rinsed and overlaid with 70% glycerol. Photomicrographs were taken using a Zeiss AxionVision inverted microscope with an Axiocam colour CCD camera.

2.2.15 Immunofluorescence staining

Cortical neurons grown on poly-D-lysine pre-coated coverslips were fixed with 4% sucrose-PFA solution for 30 min at 25°C, rinsed using 10 mM glycine in PBS solution permeabilised for 30 min in a solution containing 0.2% (v/v) Triton X-100 and 10 mM glycine in PBS. Cells were then washed 3x with a solution containing 0.1% Triton X-100 in PBS and blocked using a 5% BSA for 1 h. Primary antibodies were incubated overnight at 4°C in blocking buffer. The next day, samples were washed 3x with PBS containing 0.1% (v/v) Triton X-100 and incubated with Alexa Fluor-conjugated anti-mouse or anti-rabbit secondary antibodies diluted in blocking buffer (1:1000) for 1h at room temperature. To account for background signal primary antibodies were omitted. Unbound secondary antibody was washed 3x with PBS containing 0.1% (v/v) Triton X-100, and once with PBS only, coverslips were then mounted on microscope slides using the hard set DAPI Vectashield mounting medium. Slides were visualised using an Olympus microscope with appropriate filters and objectives, pictures were taken using a Coolsnap HQ camera. Depending on the experiment 10X or 20X objective magnification with a numerical aperture of 0.5 or 0.75 were used as setting. Filters used were as

follows (Ex/Em, nm): DAPI 365/397, β-III-Tubulin-FITC 450-490/515-565, Alexa- Fluor-594 594/-12/615.

Axon length was measured using the NeuroJ plugin from Image J (∼250 axons measured per condition from independent experiments). Neurons displaying a 3x longer Tau-positive neurite were considered to be polarized, a total of around ∼1400 neurons per condition from independent experiments were counted. Antibodies used are shown in Table 1.1.

2.2.16 Quantitative Real time PCR

RNA was isolated using Trizol according to the manufacturer’s instructions, and purified with the DNA-free kit. Samples were processed using the Power SYBR

Green RNA-to-CT 1-Step Kit. Reactions were prepared by adding 20 ng of RNA per sample in triplicate, forward (F) and reverse (R) primers, Reverse transcriptase (RT) enzyme, and the Power SYBR Green RT-PCR Mix. Thermal cycling conditions were as follows: 48°C for 30 min, 95°C for 10 min, 95°C for 15 sec, 60 °C for 1 min (40 cycles), 95°C for 15 sec, 60°C for 15 sec and 95°C for 15 sec (melt curve). Data were analysed with a CFX-96 Real-Time PCR Detection Systems (BioRad) and Microsoft Office Excel using the 2-∆∆CT method (Livak and Schmittgen, 2001). GAPDH was used as an internal control for normalisation. Primer sequences are shown in Table 2:

Table 2. RT-PCR primer sequences Gene Forward Reverse Atp1a2 AGGCGGTGTGGTCTTGGGAT CCACCCCCATTTTCCGCAGT Bdnf TGTGACAGTATTAGCGAGTGG TACCGGGACTTTCTCTAGGAC Bim GCCCCTACCTCCCTACAGAC AGGACTTGGGGTTTGTGTTG cFos AAAGTAGACCAGCTATCTCCT AAGTTGATCTGTCTCCGCT Egfr GCCATCTGGGCCAAAGATACC GTCTTCGCATGAATAGGCCAAT Fgfr3 CCGGCTGACACTTGGTAAG CTTGTCGATGCCAATAGCTTCT Gapdh GCGACTTCAACAGCAACTC CATTGTCATACCAGGAAATGAGC Gpm6b TGGGCTTACTTAAAGGATGCAAG TTGAGTTGTTCTTTTGAGCGAGA Lamp2 ATGTGCCTCTCTCCGGTTAAA GCAAGTACCCTTTGAATCTGTCA Ndrg2 GAGTTAGCTGCCCGCATCC GTGACCGAGCCATAAGGTGTC Neurod1 AGGAATTCGCCCACGCAGAA TGGTCATGTTTCCACTTCCTGTTGT Npas3 CACTGGCCATTGAAGTATTTGAAG CCACTTGTGAGAGGCCTAGGTAGA Npas4 CTGGATTTCTCCTTGTATTCACAG CAACCAGGTCCACCATAGAG Ntrk2 GACAATGCACGCAAGGACTT AGTAGTCGGTGCTGTACACA Pdgfra TACCAGACCCAGACATGGCC TGGTGCGGCAAGGTATGAT Rgs2 TGATTGCCCAAAATATCCAA GGGCTCCGTGGTGATCTG Sin1 TGCTCAAGGCAGTGAAAAGA AGCGATGTTAGGCTCACTCTG

Primer efficiency was tested by using serial dilutions of template and the results are shown in Table 6 (Appendix B). Efficiency was calculated according to the equation: � = −� + ��^(−�/��)

2.2.17 Hoechst staining

Neurons were stained with Hoechst 33342 (5 µg/ml) for 20 min at 37 °C and nuclei were visualised using an AxioVision inverted microscope. Images were taken using a colour CCD camera. Nuclei were considered apoptotic when they were fragmented or condensed. A total of at least 200 cells per condition from independent experiments were counted.

2.2.18 Cellular fractionation

Media was removed and neurons were washed with PBS, scraped and collected in 1 ml of isolation buffer containing 250 mM sucrose, 10 mM Tris-HCl and 0.1 mM EGTA. Homogenisation was carried out using a tissue homogenizer for 1 min, Samples were then spun for 10 min at 500g to pellet nuclei while the supernatant was spun again for 20 min at 8000g to pellet mitochondria. Pellets were resuspended in TLB.

2.2.19 Microarrays

For microarray analysis, neurons were treated with or without 4OHT after plating (0 DIV) and after 12 DIV RNA was collected and extracted using Trizol according to the manufacturer’s instructions. RNA was purified with the DNA-free kit. RNA purity was verified by reading absorbance reading at 260/280 nm with values of ∼2.0. The microarray experiment was performed by preparing and labelling double-stranded cDNA using the One-Cycle targeted labelling protocol from Affymetrix and the GeneChip® 3' IVT PLUS Reagent. Double stranded cDNA was biotinylated, cleaned up, fragmented and hybridised onto the Affymetrix GeneChip Exon 3’IVT mouse Array for 16 h at 45 °C. Following hybridisation, arrays were washed and stained with streptavidin-phycoerythrin followed by amplification of fluorescence by adding biotinylated antistreptavidin antibody. Fluorescent signal was detected by scanning the arrays. Each condition (wt and Sin1 ko neurons) was analysed in biological duplicates, so a total of 4 samples were analysed.

2.2.20 Statistical analysis of microarray data

Technical quality control of the samples was carried out with dChip (V2005). Background correction, expression analysis and data normalisation was done with Partek Gs 6.6 using the RMA algorithm. Principal component analysis (PCA) was performed using Partek to analyse variability among samples and to establish relationships. Differential expression tests were conducted with Limma in Bioconductor to compare differences in gene expression in wt vs Sin1 ko neurons. Genes with a log2 change of ±0.585 and a p value <0.05 were selected and used for further bioinformatics analysis using PANTHER software (Mi et al., 2013).

2.2.21 Statistical analysis

Data were analysed by one-way ANOVA with post hoc Dunnett's when comparing vs control or two-way ANOVA with post hoc Tukey's test for multiple comparison, and t-test using GraphPad Prism. Significant differences were considered when p≤0.05 and are indicated by an asterisk.

Results

3. Sin1 in the survival of mitotic cells

The biological function of Sin1 has been related to cell survival due to its role in regulating Akt as part of mTORC2 (Jacinto et al., 2006). However, this has not been rigorously demonstrated. For instance, primary MEFs derived from the Sin1 knockout mouse model do not display a defect in cell survival under normal conditions, but are more susceptible to cell death in response to hydrogen peroxide (H2O2) and etoposide (Jacinto et al., 2006). Furthermore, immortalised MEFs lacking Rictor, another mTORC2 component, exhibit a slower growth rate that correlates with a defect in cell proliferation (Shiota et al., 2006). Furthermore, MEFs generated from knockout mouse models may not represent the best system to study gene function because of the development of compensatory survival mechanisms during embryonic development. In addition, the rewiring of signalling pathways may occur during in vitro immortalisation of MEFs, as a consequence of clonal selection to provide proliferative and survival advantages. To circumvent this problem, a conditional Sin1 knockout model was created in the laboratory to examine, in vitro, the effect of the loss of Sin1 expression in a temporal-dependent manner. Additionally, in vivo models can be devised to mimic pathological conditions associated with sudden abnormal regulation of mTOR signalling.

3.1 Methodology used to study the role of Sin1 in cell survival

Murine Sin1 is located on chromosome 2 and comprises 11 exons. The conserved region in the middle (CRIM) domain, essential for proper Sin1 function is encoded by exons 3-5, while the Ras-binding domain (RBD) and the pleckstrin homologue (PH) domain are encoded by exons 5-7 and 8-11, respectively (Figure 3.1A, (Schroder et al., 2007). The conditional Sin1 knockout mouse model was created by flanking exon 3 with loxP sites, referred to as the floxed allele (F) (Lee, 2010). Homozygous Sin1F mice expressing Cre fused to a mutated form of the ligand- binding domain of the estrogen receptor (CreER) under the control of a ubiquitous (CMV) promoter, were subsequently generated. This system permits the specific ablation of floxed genes in vitro following the incubation of CreER expressing cells with 4OHT to trigger the nuclear translocation of Cre where it specifically recombines the loxP sites (Hayashi and McMahon, 2002). CreER-mediated recombination of the Sin1F gene generated a knockout allele (Fig. 3.1B).

Figure 3.1 Strategy to generate a conditional Sin1 knockout mouse model A) Schematic representation of Sin1 (protein) depicting its domains and Sin1 (gene) locus formed by 11 exons. Dotted lines show the exons that codify for the conserved region in the middle domain (CRIM, exons 3-5), a Ras binding domain (RBD, exons 5-7), and the pleckstrin domain (PH, exons 8-11). B) To generate a conditional allele, a region flanking exon 3 (gray box) was modified by introducing loxP sites to disrupt the CRIM domain, suggested to be essential for Sin1 function. CreER-mediated recombination of the loxP sites generates a dysfunctional knockout allele where a shift in the reading frame generates a STOP codon.

3.2 Sin1 can be conditionally inactivated in MEFs after 4OHT treatment

CreER;Sin1F/F fibroblasts were obtained from mouse embryos. The cells were incubated with increasing concentrations of 4OHT for 24 h. The levels of Sin1 were analysed by immunoblot 48 h later to determine the optimal dose for deleting Sin1 in vitro using an antibody that recognizes the middle and C-terminal regions. The result shows a partial reduction in Sin1 protein expression at 100 nM and a maximal effect at 500 nM relative to cells treated with vehicle only (Fig. 3.2A). Based on these results, a further experiment was carried out to determine the kinetics of the effect of 4OHT treatment at 500 nM. CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT and the levels of Sin1 were detected after 24, 48 and 72 h by immunoblot. 4OHT treatment caused a time-dependent reduction in Sin1 with a maximal effect at 48 h (Fig. 3.2B).

Figure 3.2 Inactivation of Sin1 in MEFs after 4OHT treatment. A) Increasing 4OHT concentrations effect on Sin1 levels. CreER;Sin1F/F MEFs were treated with 0, 100, 300 and 500 nM 4OHT for 24 h and Sin1 protein levels were analysed by immunoblot 48 h after treatment. Actin was used as a loading control. B) 4OHT time-course. CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT for the indicated times and cell lysates were analysed for Sin1 and Akt expression and Akt phosphorylation at serine 473 (pS473) and threonine 308 (pT308) by immunoblot. Actin was used as a loading control. Representative experiment from two repeats.

Previous research has demonstrated the essential requirement of Sin1 for Akt phosphorylation on Ser473 (Jacinto et al., 2006; Yang et al., 2006). Therefore, the effect of the loss of Sin1 expression on Akt phosphorylation at both, Ser473 and Thr308 was evaluated. The phosphorylation of Akt at Ser473 was not affected up until 24 h 4OHT treatment and it was even slightly increased at 48 h (Fig. 3.2B). This increase could be due to the fact that the media was changed after 24 h in order to remove 4OHT. Similarly, Akt phosphorylation on Thr308 was increased following the addition of fresh media (Fig. 3.2B). However, Sin1 was undetectable at 48 h, suggesting that the replenishment of growth factors and other essential nutrients can increase Akt activity independently of Sin1 (Fig. 3.2B). In contrast and consistent with the requirement of Sin1 in mTORC2/Akt signalling (Jacinto et al., 2006; Yang et al., 2006), the level of Ser473, but not of Thr308, phosphorylation was significantly reduced at 72 h (Fig. 3.2B). This observation confirmed that the Cre/loxP approach reproduced the abnormal phenotype associated with mTORC2 deficiency, in which phosphorylation of Akt on Ser473 did not affect Thr308 phosphorylation (Guertin et al., 2006; Jacinto et al., 2006;

Shiota et al., 2006). Additionally, a correlation between the absence of Sin1 and reduced Akt protein expression was observed (Fig. 3.2B), consistent with decreased protein stability caused by the loss of Ser473 phosphorylation (Facchinetti et al., 2008).

Based on this initial characterisation, CreER;Sin1F/F MEFs were incubated with 500 nM 4OHT and use after 72 h to produce Sin1-deleted MEFs. Control samples correspond to mock-treated Sin1F/F MEFs, unless indicated.

3.3 The loss of Sin1 decreases Akt activity in response to mitogens in MEFs

Sin1 was required for mediating Akt phosphorylation on Ser473 under basal conditions (Fig. 3.2B). Next, the requirement of Sin1 for Akt phosphorylation and activation in response to growth factors was evaluated. In this experiment, cells were serum-deprived for 12 h prior to being re-stimulated with serum for 5, 10 and 15 min. The specific loss of Sin1 expression in Sin1F/F MEFs incubated with 4OHT and carrying the CreER transgene was evaluated and confirmed by immunoblot (Fig. 3.3A), while increased Sin1 expression was observed in control cells after 10 min serum stimulation (Fig. 3.3A).

The level of phosphorylated Akt and Akt activity were analysed by immunoblot and protein kinase assay, respectively. Starvation caused a reduction in the level of Ser473 phosphorylation, which was more pronounced in the absence of Sin1 (Fig. 3.3A). In control MEFs expressing Sin1, serum stimulation caused a transient increase in Akt phosphorylation on both Ser473 and Thr308 residues, reaching a peak after 5 min (Fig. 3.3A). Increased phosphorylation on Ser473 was significantly impaired in Sin1-null MEFs over the time course of serum stimulation, (Fig. 3.3A). In contrast, no marked difference was observed in the level of Thr308 phosphorylation between mock-treated and 4OHT-treated MEFs, under basal or stimulated conditions (Fig. 3.3A). Furthermore, control and Sin1-deleted MEFs displayed a similar level of Akt (Fig. 3.3A). This was in contrast to decreased Akt stability observed in Sin1-deleted MEFs cultured in growth media (Fig. 3.2B). This apparent discrepancy may reflect the different level of CreER-mediated gene recombination, since the reduction in Sin1 levels was much higher in the first experiment. To demonstrate the specific effect of Sin1 on Akt signalling, the levels of phosphorylated and total Erk1/2 in control and Sin1-null MEFs were evaluated.

Phosphorylated Erk1/2 was not detected in starved cells, but it increased after serum stimulation. This was not affected by the loss of Sin1 (Fig. 3.3A).

Most studies use the level of Akt phosphorylation on either Ser473 and/or Thr308 as an indication of protein kinase activity. Nonetheless, to confirm the role of Sin1 in controlling Akt function, the effect of Sin1 deletion on Akt activity by protein kinase assay was measured. The peptide used to assay Akt activity corresponds the amino acids 4-10 of GSK3β, where its phosphorylation, corresponding to Akt activation has been reported to be dramatically reduced in cells expressing S473A non-phosphorylatable mutants (Alessi et al., 1996b). This assay allows then to examine the ability of Akt to phosphorylate a consensus sequence of a substrate in vitro, which in turn correlates with its activity under specific circumstances. Consistent with immunoblot analyses, Akt activation was transient with a maximal significant activity at 10 min after of serum stimulation (Fig. 3.3B, *p<0.05). This was significantly reduced in the absence of Sin1 (Fig. 3.3B, p<0.05). The residual level of Akt activity detected in Sin1-null MEFs is consistent with normal level of Akt phosphorylation at Thr308 (Fig. 3.3A and B).

Figure 3.3 The loss of Sin1 impairs Akt phosphorylation on Ser473 and decreases Akt activity after growth factor stimulation. A) CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT and after 72 h, serum-deprived for 12 h and re-stimulated with serum for the indicated times. The levels of pS473, pT308, total Akt and Sin1 were analysed by immunoblot. pErk1/2 and total Erk1/2 were used as control. Representative experiment from 4 independent repeats. B) Akt activity measured under the conditions shown in A). Data are mean ±SEM from 4 independent experiments and were analysed by two- way ANOVA with post hoc Tukey's test. *p<0.05 -4OHT 10 min serum vs control and 10 min serum -4OHT vs +4OHT.

3.4 mTOR kinase inhibition decreases pSer437

To determine whether the residual level of Akt phosphorylation on Ser473 detected in Sin1-null MEFs after mitogenic stimulation was dependent on mTORC2 activity, control and Sin1-null MEFs were treated with DMSO (vehicle) or Torin1, an mTOR kinase inhibitor (Thoreen et al., 2009). As previously observed (Fig. 3.3A), serum stimulation increased Sin1 expression and Akt phosphorylation on Ser473 in control MEFs (Fig. 3.4). Ser473 phosphorylation was significantly decreased in cells lacking Sin1 and completely inhibited in both control and Sin1- deleted MEFs incubated with Torin1 (Fig. 3.4). These results indicated that Akt phosphorylation on Ser473 in Sin1-deleted MEFs was dependent on residual mTORC2 activity. In contrast, Thr308 phosphorylation, which was not affected by

the loss of Sin1, was not inhibited by Torin1 (Fig. 3.4). In fact, Thr308 phosphorylation was slightly but notably higher in control and Sin1-null MEFs incubated with Torin1 compared to DMSO-treated MEFs (Fig. 3.4).

The phosphorylation of S6K1 on threonine 389 (Thr389) has been reported to be decreased in Rictor-null primary human fibroblasts under growing condition (Rosner et al., 2009). Therefore, the phosphorylation of S6K1 on Thr389 in control and Sin1-null MEFs under starved and serum stimulated conditions was monitored to examine the role of Sin1 in mTORC1 signalling. Sin1-null MEFs displayed a defect on Thr389 phosphorylation under starved condition, while no marked difference was observed between control and Sin1-deleted MEFs in response to serum stimulation (Fig. 3.4). Considering that Akt can regulate mTORC1 activity (Gingras et al., 1998; Hay and Sonenberg, 2004a), it is proposed that this specific defect may be a consequence of decreased Akt phosphorylation on Ser473 in serum-starved Sin1-deleted MEFs (Fig. 3.3A). This observation contrasts with a previous study in which the absence of Thr389 phosphorylation in starved wild type and Sin1 knockout immortalised MEFs was shown (Liu et al., 2013a).

Figure 3.4 mTOR kinase inhibition abolishes Akt Ser473 phosphorylation in control and Sin1-null MEFs. CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT and after 72 h, serum- deprived for 12 h and re-stimulated with serum for 5 min, in the absence (DMSO) or the presence of the mTOR kinase inhibitor Torin1 (200 nM). The levels of pS473, pT308, total Akt were analysed by immunoblot. Phosphorylation of S6K1 on threonine 389 (T389) and total S6K1 were also evaluated to monitor mTORC1 activity. Sin1 levels were examine to confirm the efficiency of the targeted conditional deletion. Representative experiment from 3 independent repeats.

Altogether, these data clearly show that Sin1 can be conditionally inactivated in MEFs using the CreER/loxP system. The lack of Sin1 expression impairs Akt phosphorylation and activity after growth factor stimulation.

3.5 The loss of Sin1 decreases cell survival

Akt has a key role in regulating cell survival (Song et al., 2005; Manning and Cantley, 2007). To test the functional effect caused by the loss of Akt Ser473 phosphorylation after Sin1 deletion, MEFs response to oxidative stress was evaluated. CreER;Sin1F/F MEFs were untreated or treated with 500 nM 4OHT and after 3 days incubated with H2O2 and Akt phosphorylation and cell survival were evaluated. H2O2 treatment increased Akt Ser473 phosphorylation in control MEFs with a maximum effect after 10 min (Fig. 3.5A). This was impaired in Sin1-deleted cells. The effect was specific for Ser473 phosphorylation since no difference was observed on Thr308 phosphorylation between the two different genotypes. Total Akt levels also remained unchanged (Fig. 3.5A).

Figure 3.5 The loss of Sin1 impairs Akt phosphorylation on Ser473 in response to oxidative stress. A) CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT and after 72 h treated with 500 µM H2O2 for the indicated times. The levels of pS473, pT308, total Akt and Sin1 were analysed by immunoblot. Representative experiment from 3 independent repeats. B) Cell survival was evaluated 3, 6, 9 and 12 h after H2O2 treatment by MTT. Data are mean ±SEM from 3 independent experiments. *p<0.05.

To establish a link between impaired Akt phosphorylation and H2O2 toxicity, cell survival was measured 3, 6, 9 and 12 h after H2O2 treatment. The results show that H2O2 decreased MTT reduction in a time dependent manner, with a 50% reduction observed at 12 h. MEFs lacking Sin1 were 25% less viable than control cells under basal and treated conditions (Fig. 3.5B). This decrease in MTT reduction correlated with an observed decrease in the number or healthy-looking viable cells (Fig. 3.6C) indicating that this observed reduction of MTT transformation corresponds with a decrease in the number of live cells and not with a reduction in mitochondrial metabolism unrelated to the number of viable cells.

To rule out any non-specific effects caused by 4OHT treatment, the survival of Sin1F/F MEFs lacking the CreER transgene was examined. A similar analysis was carried out to test the potential toxic effect of non-specific Cre-mediated DNA recombination using CreER;Sin1+/+ and CreER;Sin1+/F MEFs. 4OHT treatment did not affect the viability of Sin1F/F MEFs (Fig. 3.6A). CreER;Sin1F/F MEFs incubated with 4OHT were used as a positive control. As expected, Cre-mediated Sin1 recombination decreased MTT reduction by 25% (CreER;Sin1F/F; Fig. 3.6A). This was not observed following CreER activation in wild type MEFs or in cells harbouring heterozygous floxed mutation (Sin1+/+ and Sin1+/F; Fig. 3.6A).

Together, these results firmly established the requirement of Sin1 in mediating the survival response of cells under basal conditions.

Figure 3.6 The loss of Sin1 decreases cell survival in MEFs. A) Sin1F/F, CreER;Sin1F/F, CreER;Sin1+/F and CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT and cell survival was evaluated 72 h after by MTT assay. Values are expressed as percentage of untreated cells. Data are mean ±SEM from seven independent experiments. *p<0.05. B) Caspase 3 activity was measured in CreER;Sin1F/F MEFs 72 h after treatment with or without 4OHT. Values are expressed as percentage of maximal activation (sorbitol treatment). Data correspond to the mean ±SEM from 3 independent experiments. C) Micrographs showing the effect of the loss of Sin1 on the morphology of MEFs (dotted lines, outline cells with enlarged cytoplasm and flat morphology). Scale bar=10 µm.

Next, to test whether the observed decrease in MTT metabolism associated with the loss of Sin1 expression was a consequence of increased apoptotic cell death, caspase 3 activity was measured using a fluorogenic caspase assay. Sorbitol was used as a positive control. No evidence of increased caspase 3 activity in the absence of Sin1 was found (Fig. 3.6B). However, it was noticed that MEFs lacking Sin1 displayed an abnormal morphology. More specifically, the cells became

flatter, larger and more adherent to the dish, features often observed in senescent cells (Fig. 3.6C).

To confirm that the decrease in the number of viable cells caused by the loss of Sin1 resulted from an increase in cellular senescence, cells were stained with the senescence marker β-galactosidase (Dimri et al., 1995). The number of positive cells was counted every other day for 10 days after Sin1 deletion. 6 days after the onset of the experiment, a significant increase in the number of senescent cells was observed in MEFs lacking Sin1 (Fig. 3.7A). Examples of positive cells for β- galactosidase staining (blue) and displaying characteristic morphological features of senescence, included enlarged flat cytoplasm, is shown (Fig. 3.7B). Senescence is induced following the activation of p53-p21 and p16-pRB pathways (Ben-Porath and Weinberg, 2005). Therefore, the effect of Sin1 ablation on the levels of p16, p21 and p53 expression was examined by immunoblot analysis. Considering that Sin1-null MEFs displayed a lower level of p16 at day 0, but a higher level at day 6, compared to control cells, it can be proposed that Sin1 partially contributes to suppressing p16 expression in MEFs cultured over a long period of time (Fig. 3.7C). In contrast, no consistent differences were observed in the level of p21 and p53 between control and Sin1-deleted MEFs, over the time course of the experiment (Fig. 3.7C). Taking together, these results suggest that the loss of Sin1 decreases cell survival by potentially inducing premature senescence through the induction of p16 expression.

Figure 3.7 The loss of Sin1 increases senescence. A) CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT and 72 h after re- plated in different dishes. Senescence was evaluated by counting the number of cells positive for β-galactosidase every other day for 10 days. Values correspond to the percentage of positive cells relative to starved cells (used as positive control). Data are mean ±SEM from three independent experiments. *p<0.05. B) Micrographs showing β-galactosidase staining after Sin1 deletion (Day 6) as well as the morphology of MEFs undergoing senescence. Scale bar=10 µm. C) The level of p16, p21, and p53 was analysed by immunoblot under the same conditions evaluated in A). Actin was used as a loading control. Representative experiment from 3 independent repeats.

3.6 CreER activation affects MEFs proliferation

The results presented so far showed that the loss of Sin1 decreased cell survival and increased senescence. To establish a link between these abnormal phenotypes, the effect of Sin1 deletion on cell proliferation was evaluated. CreER;Sin1+/+ and CreER;Sin1+/F MEFs were analysed in parallel with CreER;Sin1F/F MEFs to rule out potential side effects associated with non-specific Cre-mediated DNA recombination. MEFs were mock treated or treated with 4OHT and 72 h after, cells were trypsinized and re-plated. Cell proliferation was assessed every other day for 6 days (Fig. 3.8A). MEFs different genotypes displayed different proliferative capabilities (Fig. 3.8B, open symbols). This could be due to the fact that cells were obtained from mice that did not have the exact same background and biological variability between different preparations of primary cell cultures. More worryingly, the proliferation rate of MEFs of all three different genotypes was suppressed following the incubation of the cells with 4OHT (Fig. 3.8B, closed symbols). It has been previously reported that CreER activation alone can cause proliferation and growth defects, as well as chromosomal aberrations, aneuploidy and other non-specific genomic damage (Loonstra et al., 2001; Silver and Livingston, 2001). This problem can be overcome by using a lower 4OHT concentration and by decreasing the time of exposure (Loonstra et al., 2001). Therefore, it was tested whether the unspecific effect of CreER on cell proliferation could be eliminated by treating CreER;Sin1+/+ MEFs with 5 times less 4OHT (i.e., 100 nM) for 5 hr instead of for 24 h (Fig 3.8A). Under these new experimental conditions, 4OHT was still capable of suppressing cell proliferation (Fig 3.8C). Therefore, it was concluded that the CreER/loxP system was not a suitable approach to study cell proliferation using primary MEFs.

Figure 3.8 CreER activation affects the proliferation of MEFs. A) CreER;Sin1+/+, CreER;Sin1+/F and CreER;Sin1F/F MEFs were treated with 0 or 500 nM 4OHT (closed and open symbols, respectively) for 24 h, split and re-plated 2 days later. Proliferation was evaluated every other day for 10 days by crystal violet. B) Absorbance corresponding to relative cell number was quantified using a spectrophotometer. Data are mean ±SEM from three independent experiments. *p<0.05. C) CreER;Sin1+/+ MEFs were treated with 0 or 100 nM 4OHT (closed and open symbols, respectively) for 5 h, split and re-plated 2 days later . Proliferation was evaluated as in B) Data are mean ±SD from two independent experiments.

3.7 Discussion

To clarify the biological function of Sin1, a novel transgenic mouse model that permits the conditional deletion of the Sin1 gene was created. This model represents an advantage over the straight knockout model by limiting the establishment of potential compensatory mechanisms that can occur during embryonic development. Furthermore, this system can circumvent early embryonic lethality associated with Sin1 gene deletion to allow the effect of the loss of Sin expression to be examined in differentiated cells and adult animals.

A novel conditional knockout model was successfully established by generating fibroblasts from 13 days old CreER;Sin1F/F embryos where it was demonstrated that the conditional ablation of Sin1 in MEFs recapitulated previous findings obtained using Sin1-/- MEFs. More specifically, using this system it was shown that the loss of Sin1 selectively decreased Akt phosphorylation on Ser473 under basal conditions (Fig. 3.2) and in response to mitogenic stimulation (Fig. 3.3). The residual phosphorylation of Ser473 observed in the absence Sin1 could have been due to other kinases such as integrin-linked kinase (ILK), DNA dependent protein kinase atypical, IκB kinase ε and TANK-binding kinase 1 (TBK1) (Delcommenne et al., 1998; Bozulic et al., 2008; McDonald et al., 2008; Surucu et al., 2008; Ou et al., 2011; Xie et al., 2011). This possibility was ruled out by the demonstration that Torin1, an inhibitor of mTOR activity, completely inhibited Ser473 phosphorylation in both, control and Sin1-deleted MEFs (Fig. 3.4). Deletion of floxed genes following Cre-mediated recombination does not occur with 100% efficiency (Hayashi and McMahon, 2002). Therefore, it is proposed that CreER;Sin1F/F MEFs incubated with 4OHT display a residual level of mTORC2 activity due to incomplete Sin1 inactivation. Overall, these results are consistent with the idea that Sin1 is an essential component of mTORC2 required for phosphorylating Akt on Ser473.

Despite the remaining level of Akt Ser473 phosphorylation, the loss of Sin1 caused a significant reduction in cell survival under basal conditions (Fig. 3.5B). However, in contrast to the original report showing that primary Sin1 knockout MEFs are more susceptible to stress (Jacinto et al., 2006), no difference in the response of control and Sin1-deleted MEFs to H2O2–induced death was observed (Fig. 3.5B). One reason for this discrepancy may reside in the fact that cell survival

under basal conditions was not impaired in the aforementioned study. The ability of Sin1 knockout MEFs to survive in culture may be a consequence of cellular adaption to gene deletion acquired during early embryonic development to evade death. Compensatory mechanisms are much less likely to occur with conditional gene deletion approaches because there is only a short period of time that separates the loss of protein expression and biochemical analyses of the cells. Therefore, CreER;Sin1F/F MEFs incubated with 4OHT will provide a very useful tool in future studies aimed at characterising and analysing the regulation of Akt by mTORC2 and also to establish the biological relevance for cellular functions. In particular, this system will enable to understand the specific role of Ser473 phosphorylation with regards to determining substrate specificity of Akt. Analysis of the phosphorylation status of Akt downstream targets showed that phosphorylated Akt only on Thr308 retains catalytic activity that seems rather specific. For instance, the phosphorylation of well-characterized Akt targets such as TSC2 and GSK3β was not affected while the phosphorylation of Foxo transcription factors was significantly reduced (Guertin et al., 2006; Jacinto et al., 2006; Shiota et al., 2006). This suggests that Akt phosphorylation determines its specificity rather than its overall activity, an interesting hypothesis considering the differences in localization of both Akt and its targets (Song et al., 2005; Martelli et al., 2012). Therefore, using this system it will be possible to characterize in more detail this hypothesis. This could be achieved by screening the phosphorylation status of a wider range of Akt targets using mass spectrometry analysis, since so far only a small subset of Akt targets affected by the loss of Ser473 phosphorylation has been reported. Furthermore, the biological relevance of these findings, in terms of differences in subcellular localization, can also be tested by immunocytochemistry and cell fractionation experiments.

The requirement of Sin1 to prevent Foxo1/3-mediated transcription by maintaining Foxo1/3 phosphorylation through Akt activation (Jacinto et al., 2006) led to test the possibility that decreased cell survival caused by the loss of Sin1 was a consequence of increased apoptotic cell death. However, no evidence to support this hypothesis was found (Fig. 3.6B). It is possible that the residual levels of Akt phosphorylation on Ser473 in Sin1-null MEFs are sufficient to suppress apoptosis under basal conditions and/or redundant signalling mechanisms are activated in the absence of Sin1 to inhibit apoptosis. Alternatively, Ser473 phosphorylation may not be important for Akt to inhibit the function of pro-apoptotic proteins. This

possibility cannot be rule out by studies based on PI3K inhibitors, knockdown of Akt isoforms, or expression of constitutively active Akt (Datta et al., 1999; Manning and Cantley, 2007), which did not distinguish the effect caused by the loss of total Akt activity as opposed to the loss of individual activating phosphorylation. Therefore, additional experiments will need to be performed in the future to specifically address the requirement of Ser473 in mediating the anti-apoptotic function of Akt downstream of mTORC2. This can be accomplished by analysing the levels of phosphorylated Bad and Caspase 9 on Akt-dependent residues.

To further characterise the requirement of Sin1 in maintaining the survival of MEFs and based on the observation that Sin1-deleted MEFs displayed a morphology characteristic of senescent cells, the possible role of Sin1 in senescence was investigated. These experiments were carried out following long-term loss of Sin1 expression. More specifically, 3 days after gene disruption, cells were split every other day for 10 days. Under this experimental design, it was observed that the absence of Sin1 accelerated senescence in a p16-dependent manner (Fig. 3.7A- C). Defects in cell proliferation caused by the loss of Sin1 were carried out then to further characterise this senescent phenotype since loss of PTEN-induced senescence lacks the initial proliferative phase observed in oncogenic-induced senescence (Alimonti et al., 2010). Proliferation was found to be rapidly and significantly impaired after Sin1-deletion (Fig. 3.8B). Proliferation was evaluated in parallel in CreER;Sin1+/+ MEFs to rule out unspecific effects caused by CreER activation alone and, unfortunately this turned out to be the case (Fig. 3.8B). A similar phenomenon had been previously reported in CreER-expressing MEFs and was circumvented by lowering 4OHT concentration and decreasing the time of exposure (Loonstra et al., 2001). However, the use of this approach was unsuccessful in bypassing the defect caused by CreER activation (Fig. 3.8B). This limits the type of analyses that can be carried out with the Cre/loxP system and highlights the need for proper control experiments in studies using the Cre- mediated gene recombination system in both, cells and mice (Bersell et al., 2013). Therefore, it remains to be further clarified whether CreER;Sin1+/+ MEFs displayed premature senescence and whether the phosphorylation status of Akt on Ser473 is affected by CreER activation.

60 4. Sin1 in neuronal survival

The genetic demonstration that Rictor or Sin1 knockout Drosophila displayed a decrease in the number of dendritic branches and an increase in the amount of crossing points has suggested a role of TORC2 in dendritic tiling in Drosophila class IV neurons (Koike-Kumagai et al., 2009). Consistently, knockdown of Rictor expression in rat hippocampal neurons was shown to delay dendritic arborisation and to inhibit dendritic growth by decreasing Akt phosphorylation (Urbanska et al., 2012). On the other hand, Akt is essential for neuronal polarisation and axon/dendrite outgrowth (Barnes and Polleux, 2009; Read and Gorman, 2009). These observations have led to the idea that mTORC2/Akt signalling is critical for the establishment of functional synapses to maintain neuronal survival during brain development. To examine the role of Sin1 in this process, a model of primary culture of neurons in which the Sin1 gene could be inactivated was developed.

4.1 Methodology to study the role of Sin1 in neuronal survival

Cortical neurons were generated from 16-18 days old CreER;Sin1F/F embryos. Sin1 deletion was induced by incubating the cells with 4OHT (Fig. 4.1). Overall, cortical neurons have been extensively used to study neuronal development in vitro due to their ability to repolarise and form functional networks (Barnes and Polleux, 2009). This is also an excellent model to study neurodegeneration due to their susceptibility to cell death and because excessive loss of cortical neurons has been associated with pathological conditions such as Alzheimer's disease, stroke and hypoglycemic damage (Lesuisse and Martin, 2002).

For all experiments, neurons of different genotypes were plated and mock-treated or treated with 4OHT after plating (0 DIV, Fig. 4.1A). Control experiments were designed and performed in to order test the suitability of the system (Fig. 4.1B). First, Sin1F/F neurons lacking CreER expression were used to rule out unspecific effects caused by long-term 4OHT treatment. Next, CreER;Sin1+/+ mock-treated and treated with 4OHT were used to rule out unspecific toxic effects caused by CreER expression (Fig. 4.1B).

Finally, CreER;Sin1F/F mock-treated and treated with 4OHT were designated wt and ko neurons, respectively (Fig. 4.1B).

Figure 4.1 Strategy to generate conditional Sin1 knockout neurons A) Cortical neurons were plated and mock-treated or treated with 4OHT after plating (0 DIV), and depending on the experiment, collected after different time points. B) Sin1F/F neurons lacking CreER expression were used to test the effect of long-term 4OHT treatment while CreER;Sin1+/+ were used to test the effect of CreER expression alone on survival. CreER;Sin1F/F mock-treated and treated with 4OHT were designated wt and ko neurons, respectively (Scheme in A modified from Barnes and Polleux, 2009).

4.2 Conditional inactivation of Sin1 decreases Akt S473 phosphorylation in neurons

The efficiency of Cre-mediated gene recombination was tested by comparing the levels of Sin1 protein and mRNA after 7 and 14 DIV. CreER;Sin1F/F cortical neurons, mock treated or treated with 100 nM 4OHT were designated wt and ko neurons. The levels of Sin1 protein and mRNA were evaluated by immunoblot and RT-PCR, respectively. The results show that 4OHT treatment caused a significant reduction in Sin1 protein after 7 and 14 DIV. Consistently, a 50% decrease in the levels of Sin1 mRNA on day 7 and an 80% reduction on day 14 in vitro was observed (Fig. 4.2B).

Results presented in the previous section show that Sin1 can be specifically inactivated in CreER;Sin1F/F cortical neurons incubated with 4OHT.

Figure 4.2 Conditional inactivation of Sin1 decreases pS473 in neurons. A) CreER;Sin1F/F cortical neurons were mock treated (wt) or treated (ko) with 100 nM 4OHT after plating (0 DIV) and Sin1 levels were evaluated by immunoblot after 7 and 14 DIV. Actin was used as a loading control. Representative experiment from 2 independent repeats. B) Sin1 mRNA levels were measured by RT-PCR after 7 and 14 DIV. The data are presented as the mean ± SD from two independent experiments. C) Sin1 is required for Akt phosphorylation on Ser743 in neurons. The levels of phosphorylated Ser473 (pS473), phosphorylated Thr308 (pT308), total Akt, phosphorylated Foxo (pS253) and GSK3β pS9, and Sin1 was monitored by immunoblot after 7, 12 and 14 DIV. Actin was used as a loading control. Representative experiment from 4 independent repeats.

To examine the requirement of Sin1 for mediating Akt phosphorylation in neurons, the level of phosphorylated Akt on Thr308 and Ser473 residues was examined after 7, 12 and 14 DIV. Akt phosphorylation on Ser473 was only slightly reduced after 7 DIV, but significantly decreased after 12 and 14 DIV (Fig. 4.2C). In contrast, the absence of Sin1 did not affect the level of Akt phosphorylation on Thr308. In addition, consistent with previous findings in MEFs (Fig. 3.2B), decreased Ser473 phosphorylation correlated with decreased Akt expression (Fig. 4.2C). Furthermore, decreased pS473 Akt resulted in decreased Foxo phosphorylation but it did affect GSKβ phosphorylation on serine 9 (pS9, Fig.4.2C), in agreement with previous studies (Guertin et al., 2006; Jacinto et al., 2006), where the specific loss of S473 phosphorylation only affected a subset of Akt substrates. Taken together, these results demonstrate that Sin1 is required for the phosphorylation of Akt on Ser473 in cortical neurons.

To test the biological relevance of impaired Akt phosphorylation on Ser473, the susceptibility of Sin1 ko neurons to excitotoxic stress was examined. wt and Sin1 ko neurons displayed no significant difference with regards to their sensitivity to glutamate (Fig. 4.3A). Nonetheless, like Sin1-deleted MEFs (Fig. 3.5B), neurons lacking Sin1 displayed a significant reduction in MTT metabolism, indicative of a reduction in cell viability under basal conditions (Fig. 4.3A). To corroborate this observation, the survival of wt and ko neurons was evaluated again without manipulating/treating the neurons with or without glutamate, and a decrease in MTT transformation was consistently obtained (Fig. 4.3B). To rule out unspecific effects due to prolonged 4OHT treatment or CreER expression in neurons, as previously observed in MEFs (Fig. 3.8B), the survival of Sin1F/F neurons lacking CreER as well as that of CreER;Sin1+/+ mock treated or treated with 4OHT was evaluated (Fig. 4.1B). The survival of CreER;Sin1F/F mock treated (wt) or treated (ko) was analysed in parallel to confirm this result in cultures prepared at the same time (Fig. 4.3C). Consistent with the results obtained previously, 4OHT did not have any effect on the MTT assay, suggesting that 4OHT does not affect the viability of neurons lacking CreER expression or neurons expressing CreER but lacking the Floxed alleles, thereby indicating that the effect in cell survival is due to the decrease in Sin1 expression (Fig. 4.3C). Furthermore, Sin1 ko neurons displayed fewer and unhealthy processes, and overall a damaged network (Fig. 4.3F).

Figure 4.3 The lack of Sin1 decreases neuronal survival and cell size A) Sin1F/F cortical neurons were mock treated (wt) or treated (ko) with 100 nM 4OHT after plating (0 DIV). After 14 DIV neurons were incubated with 0 (vehicle) or 100 µM Glutamate for 30 min. Cell survival was measured by MTT assay 24 h later. Values are expressed as percentage of untreated control cells. The data are presented as the mean ± SEM from three independent experiments. *p<0.05. B) Cell survival was evaluated in wt and ko neurons at 14 DIV by MTT. *p<0.05. C) Neurons of the indicated genotype were mock treated or treated with 4OHT and cell survival was evaluated at 14 DIV. The data are presented as the mean ± SEM from three independent experiments. *p<0.05. D) The number and E) size of neurons was analysed and the data are expressed as % of wt cells ± SEM from 3 independent experiments, *p<0.05. F) Micrographs showing the morphology of wt and ko. Scale bar 10 µm.

Based on these observations, the number and size of neurons were quantified. Sin1 knockout neuronal cultures displayed a 35% decrease in cell number, further

demonstrating the decreased in cell survival caused by the loss of Sin1 (Fig. 4.3D). Cell size, measured relative to the total area of healthy-looking neurons, was also significantly reduced by a 20% in Sin1 ko neurons (Fig. 4.3E). Together, these results convincingly demonstrate that Sin1 is required for neuronal survival and is involved in regulating neuronal size.

4.3 Loss of Sin1 increases apoptotic neuronal death

To characterise the cellular mechanism underlying the survival function of Sin1 in neurons, the effect of Sin1 deletion on apoptotic cell death was examined. First, the number of neurons with condensed, fragmented nuclei, characteristic of later stages of apoptotic cell death (Kerr et al., 1972; Wyllie, 1980) was counted. A significant increase in apoptotic nuclei was observed in ko neurons compared to wt cells after 14 DIV (Fig. 4.4A). Although, wt and ko neurons presented no sign of DNA fragmentation up until 14 DIV, DNA laddering was detected after 21 DIV in the absence of Sin1 (Fig. 4.4B). Caspase 3 activation was evaluated by detecting the cleavage of the pro-form (37 kDa) into an active product (p19), as well as by caspase 3 assay using a fluorogenic substrate. Neither caspase 3 cleavage (Fig. 4.4C) nor increased caspase 3 activity (Fig. 4.4D) were observed in neurons lacking Sin1 after 7 and 14 DIV.

Figure 4.4 The loss of Sin1 increases neuronal apoptosis A) The number of fragmented and condensed apoptotic nuclei stained using Hoechst was counted after 14 DIV. Data are expressed as percentage of apoptotic cells relative to total. B) DNA laddering was assessed by ethidium bromide staining following electrophoresis at the indicated times (DIV). C) Cleaved caspase 3 and Bim expression after 7 and 14 DIV were detected by immunoblot. Actin was used as a loading control. Representative experiment from 2 independent repeats. D) Caspase activity was measured using a fluorogenic substrate after 14 DIV. Neurons treated with staurosporine (ST) (100 nM) and ST plus zVAD (20 µM) were used as positive controls. Data are expressed as % of maximal activation (ST) from three independent experiments. E) Neurons were treated with the pan- caspase inhibitor zVAD (20 µM) after 12 DIV or with F) QVD (20 µM) after 7 and 11 DIV. Cell survival was measured by MTT assay after 14 DIV. Values are expressed as percentage of wt cells. The data are presented as the mean ± SEM from three independent experiments*p<0.05. G) Bim mRNA was measured by qRT-PCR in neurons after 7 and 14 DIV. Data are expressed as fold ± SD relative to wt cells at 7 DIV from two independent experiments.

To confirm that Sin1 deficiency induced neuronal death independently of caspases, the effect of a pan-caspase inhibitor, namely zVAD (20 µM), on cell , was tested. zVAD was added to the culture after 12 DIV and cell survival was evaluated after 14 DIV. The ability of zVAD to prevent staurosporine-induced caspase 3 activation was used as positive control (Fig. 4.4D). Under these experimental conditions, zVAD was unable to rescue neuronal death caused by the loss of Sin1 and measured after 14 DIV (Fig. 4.4E). Similarly, incubation of neurons with QVD, a less cytotoxic and more effective pan-caspase inhibitor (Chauvier et al., 2007), twice, on day 7 and 11, did not prevent the neuronal loss of Sin1 ko neurons after 14 DIV (Fig. 4.4F). Altogether, these results demonstrate that the increased number of apoptotic nuclei caused by Sin1 deficiency is independent of caspase activation. A type of caspase-independent apoptotic neuronal death caused by short time exposure to glutamate has been previously reported to occur in a Bim-dependent manner (Concannon et al., 2010). Furthermore, the bim promoter is a well-characterised target of Foxo transcription factors implicated in neuronal death (Gilley et al., 2003; Biswas et al., 2007; Davila et al., 2012). Hence, to examine the role of Bim in Sin1-mediated cell survival, changes on the levels of Bim mRNA and protein in wt and ko neurons were examined. The loss of Sin1 did not have an effect on the levels of Bim protein (Fig. 4.4C). However, the loss of Sin1 caused an important decrease in Bim mRNA levels after 7 and 14 DIV (Fig. 4.4G).

4.4 Autophagy is not increased in Sin1 ko neurons

Since Sin1 ko neurons displayed only certain characteristics of classical apoptosis, other mechanisms underlying neuronal loss in the absence of Sin1 were investigated. In particular autophagy was examined as a potential stress response associated with Sin1 deficiency by analysing the autophagy markers LC3-II and p62 (Denton et al., 2012). The level of p62 was slightly reduced in Sin1 ko compared to wt neurons at 7 and 14 DIV (Fig. 4.5A), while the level of lipidated LC3 (LC3-II, lower band) was very similar after 7 DIV and slightly increased after 14 DIV in ko cells (Fig. 4.5A). This suggested that Sin1 contributed to inhibiting autophagy in neurons raising the possibility that autophagy acts as a potential mechanism by which Sin1 ko neurons undergo death. This hypothesis is supported by genetic evidence showing that neurons lacking essential

components of the autophagic machinery display decreased survival (Hara et al., 2006; Komatsu et al., 2006).

However, autophagy can also be activated to protect cells against stress (Kroemer et al., 2010; Das et al., 2012). Therefore to clarify the role of autophagy as a pro- or an anti-cell death mechanism in neurons, neurons were treated with an inhibitor of autophagy (3MA) on day 12, and survival was measured at 14 DIV. 3MA treatment decreased the survival of neurons, causing a 50% increase in cell death (Fig. 4.5B). Sin1 ko neurons incubated with 3MA displayed a similar reduction in survival (Fig. 4.5B). Similarly, an 85% increased neuronal death was observed following incubation of wt and Sin1 ko cells with bafilomycin, an inhibitor of the autophagosome-lysosome fusion (Fig. 4.5B). These results indicate that autophagy acts as a pro-survival mechanism in neurons. Therefore increased autophagy in the absence of Sin1 cannot be responsible for the decreased survival of Sin1 ko neurons under basal conditions. Instead, autophagy may be activated to counteract the stress caused by impaired mTORC2/Akt signalling.

Figure 4.5 Autophagy acts as a survival mechanism in neurons. A) The level of the autophagic markers p62 and LC3II were evaluated in cortical neurons at 7 and 14 DIV. Actin was used as a loading control. Representative experiment from 2 independent repeats. B) Neurons were treated with the autophagy inhibitor 3MA (5 mM) at 12 DIV and cell survival was measured by MTT assay at 14 DIV. Values are expressed as percentage of mock treated cells. The data are presented as the mean ± SEM from three independent experiments. *p<0.05.

4.5 The loss of Sin1 does not increase necroptotic neuronal death

An alternative more recently described form of organised necrosis, termed necroptosis, was evaluated as a potential mechanism of caspase-independent apoptotic cell death. One of the key events that occurs in necroptosis is the release from the mitochondria and the translocation to the nucleus of the apoptosis-inducing factor AIF (Delavallée et al., 2011). Therefore, the effect of Sin1-deficiency on the subcellular distribution of AIF was examined by analysing mitochondrial and nuclear extracts of neurons. Sin1 ko neurons displayed a slight decrease in mitochondrial AIF compared to control cells, indicative of mitochondrial release of AIF in the absence of Sin1 (Fig. 4.6A). However, no increase in nuclear AIF was detected in Sin1 knockout neurons compared to wt cells (Fig. 4.6A). Considering that a significant amount of VDAC, a mitochondrial marker, was detected in nuclear fractions, the possibility that Sin1 deletion causes nuclear accumulation of AIF cannot be excluded, but this effect is masked by mitochondrial contamination of nuclear fractions.

One of the other features of necrosis and necroptotic cell death is the disruption of the plasma membrane (Syntichaki and Tavernarakis, 2003). Therefore, the release of the cytosolic enzyme lactate dehydrogenase (LDH) in the media, caused by plasma membrane disruption, was assessed as another mean to analyse necroptosis. The results show that Sin1 ko and wt neurons display a similar amount of LDH activity in the media (Fig. 4.6B).

Figure 4.6 The loss of Sin1 does not increase necroptotic neuronal death. A) AIF release from the mitochondria and translocation to the nucleus was evaluated in neurons at 14 DIV by immunoblot analysis. VDAC and lamin B were used as controls for the mitochondrial and nuclear fractions, respectively. * unspecific band. Representative experiment. B) LDH release in culture media was measured at 14 DIV. The release from Triton-treated neurons was use to calculate maximal LDH activity. The data are presented as the mean ± SEM from three independent experiments. Neurons were treated with the necroptosis inhibitor Nec1 (5 µM) at 12 DIV C), and at 7 and 11 DIV D) and cell survival was measured by MTT assay at 14 DIV. Values are expressed as percentage of wt treated cells. The data are presented as the mean ± SEM from three independent experiments. *p<0.05.

In parallel, wt and Sin1 ko neurons were incubated with the necroptosis inhibitor necrostatin 1 (Nec1) to determine whether the decrease in cell survival caused by the loss of Sin1 could be prevented by blocking necroptosis. Neurons were treated with Nec1 on day 12 and the MTT transformation measured on day 14. Nec1

treatment slightly increased the MTT reduction of wt neurons, but did not prevent the observed decrease that correlated with the death of Sin1 ko neurons (Fig. 4.6C). To investigate whether decreased neuronal survival associated with Sin1 deletion could be prevented by incubating the cells with Nec1 at early time points, neurons were treated twice with the inhibitor, at 7 and 11 DIV. Under this new experimental condition, no evidence that blocking necroptosis prevented neuronal loss caused by the absence of Sin1 was found (Fig. 4.6D). Taken together, these results show that necroptosis is not a mechanism by which the loss of Sin1 decreases neuronal survival.

Next, neuronal polarisation and changes in the synaptic protein Synaptophysin (Syp) were analysed in wt and Sin1 ko neurons to investigated the role of Sin1 in neuronal polarisation and synaptogenesis in order to establish a correlation between defects in these two processes and the observed decrease in neuronal survival.

4.5.1 The loss of Sin1 does not affect neuronal polarisation

Akt has been shown to be crucial for neuronal polarisation and axonal growth (Shi et al., 2003; Read and Gorman, 2009). Importantly, Akt phosphorylated on Ser473 localises at the tip of the axon and is essential for axon specification and growth (Shi et al., 2003). Since Akt phosphorylation on Ser473 depends on Sin1, the requirement of Sin1 in neuronal polarisation and axonal growth was evaluated. At day in vitro 3 (3 DIV), wt and ko neurons were fixed and immunostained with the axon-specific marker Tau and the neuronal specific marker βIII tubulin (Fig.4.7A- B). Both, the length of the axons and the number of polarised neurons were analysed and no significant decrease in axonal length in Sin1 ko neurons was observed (Fig. 4.7D). Moreover, no difference was detected in the number of polarised neurons between wt and Sin1 ko neurons (Fig. 4.7E). To analyse this in more details, the level of Sin1 and phosphorylated Akt was analysed by immunoblot. As expected, Sin1 expression was reduced in ko neurons, after 3 DIV. However, this did not correlate with a significant decrease in Akt phosphorylation on Ser473 (Fig. 4.7C). Similarly, there was no marked difference in the level of Akt and phosphorylated Akt on Thr308, between wt and Sin1 ko neurons (Fig.4.7C).

Figure 4.7 The loss of Sin1 does not affect neuronal polarisation. A) Schematic representation of the experimental design. Neurons were plated and mock treated (wt) or treated with 4OHT (ko). B) 3 days after plating and 4OHT treatment, neurons were fixed and immunostained with the axonal marker Tau and βIII tubulin to visualised neurites. Scale bar 10 µm. C) Sin1, phosphorylated Ser473 (pS473), Thr308 (pT308), and total Akt were analysed by immunoblot. Representative experiment from 3 independent repeats. Actin was used as a loading control. D) Axon length was measured and is expressed as a percentage relative to wt neurons. E) The number of polarised neurons is expressed as a percentage relative to the total number of neurons. F) wt and ko neurons were treated with the mTOR kinase inhibitor Torin1 (200 nM) for 2 h and the level of phosphorylated Akt on Ser473, total Akt and Sin1 was detected by immunoblot. Representative experiment from 2 independent repeats. (Scheme in A modified from Barnes and Polleux, 2009).

Therefore, the lack of effect of Sin1 deletion on axon length and polarisation could be a consequence of normal level of Akt phosphorylation on Ser473 in Sin1 null cells at 3 DIV. To test whether phosphorylated Akt on Ser473 was due to mTORC2 activity, neurons were treated with the mTOR kinase inhibitor, Torin1. Inhibition of mTOR kinase activity completely inhibited Ser473 phosphorylation in both wt and Sin1 ko neurons, suggesting that there may be remaining undetectable levels of Sin1 that are sufficient to maintain Ser473 phosphorylated, or that other kinases upstream mTOR substitute or are responsible for maintaining this phosphorylation at early stages of development due to its essential role in polarisation and survival (Fig.4.7F).

4.6 The loss of Sin1 does not affect Synaptophysin level

The establishment of functional synapses is essential for proper neuronal function (McAllister, 2007). To test whether Sin1 ko neurons retained the ability to express synaptic proteins and hence form functional synapsis, the levels of Synaptophysin, an essential presynaptic protein (Kwon and Chapman, 2011), were analysed both, by immunofluorescence, to observe its localisation and by immunoblot. In addition, the mRNA levels of Syp were evaluated by RT-PCR. As expected, Syp localised to the neuronal soma and along the neurites (Fig. 4.8A), and its expression increased over time as neurons mature in vitro (Fig. 4.8B). Althought the localisation of Syp was not affected by the loss of Sin1 (Fig. 4.8A), a slight but reproducible decrease in the levels of Syp expression was detected in Sin1 ko neurons at 7 and 14 DIV (Fig. 4.8B). However, Syp mRNA levels at 12 DIV were similar those observed in wt neurons (Fig. 4.8C). This transient decrease may be compensated to maintain Syp levels and ensure proper synaptogenesis, however, this compensation cannot be sustain as neurons start to die, hence the decrease observed at 14 DIV. Further studies will need to be conducted in order to further investigate the role of Sin1 in synaptic transmission.

Figure 4.8 The loss of Sin1 does not affect Synaptophysin expression A) wt and ko neurons were fixed and immunostained with an anti-Synaptophysin (Syp) antibody followed by a fluorescence-conjugated secondary antibody. Representative micrographs were taken using a fluorescent microscopy and depict Synaptophysin localisation in neurons. Scale bar 10 µm. B) The level of Synaptophysin was analysed by immunoblot at the indicated times. Actin was used as a loading control. Representative experiment from 3 independent repeats. C) Synaptophysin mRNA level was measured by RT-PCR at 12 DIV. The data are presented as the mean ± SEM from three independent experiments.

4.7 Discussion

Sin1 has been reported to be required for dendritic tiling in Drosophila neurons (Koike-Kumagai et al., 2009), while Rictor knockdown in rat hippocampal cultured neurons decreased dendritic arborisation (Urbanska et al., 2012). However, the relevance of these findings has not been clearly established, mostly because of the early embryonic lethality caused by the deletion of components of the mTORC2 signalling pathway in mice (Guertin et al., 2006; Jacinto et al., 2006; Shiota et al., 2006). In particular, the role of Sin1 in mammalian neurons has never been investigated. To address this issue, a novel model of primary cortical neurons from CreER;Sin1F/F mouse embryos was generate to conditionally ablate Sin1 expression. Using this system, it was demonstrated that Sin1 expression can be successfully disrupted following the incubation of CreER;Sin1F/F neurons with 4OHT (Fig. 4.2A). Cortical neurons have been extensively used to study various neuronal processes (Lesuisse and Martin, 2002). In particular, mature cortical neurons have been employed to explore molecular mechanisms associated with pathological conditions, such as stroke or traumatic brain injury, as well as age- related neurodegenerative conditions (Lesuisse and Martin, 2002; Saxena and Caroni, 2011; Baron et al., 2014). Cortical neurons can also be employed to study important developmental processes, including cellular polarisation and the formation of functional networks (Barnes and Polleux, 2009; Beaudoin et al., 2012). Embryonic neurons mature in vitro and become fully functional neurons from around day 10 onwards in vitro because from this point, they display functional synapses and have established hundreds of connections forming a complex network (Lesuisse and Martin, 2002; Beaudoin et al., 2012). Consequently, the Sin1 ko cortical neuronal model constitutes an important in vitro system to permit the identification of relevant phenotypic defects associated with neurodegeneration. Sin1 deletion decreased Akt phosphorylation on Ser473 in mature neurons (Fig. 4.2C) and caused a decrease in cell size (Fig. 4.3E) and cell survival (Fig. 4.3A-D). Decrease cell size has been previously reported in Rictor knockout Purkinje cells (Thomanetz et al., 2013), Rictor knockout cerebral cortex (Carson et al., 2013) and in dopaminergic neurons transfected with dominant negative Akt (Mazei-Robison et al., 2011). This is an important finding since it corroborates previous observations and furthers aids to establish the function and significance of mTORC2 in neurons.

The decreased phosphorylation of Akt on Ser473 did not correlate with increased neuronal sensitivity to excitotoxicity (glutamate treatment; Fig. 4.3A), but it was consistent to that observed in MEFs, where H2O2 treatment did not increase the susceptibility of fibroblasts to death (Fig. 3.5B). A possible explanation for this lack of increase sensitivity is that Sin1 ko neurons may be increasing the anti-apoptotic or cell death response beforehand, so that in the presence of the toxic stimuli they already express more genes involved in survival or less pro-apoptotic genes (See Chapter 5).

Importantly, like in MEFs, Sin1 was found to be required for maintaining cell survival under basal conditions through inhibiting death via a caspase-independent mechanism. More specifically, the loss of Sin1 caused an increase in the number of neurons with condensed nuclei and DNA laddering, independently of increased caspase 3 activity (Fig. 4.4A-D). However, DNA laddering was observed after 21 days, suggesting that possibly at later time points, more neuronal death with clearer apoptotic features such as increased caspase-3 activity, occurs due to the inability of neurons to cope with a decrease in Sin1 and thus active Akt.

The lack of caspase-dependent apoptosis result was surprising considering that Akt is known to negatively regulate cell death by apoptosis via both transcriptional dependent and independent mechanisms (Datta et al., 1999; Song et al., 2005). For example, Akt can suppress increased Bim expression by inhibiting the nuclear translocation of Foxo3 upon phosphorylation (Dijkers et al., 2002; Stahl et al., 2002). Similarly, Akt can block the pro-apoptotic function of Bad by sequestering Bad in the cytoplasm through 14-3-3 interaction (Datta et al., 1997). However, Akt phosphorylation on Ser473 may not be required for Bad phosphorylation since, as previously discussed, decrease Ser473 phosphorylation affects only affects a subset of Akt targets (Polak and Hall, 2006), possibly due to its subcellular localisation (Bhaskar and Hay, 2007). Alternatively, the requirement of Ser473 may be cell and/or context specific since the level of Foxo1 phosphorylation on S256 in neurons lacking Rictor is, in fact, increased (Thomanetz et al., 2013). Thus, it remains to be established in Sin1-null neurons the set of targets affected by the loss of Akt Ser473 phosphorylation and its relationship to the increase in apoptotic death. Apoptosis is an important mechanism of neuronal death, particularly during brain development (Nijhawan et al., 2000). However, mature neurons are equipped by redundant mechanisms to effectively suppress

programmed cell death, enabling these irreplaceable cells to survive for an entire lifetime (Mattson, 2000). Therefore, it is possible that in the absence of Sin1 and decreased Akt signalling, neurons activate alternative mechanisms to block the activation of the caspase cascade, and survive until the mechanisms to inhibit or bypass death are exhausted. Based on the characteristic morphology displayed by the dying cells, it was expected that Sin1 ko neurons underwent a form of programmed cell death (Fig. 4.3F). In deed, it was found that Sin1 ko neurons displayed a slight, but nonetheless reproducible, decreased level of mitochondrial AIF, compared to wt neurons (Fig. 4.6A). This is interesting considering that the translocation of AIF from the mitochondria to the nucleus has been implicated in mediating nuclear condensation independently of caspase activation (Leist and Jäättelä, 2001). Furthermore, AIF translocation to the nucleus has recently been reported to take place after Akt inhibition in colon cancer cells (Agarwal et al., 2014). Therefore, it is possible that Sin1 promotes neuronal survival, at least in part, by preventing the mitochondrial release of AIF. Further studies, including immunocytochemical analyses to determine the subcellular localisation of AIF in wt and Sin1 ko neurons, as well as treatment with an AIF inhibitor, will be required to confirm this hypothesis.

Neuronal polarisation and the formation of functional synapses are essential processes required for proper neuronal function and hence survival (McAllister, 2007; Barnes and Polleux, 2009). Thus, in order to establish whether the loss of Sin1was affecting survival by impairing these two processes, neuronal polarisation as well as the levels of one of the most abundant synaptic protein, Synaptophysin were evaluated. The loss of Sin1 did not affect neuronal polarisation and axon length (Fig. 4.7D-E). In fact, despite the reduction in Sin1 level at day 3, the level of Akt phosphorylation on Ser473 was only slightly reduced (Fig.4.7C), while the level of phosphorylated Thr308 and total Akt remained unchanged (Fig.4.7C). Therefore, the lack of effect of Sin1 deletion on axon length and polarisation could be explained by the fact that phosphorylation on Ser473 remains unchanged shortly after Sin1 inactivation (Fig.4.7C). One possibility is that the absence of mTORC2, Akt is phosphorylated by another kinase such as ILK, DNA dependent protein kinase atypical, IκB kinase ε or TBK1 as previously reported (Delcommenne et al., 1998; Bozulic et al., 2008; McDonald et al., 2008; Surucu et al., 2008; Ou et al., 2011; Xie et al., 2011). This hypothesis was ruled out by showing that an mTOR inhibitor, Torin1, completely inhibited Akt Ser473

phosphorylation in cortical neurons at 3 DIV (Fig.4.7F). Alternatively, Akt may be specifically protected against dephosphorylation for a short period after the initial loss of Sin1, due to its essential role in regulating key processes required for neuronal development and survival (Tschopp et al., 2005; Dummler and Hemmings, 2007). This possibility remains to be tested.

On the other hand, the levels of synaptophysin were only transiently affected by the loss of Sin1, possibly as a compensatory mechanism to counteract the loss of Sin1 at early time points, however, this cannot be longer be the case as neurons start to die (Fig. 4.8B and 4.3F). The damaged network observed in Sin1 ko neuronal cultures (Fig. 4.3F) could be related to the previously reported effect of Rictor knockdown on dendritic arborisation (Urbanska et al., 2012). Furthermore, Rictor knockout pyramidal neurons displayed less dendritic spines (Huang et al., 2013). Therefore, reduced synaptic input may be responsible for decreased expression of survival genes after synaptic stimulation (Hardingham and Bading, 2010), thereby contributing to neuronal death in the absence of Sin1. To test this possibilities, the number of dendritic spines and the levels of excitatory and inhibitory synaptic activity remain to be evaluated.

Taken together, the results presented in this chapter showed that Sin1 is required for neuronal survival, but the precise mechanism remains to be uncovered.

5. Sin1 and gene expression in neurons

Neuronal survival is directly controlled by synaptic activity. Basal physiological levels of synaptic activity maintain the expression of genes involved in cell survival, a process often referred to as 'activity-dependent neuroprotection' (Hardingham and Bading, 2010). Calcium is known to regulate this process by controlling the communication between the synapse and the nucleus, causing changes in gene expression (Zhang et al., 2009). For example, synaptic stimulation of the glutamatergic N-methyl-D-aspartate (NMDA) receptor causes calcium entry and calcium-induced calcium release from intracellular stores, leading to the activation of the transcription factor CREB (Papadia et al., 2005). CREB activation induces the expression of genes that confer protection from insults (e.g. increased expression of anti-apoptotic proteins such as Bcl-2) and genes that increase cellular antioxidant defences (Papadia et al., 2005). CREB can also decrease the expression of pro-apoptotic proteins (Lonze and Ginty, 2002). Activity-induced neuroprotection can also occur independently of calcium and CREB via the PI3K pathway (Papadia et al., 2005). Likewise, changes in gene expression are required to execute programmed cell death (Portt et al., 2011). In order to determine whether the loss of Sin1 causes changes in gene expression that may be related to the observed survival phenotype, and to uncover novel genes regulated by mTORC2 signalling, microarray analysis was performed in neurons after Sin1 deletion.

5.1 Methodology used to study the role of Sin1 in gene expression

Microarray technology has become a useful tool to evaluate changes in gene expression across the genome (Hoheisel, 2006). This technology is based on the signal produced by the hybridisation of probes with their particular target, which directly correlates with the amount of mRNA present in the sample and thus, with the level of expression of the gene (Hacia et al., 1998). Each probe is designed to hybridise with different mRNA sequences. The mouse genome array that was used in this study permits the analysis of more than 39,000 transcripts and variants. Based on results show in Chapter 4, arrays were performed at a time point when Sin1 ko neurons appeared healthy, displaying no morphological changes. Hence, cortical neurons were cultured and treated with 4OHT on 0 DIV. Both, RNA and proteins were extracted from cells at 12 DIV. Protein lysates were

used to confirm efficient recombination of the Sin1F allele by immunoblot analysis using a phospho-Ser473 Akt antibody, since at this point, the antibody used to detect Sin1 was no longer commercially available. Two independent neuronal preparations were analysed.

As shown in Figure 5.1A, the levels of phosphorylated Akt on Ser473 were significantly reduced in both neuronal preparations. This decrease was in agreement with 50% reduction in Sin1 mRNA (Fig. 5.1B).

Figure 5.1 pS473 Akt and Sin1 mRNA levels in cortical neurons at 12DIV CreER;Sin1F/F neurons were mock treated (wt) or treated with 100 nM 4OHT (ko) after plating (0 DIV) and cells collected after 12 DIV. A) Lysates obtained from two independent neuronal cultures were analysed by immunoblot using a specific antibody to phosphorylated Akt on Ser473 (pS473). Actin was used as a loading control. B) Sin1 mRNA level was measured by RT-PCR in the same samples. The data are presented as the mean ± SD from the two independent cultures.

After statistical analysis of the microarray data, 9 up-regulated and 231 down- regulated genes were identified (Fig. 5.2). The small number of up-regulated genes may be explained by the fact that neurons under resting conditions are not transcriptionally very active (Akins et al., 1996). The total number of genes expressed in a higher level (log2 change ≥0.585) was around 30, but with p values higher than 0.05. Among these genes, cFos, Npas4, Bdnf, and Rgs2 displayed the highest levels of expression.

Figure 5.2 Sin1 dependent gene expression in cortical neurons. Microarray analysis was performed with mRNAs extracted at 12 DIV from wt or ko. Data were analysed and the number of genes with a significant differential expression is shown (log2 change of ±0.585 and a p<0.05). The total number of significantly up (red) or down (green) regulated genes is shown.

A list containing the identity of the 231 down-regulated genes was further analysed for gene ontology (GO) enrichment.

5.2 Functional analysis of genes down-regulated in absence of Sin1

In order to establish a functional link between Sin1 deletion and changes in neuronal gene expression, the list of down-regulated genes was analysed using gene ontology (GO) enrichment bioinformatics tools. This analysis finds whether there is an over-representation of genes associated with different categories, including Biological Processes, Cellular Components and Molecular Function. The analysis was also performed to determine whether a particular Protein Class was significantly over-represented in the list of down-regulated genes. Finally, the analysis examined whether clusters of these down-regulated genes were enriched in certain signalling pathways.

Figure 5.3 Functional analysis enrichment of gene ontology terms. The set of down-regulated genes in Sin1 ko neurons was analysed using PANTHER to determine significant enrichment of gene ontology (GO) terms associated to A) Biological Processes, B) Cellular Component and C) Molecular function. The graphs display the number of relevant genes belonging to the specified category and next to the corresponding p value.

The statistically significant enrichments for Biological Processes are depicted in Figure 5.3A. Both, complex biological processes such as neurotransmission and transcription, as well as more basic cellular processes, such as amino acid and lipid metabolism, were found to be affected. Around 20% of the total of down- regulated genes were found to be enriched in the nucleobase-containing

compound metabolic processes. This is in accordance with a significant number of DNA binding (transcription factor activity) and mRNA binding proteins found in the Molecular Function category (Fig.5.3C). Furthermore, genes related to neurological system processes such as nervous system development, synaptic transmission and neurotransmitter secretion processes, were also significantly enriched. Significant enrichment of genes involved in cell-cell adhesion, chromatin organisation, as well as cell cycle, was also observed.

Interestingly and in agreement with the role of mTORC2 in regulating actin cytoskeleton (Jacinto et al., 2004), both cytoskeleton and actin cytoskeleton genes were found in the Cellular Component category (Fig. 5.3C). Extracellular region and extracellular matrix were the next cellular component categories found to be over-represented. This correlates with the enrichment in Biological Processes such as cell adhesion, synaptic transmission and neurotransmitter secretion (Fig. 5.3A).

The Molecular Function categories with a significant enrich number of genes also correlated with the enrichment in genes related to the over-represented Biological Processes and Cellular Components described earlier. Some GO terms illustrating this point are 'mRNA binding', 'DNA binding transcription factor activity', 'receptor activity', 'receptor binding', 'structural constituent of cytoskeleton', 'cytoskeletal protein binding' and 'anion channel activity' (Fig.5.3C).

Next, Protein Class analysis showed that, in accordance with the enrichment in genes related to 'nucleic acid binding' and 'transcription factor activity' found under the Molecular Function category (Fig.5.3C), 30 out of the 231 down-regulated genes coded for transcription factors (Fig.5.4A). Furthermore, 28 out of the 231 genes coded for cell surface receptors (Fig. 5.4A). Other Protein Class found were extracellular matrix proteins, cytoskeletal proteins, cell adhesion molecules and anion channel (Fig. 5.4A). Finally, in terms of catabolic enzymatic activity, enrichment of genes coding for hydrolases and oxidoreductases was observed (Fig.5.4A-B).

Figure 5.4 Protein classes affected by the loss of Sin1 in cortical neurons. A) Proportion of proteins belonging to the depicted class after the loss of Sin1 in cortical neurons. B) The number of genes belonging to the Protein class shown in A is displayed together with the corresponding p value.

As mentioned before, in the Protein Class category, the two categories with the largest number of genes were transcription factors and receptors, followed by cytoskeletal proteins, oxidoreductase and cell adhesion molecules. Among the transcription factors, 4 of them belong to the basic helix-loop-helix, and 3 to the

HMG box transcription factors family. Among the 16 total cytoskeletal proteins, 12 belong to the actin family, and 6 to the non-motor acting binding protein class (Fig.5.4B).

Finally, the representation of these down-regulated genes in specific cellular pathways was analysed. The most over-represented pathway, with 8 genes found to be down-regulated, was the Gonadotropin releasing hormone receptor pathway. In agreement with the Biological Processes, Cellular Components or Molecular Function affected, the EGF receptor pathway and angiogenesis were also found, with 4 and 7 genes, respectively. Other pathways involved in neurotransmission and neurosecretion were also observed. The down-regulated genes found in each pathway are listed in Table 3. Interestingly, genes involved in glutamatergic transmission mediated by metabotropic receptors and glutamine metabolism were also found to be affected.

Table 3. Pathways affected by the loss of Sin1 in cortical neurons

In summary, the Gene Ontology analysis suggested that the loss of Sin1 affected the communication between neurons. In addition, this analysis showed that the overall signalling from the plasma membrane to the nucleus of neurons was impaired, since a decrease in receptor activity and transcription were among the most affected processes. Furthermore, some of the down-regulated genes have also been involved in neuronal survival (Kawase-Koga et al., 2010).

5.3 Array validation by RT-PCR

In order to validate the results obtained from the microarrays, the expression of 11 down-regulated and 4 up-regulated genes was analysed by RT-PCR. The genes were selected both taking into account the fold of change and their relevance to Sin1/mTORC2 signalling. A table of the selected genes, as well as their function is shown in Table 4 and Table 5 below:

Table 4 Function of selected genes down-regulated in Sin1 ko neurons

Selected genes obtained from microarray analysis. Gene function was obtained from www.genecards.org

Table 5 Function of selected genes up-regulated in Sin1 ko neurons

Selected genes obtained from microarray analysis. Gene function was obtained from www.genecards.org.

RT-PCR was performed in the samples used for the array experiments plus freshly prepared mRNA from an independent experiment. From the 11 selected down- regulated genes, only 2 were significantly reduced: Ntrk2 and Pdgfra. In addition, a trend to be approximately 50% reduced without reaching statistical significance was observed in the case of Atp1a2, Egfr, Fgfr3 and Ndgr2 (Fig. 5.5A).

Figure 5.5 Validation of microarray data by RT-PCR of selected genes. mRNA levels of 11 selected down-regulated (A) and 4 up-regulated (B) genes was quantified by RT-PCR. Gapdh was used as an internal control. The data are presented as fold relative to the level of mRNA in wt neurons from three independent experiments. One-way ANOVA ***p<0.001, **p<0.01, *p<0.05.

In the case of the up-regulated genes, a general trend to be increased was also observed. However, the only statistically significant difference observed was for cFos, while Bdnf increase occur to a lesser extent (Fig.5.5B). This result can be explained by the difference observed among experiments, since the error bars show an important variability in the data. Nonetheless, two interesting targets were increase, with statistical significance in the case of cFos. Additional repeats are required to further confirm these observations, since at the moment the variability among samples precludes to make a clearer conclusion.

In summary, based on the array validation by RT-PCR, it is possible that one of the most significantly affected pathways, which correlates and explains the decrease in neuronal survival, is the BDNF pathway. BDNF, as well as its receptor, Ntrk2, were found to be importantly affected (up and down-regulated, respectively) in neurons lacking Sin1. It is possible that the increase in BDNF acts as a compensatory mechanism due to the important down-regulation in its receptor. Furthermore, the impairment of pathways involved in the overall cellular response to growth factors, cell communication and actin cytoskeleton may contribute to the decrease in survival.

5.3.1 Discussion

Neurons respond to changes in their environment by adjusting their gene expression program, enabling them to survive or die depending on the nature of the stimulation (Zhang et al., 2002). Therefore, to further characterise the molecular mechanism underlying cortical neuronal survival, changes on gene expression programs in wt versus Sin1 ko neurons were analysed by microarray technology. Interestingly, the number of up-regulated genes associated with the loss of Sin1 was very small in comparison to the number of down-regulated genes (Fig. 5.2). Gene ontology enrichment analysis of the down-regulated genes showed that one of the most significantly affected biological processes was transcription (Fig.5.3A). In fact, 30 of the down-regulated genes were transcription factors (Fig.5.4B), consistent with the small number of up-regulated genes. The effect of Sin1 ablation on a selected group of down- and up-regulated genes was verified by RT-PCR.

Decreased expression of genes coding for cell surface receptors involved in neuronal survival, such as Ntrk2 (the receptor for BDNF), and Pdgfra (Fig. 5.5A), was consistent with decreased survival exhibited by Sin1 ko neurons (Ghosh et al., 1994; Brunet et al., 2001; Funa and Sasahara, 2014). A trend towards decreased expression was also observed for other down-regulated genes, including Lamp2 and Ndrg2. The protein encoded by Ndrg2 was of interest for the present study because it has been reported to be important for dendritic outgrowth (Takahashi et al., 2005), providing a potential mechanism by which dendritic arborisation is impaired in mTORC2-deficient hippocampal neurons (Urbanska et al., 2012). Furthermore, changes in NDRG2 have also been reported to occur in Alzheimer's disease (Mitchelmore et al., 2004). On the other hand, Lamp2 encodes a lysosomal protein (LAMP2) required to maintain the acidic environment in the lysosome and has been suggested to mediate autophagosome and lysosome fusion during autophagy (González-Polo et al., 2005). A decrease in LAMP2 would then affect the ability of neurons to use autophagy as a survival mechanism, which may then contribute to neuronal death (Nixon and Yang, 2012). However, the difference was not statistically significant (Fig. 5.5A). This may reflect biological variability between samples, which is not unexpected in experiments using primary cell cultures. Consequently, further repeats will be

required to circumvent this problem and statistically validate the microarray data by RT-PCR.

The GO enrichment analysis of the microarray data showed that the down- regulated genes also included the extracellular region (receptors and cell adhesion ECM proteins), as well as cytoskeletal proteins such actin and actin binging proteins. This observation provides confidence in the data analysis, since one of the most widely accepted and characterised functions of mTORC2 is the regulation of the actin cytoskeleton (Cybulski and Hall, 2009). This is particularly relevant in the case of the defect in dendritic arborisation observed after decreased Rictor expression (Urbanska et al., 2012).

With regards to up-regulated genes, an important up-regulation on cFos expression was observed following the loss of Sin1. This correlated with increased BDNF mRNA, consistent with previous demonstration that cFos transcriptionally regulates BDNF (Zhang et al., 2002). Considering, that the receptor for BDNF, namely Trk2 is down-regulated, it would be predicted that Sin1 ko neurons are not responsive to elevated BDNF production. This observation suggests that the Sin1/mTORC2 signalling pathway plays an important role in controlling the response of neurons to survival extracellular stimuli, hence the increased death of neurons lacking Sin1. In fact, eight down-regulated genes belong to the apoptotic cell death category (Biological Process). These included two potentially interesting anti-apoptotic genes namely, Egfr and Adam10. Egfr encodes the receptor for epidermal growth factor (EGFR), and although EGFR is not essential for cortical neuronal survival (Wagner et al., 2006), EGFR signalling has been linked to neurodegeneration and aging (Siddiqui et al., 2012). On the other hand, knockout of Adam10 in the brain has been reported to cause defects in neuronal cortical differentiation and impaired processing of the amyloid precursor protein APP implicated in Alzheimer's pathology (Jorissen et al., 2010). The observation that the 'apoptotic cell death' category was not significantly enriched in the analysis may be related to the overall low number of anti-apoptotic or pro-apoptotic genes assigned so far to this GO term, or due to their misclassification, since some genes can have anti or pro-apoptotic functions depending on the spliced variant. In fact, the lack of a more comprehensive database for the terms such as 'apoptosis' and 'cell survival' has already been discussed, since the one currently available (http://www.geneontology.org/) is not exhaustive. For instance, it does not include

many anti-apoptotic genes while many known anti-apoptotic genes are categorized as 'functionally unknown' (Portt et al., 2011).

At the moment no analysis of gene expression regulated by mTORC2 in neurons is available. Therefore, these results will contribute to increasing our knowledge about the genomic mechanisms downstream of mTORC2. A direct comparison amongst data obtained from other mTORC2-deficient neurons and the data obtained here will shed light into the mechanism behind the requirement of mTORC2 signalling for neuronal survival and other processes related to Akt signalling. However, it is important to consider that the expression of genes evaluated in this study represents only a time point after the loss of Sin1. In the future, kinetic studies are required to distinguish genes regulated as a direct or indirect consequence of Sin1 ablation. This information will be essential for initial modelling of the Sin1/mTORC2 signalling pathway in neurons.

Finally, since changes in gene expression do not necessarily correspond with changes in protein levels, the potential interesting down and up-regulated targets in Sin1 ko neurons need to be evaluated by immunoblot analysis.

The elucidation of the gene expression programme regulated by Sin1 and mTORC2 in neurons is an important step towards understanding and characterising this signalling pathway whose function in the brain has just begun to be elucidated, but that may provide important information and novel targets related to neurodegeneration and aging.

Discussion

The study of mechanisms controlling cell survival and cell death has received much attention since defects in both processes have been associated with the loss of neurons observed in acute and chronic neuropathological conditions. One of the interesting targets is the mTOR pathway since it controls a variety of PCD mechanisms implicated in these pathological conditions (Maiese, 2014). Moreover, due to its role in controlling various aspects of physiology, increasing the molecular understanding of the mechanisms by which mTOR regulates cell functions is critical to find potentially more suitable targets for developing new therapeutic strategies with reduced undesirable side effects. Based on its unique role in promoting Akt phosphorylation, specifically on Ser473, the scaffold Sin1 protein emerges as a very interesting candidate.

To characterise the biological function of the mTORC2/Akt pathway in more detail MEFs and cortical neurons from a novel CreER;Sin1F/F transgenic mouse line were generated. The results presented in this study have provided the first genetic demonstration that neurons depend on Sin1 for their survival. Similarly, it was demonstrated that Sin1 deficiency increased cell death in MEFs, via a caspase- independent mechanism. Together, these results support the idea that Sin1 constitutes a core component of mTOR-mediated cell survival (Oh and Jacinto, 2011). However, the results obtained using MEFs contrast with previous reports using the straight knockout models of Sin1 and Rictor (Guertin et al., 2006; Jacinto et al., 2006; Shiota et al., 2006). The survival of the Sin1-/- primary MEFs generated from the straight knockout mouse is not impaired, while they displayed increase susceptibility to stress-induced cell death (Jacinto et al., 2006). On the other hand, Rictor-/- MEFs used in the Shiota et al. study were immortalized and exhibit a slower growth rate which correlates with a defect in cell proliferation (Shiota et al., 2006). These differences could be explained by the possibility that Sin1-/- or Rictor-/- MEFs obtained from straight knockout models exhibit compensatory mechanisms that developed during embryogenesis. Additionally, in contrast to this study where primary MEFs were employed, the studies used immortalised fibroblasts (Shiota et al., 2006). Further studies aimed at examining the effect of conditional deletion of Sin1 in immortalised fibroblasts will be

important to determine the requirement of Sin1 in the survival of transformed cells under basal conditions and in response to genotoxic stress, hence predicting the suitability of Sin1 drug targets for cancer therapy.

It is also important to point out that the temporal disruption of gene function in primary cells using the CreER system constitutes a tractable approach to examine rapid changes in gene expression programmes that precede a pathological situation. Gene expression analysis in neurons suggested that Sin1 is important for regulating the expression of cell surface receptors, cytoskeletal proteins and transcription factors, to promote survival (Fig. 6.1). This information constitutes an important first step towards a better and broader understanding of the signalling mechanisms underlying neuronal survival.

Figure 6.1 Sin1 maintains neuronal survival Proposed model for the requirement of Sin1 to maintain neuronal survival. Sin1 is required for Akt phosphorylation, gene expression of transcription factors (TF) and growth factor receptors (GFR). The loss of Sin1 decreases the expression of GFR genes such as Ntrk2 (BDNF receptor). The decrease in cell surface receptors causes a decrease in cell survival even in the presence of survival signals.

The advantage of the inducible CreER system is also to enable temporal and tissue-specific gene deletion in adult animals, providing a time frame to carry out long-term experiments or acute treatments (Hayashi and McMahon, 2002). This is particular useful considering that Sin1 deletion causes early embryonic death (Jacinto et al., 2006). So far, the only study addressing the function of Sin1 in vivo

has been carried out by generating a chimeric model for the specific ablation of Sin1 in the haematopoietic system, where the loss of Sin1 increased the survival of pro-B cells (Lazorchak et al., 2010).

Another advantage of the conditional knockout approach is that it decreases the chances of compensatory mechanisms to occur in vivo, which may have been the source of conflicting findings obtained from the analyses of two brain-specific Rictor knockout systems using the same neuronal specific promoter (Nestin) (Siuta et al., 2010; Thomanetz et al., 2013). Siuta et al. reported that Rictor deficiency had not effect on brain size, but caused a specific defect in dopaminergic transmission in the adulthood. In contrast, Thomanetz et al. found that Rictor deletion decreased brain volume and neuronal size, while impairing synaptic transmission and motor behaviour (Thomanetz et al., 2013). The analysis of the effect of Sin1 deletion in the brain using a NestinCreER;Sin1F/F transgenic mouse model may help resolving this conflicting findings and will establish the functional significance of Sin1 in vivo. In particular, based on evidence that Sin1 is required for neuronal survival (this study), while Rictor may be dispensable for normal brain development (Siuta et al., 2010; Thomanetz et al., 2013), it would be very interesting to investigate the requirement of Sin1 in neurodegeneration. In fact, impairment in memory in the brain specific Rictor knockout has been reported (Huang et al., 2013). Another finding supporting the idea that Sin1 protects neurons against stress associated with neurological disorders is the demonstration of a role of mTOR and Akt in neurodegenerative conditions (Maiese, 2014), where changes in Akt phosphorylation have been reported to occur in Alzheimer's, Parkinson's and Huntintong's diseases (Rickle et al., 2004; Lipton and Sahin, 2014).

6.1 Future directions

The conditional knockout system in MEFs could be used in the future to study in more details the molecular mechanism underlying Sin1-dependent regulation of Akt function and cell survival. Previous work from the lab has shown that Sin1 can be phosphorylated at Ser510 in vitro by the uncoordinated-51 (UNC-51)-like kinase 1 (ULK1) (unpublished data). ULK1 is a downstream target of mTORC1 implicated in autophagy (Hosokawa et al., 2009). The role of Sin1 phosphorylation on Ser510 could be addressed by testing the ability of phosphomimetic and non- phosphorylatable Sin1 mutants to restore the viability of Sin1-deleted MEFs. Expression of the mutants in MEFs could be achieved using adenoviral vectors. This system would also provide a useful tool to examine the requirement of Sin1 phosphorylation in enabling mTORC2 to phosphorylate Akt and mediating the phosphorylation of downstream targets using proteomic approaches. Furthermore, the role of senescence as a mechanism responsible for decreasing the survival of Sin1-deleted MEFs could be further explored. In particular, based on the relationship between senescence and autophagy (Young et al., 2009; Young and Narita, 2010), it would be interesting to test whether autophagy is increased in the absence of Sin1. To accomplish this, MEFs can be transfected with a GFP-LC3 reporter to label and visualise autophagosomes. In addition, LC3 lipidation and p62 degradation can be monitored by immunoblot analyses. On the other hand, it remains to be established whether the lack of increased sensitivity of Sin1-deleted

MEFs to death is specific for H2O2 treatment or occurs with other stresses as well.

Future work in cortical neurons should focus on the role of Sin1 in activity- dependent neuroprotection as a potential mechanism to prevent neuronal death. Synaptic NMDA receptors can be stimulated with sub-lethal doses of NMDA and the number of apoptotic nuclei in control versus Sin1 ko neurons analysed. It will also be interesting to determine whether the loss of Sin1 affects action potentials or inhibitory or excitatory currents. The specific role of Sin1 phosphorylation in controlling these processes could be determined by expressing phosphomimetic and non-phosphorylatable Sin1 mutants in neurons using lentiviral vectors. Different Sin1 isoforms could also be transfected into neurons using a similar approach and their localisation and ability to interact with different components of mTOR complexes analysed by immunocytochemistry and immunoprecipitation, respectively.

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Appendix

A List of genes

Down-regulated genes

Ensembl ID Gene Title Gene Ratio Fold- log2Ratio p-value Symbol Change ENSMUSG00000007097 ATPase, Na+/K+ transporting, alpha 2 polypeptide Atp1a2 0.2496 -4.0058 -2.0021 0.00037 ENSMUSG00000005360 solute carrier family 1 (glial high affinity glutamate transporter), member 3 Slc1a3 0.2501 -3.9991 -1.9997 0.00042 ENSMUSG00000029231 platelet derived growth factor receptor, alpha polypeptide Pdgfra 0.2636 -3.7938 -1.9236 0.00002 ENSMUSG00000017390 aldolase C, fructose-bisphosphate Aldoc 0.3071 -3.2559 -1.7030 0.00004 ENSMUSG00000027962 vascular cell adhesion molecule 1 Vcam1 0.3088 -3.2379 -1.6951 0.00016 ENSMUSG00000050953 gap junction protein, alpha 1 Gja1 0.3143 -3.1822 -1.6700 0.00004 ENSMUSG00000030317 tissue inhibitor of metalloproteinase 4 Timp4 0.3167 -3.1576 -1.6588 0.00208 ENSMUSG00000062078 quaking Qk 0.3187 -3.1376 -1.6497 0.00083 ENSMUSG00000029309 SPARC-like 1 Sparcl1 0.3194 -3.1310 -1.6466 0.00005 ENSMUSG00000031342 glycoprotein m6b Gpm6b 0.3260 -3.0675 -1.6171 0.00003 ENSMUSG00000039830 oligodendrocyte transcription factor 2 Olig2 0.3267 -3.0608 -1.6139 0.00050 ENSMUSG00000074457 S100 calcium binding protein A16 S100a16 0.3335 -2.9983 -1.5841 0.00157 ENSMUSG00000068748 protein tyrosine phosphatase, receptor type Z, polypeptide 1 Ptprz1 0.3346 -2.9888 -1.5796 0.00005 ENSMUSG00000043496 TLR4 interactor with leucine-rich repeats Tril 0.3375 -2.9629 -1.5670 0.00079 ENSMUSG00000004892 brevican Bcan 0.3393 -2.9476 -1.5595 0.00005 ENSMUSG00000019874 fatty acid binding protein 7, brain Fabp7 0.3540 -2.8249 -1.4982 0.00065 ENSMUSG00000060961 solute carrier family 4 (anion exchanger), member 4 Slc4a4 0.3550 -2.8167 -1.4940 0.00019 ENSMUSG00000028517 phosphatidic acid phosphatase type 2B Ppap2b 0.3652 -2.7384 -1.4534 0.00007 ENSMUSG00000020733 solute carrier family 9 (sodium/hydrogen exchanger), member 3 regulator 1 Slc9a3r1 0.3787 -2.6407 -1.4009 0.00070 ENSMUSG00000022018 RIKEN cDNA 1190002H23 gene 1190002H23 0.3829 -2.6115 -1.3849 0.00113 Rik ENSMUSG00000032724 ankyrin repeat and BTB (POZ) domain containing 2 Abtb2 0.3852 -2.5961 -1.3763 0.00180 ENSMUSG00000030088 aldehyde dehydrogenase 1 family, member L1 Aldh1l1 0.3913 -2.5553 -1.3535 0.00007 ENSMUSG00000046160 oligodendrocyte transcription factor 1 Olig1 0.3921 -2.5506 -1.3508 0.00017 ENSMUSG00000030428 tweety homolog 1 (Drosophila) Ttyh1 0.3948 -2.5331 -1.3409 0.00048 ENSMUSG00000039194 retinaldehyde binding protein 1 Rlbp1 0.4011 -2.4930 -1.3179 0.00009 ENSMUSG00000020649 ribonucleotide reductase M2 Rrm2 0.4015 -2.4904 -1.3164 0.00018 ENSMUSG00000030029 leucine-rich repeats and immunoglobulin-like domains 1 Lrig1 0.4021 -2.4868 -1.3143 0.00095 ENSMUSG00000024411 aquaporin 4 Aqp4 0.4050 -2.4690 -1.3039 0.00332 ENSMUSG00000022122 endothelin receptor type B Ednrb 0.4139 -2.4160 -1.2726 0.00009 ENSMUSG00000037815 catenin (cadherin associated protein), alpha 1 Ctnna1 0.4186 -2.3892 -1.2565 0.00057 ENSMUSG00000019873 receptor accessory protein 3 Reep3 0.4247 -2.3544 -1.2353 0.00125 ENSMUSG00000026385 diazepam binding inhibitor Dbi 0.4322 -2.3137 -1.2102 0.00032 ENSMUSG00000006205 HtrA serine peptidase 1 Htra1 0.4339 -2.3047 -1.2046 0.00172 ENSMUSG00000026728 vimentin Vim 0.4344 -2.3021 -1.2029 0.00018 ENSMUSG00000053931 calponin 3, acidic Cnn3 0.4388 -2.2788 -1.1883 0.00081 ENSMUSG00000000184 cyclin D2 Ccnd2 0.4463 -2.2406 -1.1639 0.00014 ENSMUSG00000030307 solute carrier family 6 (neurotransmitter transporter, GABA), member 11 Slc6a11 0.4473 -2.2358 -1.1608 0.00334 ENSMUSG00000023913 phospholipase A2, group VII (platelet-activating factor acetylhydrolase, plasma) Pla2g7 0.4498 -2.2233 -1.1527 0.00189 ENSMUSG00000031762 metallothionein 2 Mt2 0.4526 -2.2096 -1.1438 0.00015 ENSMUSG00000070436 serine (or cysteine) peptidase inhibitor, clade H, member 1 Serpinh1 0.4529 -2.2078 -1.1426 0.00016 ENSMUSG00000018593 secreted acidic cysteine rich glycoprotein Sparc 0.4560 -2.1932 -1.1330 0.00055 ENSMUSG00000024654 asparaginase like 1 Asrgl1 0.4577 -2.1850 -1.1277 0.00143 ENSMUSG00000019942 cyclin-dependent kinase 1 Cdk1 0.4602 -2.1732 -1.1198 0.00019 ENSMUSG00000052397 ezrin Ezr 0.4639 -2.1557 -1.1082 0.00041 ENSMUSG00000058135 glutathione S-transferase, mu 1 Gstm1 0.4644 -2.1533 -1.1065 0.00017 ENSMUSG00000038156 spondin 1, (f-spondin) extracellular matrix protein Spon1 0.4693 -2.1307 -1.0913 0.00076 ENSMUSG00000039323 insulin-like growth factor binding protein 2 Igfbp2 0.4699 -2.1279 -1.0894 0.00019 ENSMUSG00000067279 protein phosphatase 1, regulatory (inhibitor) subunit 3C Ppp1r3c 0.4752 -2.1044 -1.0734 0.00883 ENSMUSG00000074637 SRY-box containing gene 2 Sox2 0.4763 -2.0993 -1.0699 0.00034 ENSMUSG00000055254 neurotrophic tyrosine kinase, receptor, type 2 Ntrk2 0.4807 -2.0801 -1.0566 0.00040 ENSMUSG00000037071 stearoyl-Coenzyme A desaturase 1 Scd1 0.4848 -2.0625 -1.0444 0.00235 ENSMUSG00000054252 fibroblast growth factor receptor 3 Fgfr3 0.4850 -2.0619 -1.0439 0.00064 ENSMUSG00000034648 leucine rich repeat protein 1, neuronal Lrrn1 0.4877 -2.0505 -1.0360 0.00039 ENSMUSG00000041688 angiomotin Amot 0.4887 -2.0463 -1.0330 0.00033 ENSMUSG00000025931 progestin and adipoQ receptor family member VIII Paqr8 0.4921 -2.0319 -1.0228 0.00023 ENSMUSG00000022817 integrin beta 5 Itgb5 0.4936 -2.0260 -1.0186 0.00038 ENSMUSG00000047557 latexin Lxn 0.4944 -2.0228 -1.0164 0.00022 ENSMUSG00000026249 serine (or cysteine) peptidase inhibitor, clade E, member 2 Serpine2 0.4962 -2.0152 -1.0109 0.00074 ENSMUSG00000015243 ATP-binding cassette, sub-family A (ABC1), member 1 Abca1 0.4990 -2.0040 -1.0029 0.00024 ENSMUSG00000027984 hydroxyacyl-Coenzyme A dehydrogenase Hadh 0.5004 -1.9984 -0.9988 0.00035 ENSMUSG00000044708 potassium inwardly-rectifying channel, subfamily J, member 10 Kcnj10 0.5036 -1.9858 -0.9897 0.00032 ENSMUSG00000027419 proprotein convertase subtilisin/kexin type 2 Pcsk2 0.5064 -1.9749 -0.9817 0.00082 ENSMUSG00000021720 ring finger protein 180 Rnf180 0.5069 -1.9730 -0.9804 0.00413 ENSMUSG00000004558 N-myc downstream regulated gene 2 Ndrg2 0.5078 -1.9692 -0.9776 0.00150 ENSMUSG00000028820 splicing factor proline/glutamine rich (polypyrimidine tract binding protein Sfpq 0.5083 -1.9673 -0.9762 0.00171 associated) ENSMUSG00000008540 microsomal glutathione S-transferase 1 Mgst1 0.5092 -1.9637 -0.9736 0.00352 ENSMUSG00000030235 solute carrier organic anion transporter family, member 1c1 Slco1c1 0.5102 -1.9600 -0.9708 0.00027 ENSMUSG00000032035 E26 avian leukemia oncogene 1, 5' domain Ets1 0.5105 -1.9587 -0.9699 0.00107 ENSMUSG00000030342 CD9 antigen Cd9 0.5114 -1.9553 -0.9674 0.00131

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Ensembl ID Gene Title Gene Ratio Fold- log2Ratio p-value Symbol Change ENSMUSG00000035805 megalencephalic leukoencephalopathy with subcortical cysts 1 homolog Mlc1 0.5117 -1.9542 -0.9666 0.00057 (human) ENSMUSG00000027087 integrin alpha V Itgav 0.5176 -1.9318 -0.9500 0.00637 ENSMUSG00000003623 carnitine O-octanoyltransferase Crot 0.5230 -1.9121 -0.9352 0.00091 ENSMUSG00000026473 glutamate-ammonia ligase (glutamine synthetase) Glul 0.5231 -1.9118 -0.9349 0.00214 ENSMUSG00000002688 protein kinase D1 Prkd1 0.5240 -1.9084 -0.9323 0.00037 ENSMUSG00000026923 notch 1 Notch1 0.5242 -1.9076 -0.9318 0.00104 ENSMUSG00000026355 minichromosome maintenance deficient 6 (MIS5 homolog, S. pombe) (S. Mcm6 0.5282 -1.8933 -0.9209 0.00197 cerevisiae) ENSMUSG00000021466 patched homolog 1 Ptch1 0.5296 -1.8884 -0.9171 0.00123 ENSMUSG00000029778 adenylate cyclase activating polypeptide 1 receptor 1 Adcyap1r1 0.5331 -1.8757 -0.9074 0.00052 ENSMUSG00000021703 serine incorporator 5 Serinc5 0.5332 -1.8756 -0.9074 0.00052 ENSMUSG00000002341 neurocan Ncan 0.5340 -1.8726 -0.9051 0.00116 ENSMUSG00000020263 adaptor protein, phosphotyrosine interaction, PH domain and leucine zipper Appl2 0.5341 -1.8724 -0.9049 0.00134 containing 2 ENSMUSG00000046240 hepatocyte cell adhesion molecule Hepacam 0.5370 -1.8622 -0.8970 0.00050 ENSMUSG00000027878 notch 2 Notch2 0.5404 -1.8505 -0.8879 0.00049 ENSMUSG00000020023 transmembrane and coiled coil domains 3 Tmcc3 0.5436 -1.8396 -0.8794 0.00507 ENSMUSG00000024420 zinc finger protein 521 Zfp521 0.5499 -1.8186 -0.8628 0.00269 ENSMUSG00000029723 TSC22 domain family, member 4 Tsc22d4 0.5499 -1.8186 -0.8628 0.00044 ENSMUSG00000020282 rhomboid family 1 (Drosophila) Rhbdf1 0.5519 -1.8120 -0.8575 0.00832 ENSMUSG00000078135 EP300 interacting inhibitor of differentiation 1 Eid1 0.5546 -1.8030 -0.8504 0.00065 ENSMUSG00000091337 ENSMUSG00000091461 RIKEN cDNA 2210008F06 gene 2210008F06 0.5554 -1.8004 -0.8483 0.00188 Rik ENSMUSG00000032434 CKLF-like MARVEL transmembrane domain containing 6 Cmtm6 0.5577 -1.7930 -0.8424 0.00086 ENSMUSG00000062014 glia maturation factor, beta Gmfb 0.5579 -1.7926 -0.8420 0.00158 ENSMUSG00000040028 ELAV (embryonic lethal, abnormal vision)-like 1 (Hu antigen R) Elavl1 0.5590 -1.7889 -0.8390 0.00048 ENSMUSG00000024070 protein kinase D3 Prkd3 0.5605 -1.7842 -0.8352 0.00163 ENSMUSG00000039533 monocyte to macrophage differentiation-associated 2 Mmd2 0.5614 -1.7811 -0.8328 0.00049 ENSMUSG00000002475 abhydrolase domain containing 3 Abhd3 0.5615 -1.7808 -0.8325 0.00145 ENSMUSG00000039621 phosphatidylinositol-3,4,5-trisphosphate-dependent Rac exchange factor 1 Prex1 0.5617 -1.7802 -0.8320 0.00066 ENSMUSG00000028273 PDZ and LIM domain 5 Pdlim5 0.5618 -1.7799 -0.8318 0.00053 ENSMUSG00000039835 NHS-like 1 Nhsl1 0.5636 -1.7742 -0.8272 0.00052 ENSMUSG00000022816 follistatin-like 1 Fstl1 0.5637 -1.7740 -0.8270 0.00052 ENSMUSG00000008734 G protein-coupled receptor, family C, group 5, member B Gprc5b 0.5642 -1.7726 -0.8258 0.00447 ENSMUSG00000020914 topoisomerase (DNA) II alpha Top2a 0.5652 -1.7693 -0.8232 0.00077 ENSMUSG00000030557 myocyte enhancer factor 2A Mef2a 0.5658 -1.7674 -0.8216 0.00095 ENSMUSG00000060548 tumor necrosis factor receptor superfamily, member 19 Tnfrsf19 0.5675 -1.7622 -0.8174 0.00076 ENSMUSG00000053062 junction adhesion molecule 2 Jam2 0.5687 -1.7585 -0.8144 0.00165 ENSMUSG00000024593 multiple EGF-like-domains 10 Megf10 0.5700 -1.7544 -0.8110 0.00054 ENSMUSG00000032816 immunoglobulin superfamily, DCC subclass, member 4 Igdcc4 0.6277 -1.5931 -0.6718 0.00118 ENSMUSG00000004980 heterogeneous nuclear ribonucleoprotein A2/B1 /// heterogeneous nuclear Hnrnpa2b1 0.5711 -1.7509 -0.8081 0.00072 ribonucleoproteins A2/B1-like ENSMUSG00000042745 inhibitor of DNA binding 1 Id1 0.5715 -1.7498 -0.8072 0.00506 ENSMUSG00000024048 myosin, light chain 12A, regulatory, non-sarcomeric Myl12a 0.5765 -1.7346 -0.7946 0.00214 ENSMUSG00000041126 H2A histone family, member V H2afv 0.5767 -1.7339 -0.7940 0.00097 ENSMUSG00000086503 inactive X specific transcripts Xist 0.5768 -1.7336 -0.7938 0.00062 ENSMUSG00000022491 glycosylation dependent cell adhesion molecule 1 Glycam1 0.5778 -1.7306 -0.7913 0.00108 ENSMUSG00000013275 solute carrier family 41, member 1 Slc41a1 0.5783 -1.7293 -0.7902 0.00305 ENSMUSG00000037857 nuclear fragile X mental retardation protein interacting protein 2 Nufip2 0.5788 -1.7277 -0.7888 0.00594 ENSMUSG00000031610 scrapie responsive gene 1 Scrg1 0.5809 -1.7216 -0.7838 0.04910 ENSMUSG00000038080 lysine (K)-specific demethylase 1B Kdm1b 0.5811 -1.7210 -0.7832 0.00120 ENSMUSG00000038248 sine oculis-binding protein homolog (Drosophila) Sobp 0.5832 -1.7146 -0.7779 0.00065 ENSMUSG00000022899 solute carrier family 15 (H+/peptide transporter), member 2 Slc15a2 0.5858 -1.7072 -0.7716 0.00296 ENSMUSG00000028199 crystallin, zeta Cryz 0.5861 -1.7063 -0.7708 0.00073 ENSMUSG00000027187 catalase Cat 0.5861 -1.7061 -0.7707 0.00662 ENSMUSG00000072949 acyl-CoA thioesterase 1 Acot1 0.5869 -1.7039 -0.7688 0.00316 ENSMUSG00000055717 SLAIN motif family, member 1 Slain1 0.5882 -1.7000 -0.7656 0.00068 ENSMUSG00000032562 guanine nucleotide binding protein (G protein), alpha inhibiting 2 Gnai2 0.5889 -1.6982 -0.7640 0.00266 ENSMUSG00000028128 coagulation factor III F3 0.5894 -1.6965 -0.7626 0.00602 ENSMUSG00000060206 zinc finger protein 462 Zfp462 0.5925 -1.6878 -0.7551 0.00088 ENSMUSG00000063632 SRY-box containing gene 11 Sox11 0.5939 -1.6839 -0.7518 0.00172 ENSMUSG00000029730 minichromosome maintenance deficient 7 (S. cerevisiae) Mcm7 0.5940 -1.6834 -0.7514 0.00081 ENSMUSG00000034349 structural maintenance of chromosomes 4 Smc4 0.5960 -1.6779 -0.7467 0.00119 ENSMUSG00000021127 zinc finger protein 36, C3H type-like 1 Zfp36l1 0.5961 -1.6775 -0.7463 0.01952 ENSMUSG00000020122 epidermal growth factor receptor Egfr 0.5978 -1.6729 -0.7424 0.00333 ENSMUSG00000021846 pellino 2 Peli2 0.5985 -1.6709 -0.7407 0.00195 ENSMUSG00000037712 fermitin family homolog 2 (Drosophila) Fermt2 0.5985 -1.6709 -0.7406 0.00095 ENSMUSG00000051920 R-spondin 2 homolog (Xenopus laevis) Rspo2 0.5997 -1.6674 -0.7376 0.03246 ENSMUSG00000024639 guanine nucleotide binding protein, alpha q polypeptide Gnaq 0.6004 -1.6656 -0.7361 0.00149 ENSMUSG00000027981 amylase 1, salivary /// RNA-binding region (RNP1, RRM) containing 3 Amy1 /// 0.6007 -1.6647 -0.7353 0.00354 ENSMUSG00000074264 Rnpc3 ENSMUSG00000070348 cyclin D1 Ccnd1 0.6012 -1.6634 -0.7342 0.00158 ENSMUSG00000029178 Kruppel-like factor 3 (basic) Klf3 0.6022 -1.6607 -0.7318 0.00083 ENSMUSG00000002274 meteorin, glial cell differentiation regulator Metrn 0.6045 -1.6544 -0.7263 0.00231 ENSMUSG00000052727 microtubule-associated protein 1B Mtap1b 0.6076 -1.6459 -0.7189 0.00137 ENSMUSG00000007872 inhibitor of DNA binding 3 Id3 0.6081 -1.6444 -0.7176 0.00819 ENSMUSG00000046743 FAT tumor suppressor homolog 4 (Drosophila) Fat4 0.6091 -1.6417 -0.7152 0.00287 ENSMUSG00000005973 reticulocalbin 1 Rcn1 0.6095 -1.6406 -0.7143 0.00255 ENSMUSG00000030111 alpha-2-macroglobulin A2m 0.6106 -1.6377 -0.7117 0.00545

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Ensembl ID Gene Title Gene Ratio Fold- log2Ratio p-value Symbol Change ENSMUSG00000062352 integrin beta 1 binding protein 1 Itgb1bp1 0.6107 -1.6374 -0.7114 0.00900 ENSMUSG00000022500 LPS-induced TN factor Litaf 0.6110 -1.6366 -0.7107 0.01811 ENSMUSG00000006728 cyclin-dependent kinase 4 /// cyclin-dependent kinase 4-like Cdk4 0.6133 -1.6305 -0.7053 0.00094 ENSMUSG00000021379 inhibitor of DNA binding 4 Id4 0.6143 -1.6278 -0.7029 0.00106 ENSMUSG00000038252 non-SMC condensin I complex, subunit D2 Ncapd2 0.6152 -1.6255 -0.7009 0.01247 ENSMUSG00000054717 high mobility group box 2 Hmgb2 0.6161 -1.6231 -0.6987 0.00158 ENSMUSG00000027447 cystatin C Cst3 0.6172 -1.6203 -0.6963 0.00112 ENSMUSG00000027111 integrin alpha 6 Itga6 0.6177 -1.6190 -0.6951 0.00130 ENSMUSG00000031004 antigen identified by monoclonal antibody Ki 67 Mki67 0.6183 -1.6174 -0.6937 0.00129 ENSMUSG00000030255 sarcospan Sspn 0.6187 -1.6162 -0.6926 0.00199 ENSMUSG00000027199 glycine amidinotransferase (L-arginine:glycine amidinotransferase) Gatm 0.6199 -1.6132 -0.6899 0.00134 ENSMUSG00000022322 Shc SH2-domain binding protein 1 Shcbp1 0.6209 -1.6106 -0.6876 0.00105 ENSMUSG00000015305 SAM and SH3 domain containing 1 Sash1 0.6219 -1.6079 -0.6852 0.01346 ENSMUSG00000030538 calcium and integrin binding 1 (calmyrin) Cib1 0.6220 -1.6078 -0.6851 0.00270 ENSMUSG00000034701 neurogenic differentiation 1 Neurod1 0.6232 -1.6048 -0.6823 0.00546 ENSMUSG00000025959 Kruppel-like factor 7 (ubiquitous) Klf7 0.6243 -1.6018 -0.6797 0.00122 ENSMUSG00000029838 pleiotrophin Ptn 0.6246 -1.6009 -0.6789 0.00122 ENSMUSG00000033624 pyruvate dehydrogenase phosphatase regulatory subunit Pdpr 0.6250 -1.5999 -0.6780 0.00218 ENSMUSG00000037465 Kruppel-like factor 10 Klf10 0.6263 -1.5968 -0.6752 0.01113 ENSMUSG00000033577 myosin VI Myo6 0.5717 -1.7493 -0.8068 0.00445 ENSMUSG00000021871 purine-nucleoside phosphorylase Pnp 0.6278 -1.5929 -0.6717 0.00118 ENSMUSG00000032849 ATP-binding cassette, sub-family C (CFTR/MRP), member 4 Abcc4 0.6280 -1.5924 -0.6712 0.00243 ENSMUSG00000016534 lysosomal-associated membrane protein 2 Lamp2 0.6293 -1.5891 -0.6682 0.00118 ENSMUSG00000028955 vesicle-associated membrane protein 3 Vamp3 0.6295 -1.5886 -0.6677 0.00532 ENSMUSG00000009418 neuron navigator 1 Nav1 0.6296 -1.5884 -0.6675 0.00185 ENSMUSG00000029687 enhancer of zeste homolog 2 (Drosophila) Ezh2 0.6298 -1.5878 -0.6670 0.00161 ENSMUSG00000028782 brain-specific angiogenesis inhibitor 2 Bai2 0.6299 -1.5876 -0.6668 0.01271 ENSMUSG00000013698 phosphoprotein enriched in astrocytes 15A Pea15a 0.6304 -1.5863 -0.6657 0.00149 ENSMUSG00000024665 fatty acid desaturase 2 Fads2 0.6306 -1.5857 -0.6651 0.00251 ENSMUSG00000019818 CD164 antigen Cd164 0.6329 -1.5801 -0.6600 0.00145 ENSMUSG00000020644 inhibitor of DNA binding 2 Id2 0.6342 -1.5768 -0.6570 0.00800 ENSMUSG00000040234 transmembrane 7 superfamily member 3 Tm7sf3 0.6346 -1.5758 -0.6561 0.00290 ENSMUSG00000024238 zinc finger E-box binding homeobox 1 Zeb1 0.6353 -1.5740 -0.6545 0.02458 ENSMUSG00000001911 nuclear factor I/X Nfix 0.6361 -1.5722 -0.6527 0.00273 ENSMUSG00000024302 dystrobrevin alpha Dtna 0.6363 -1.5715 -0.6522 0.00126 ENSMUSG00000034109 golgi integral membrane protein 4 Golim4 0.6364 -1.5714 -0.6521 0.03695 ENSMUSG00000024782 adenylate kinase 3 Ak3 0.6377 -1.5682 -0.6491 0.00128 ENSMUSG00000028675 proline-rich nuclear receptor coactivator 2 Pnrc2 0.6378 -1.5679 -0.6488 0.00451 ENSMUSG00000024998 phospholipase C, epsilon 1 Plce1 0.6383 -1.5667 -0.6477 0.00897 ENSMUSG00000040025 YTH domain family 2 Ythdf2 0.6390 -1.5648 -0.6460 0.00255 ENSMUSG00000033781 ankyrin repeat and SOCS box-containing 13 Asb13 0.6353 -1.5740 -0.6545 0.00784 ENSMUSG00000021417 enoyl-Coenzyme A delta isomerase 2 Eci2 0.6393 -1.5643 -0.6455 0.00133 ENSMUSG00000034714 protein tweety homolog 2-like /// tweety homolog 2 (Drosophila) Ttyh2 0.6396 -1.5634 -0.6447 0.00247 ENSMUSG00000030605 milk fat globule-EGF factor 8 protein Mfge8 0.6415 -1.5589 -0.6406 0.01087 ENSMUSG00000028034 far upstream element (FUSE) binding protein 1 Fubp1 0.6421 -1.5573 -0.6390 0.00191 ENSMUSG00000048490 nuclear receptor interacting protein 1 Nrip1 0.6426 -1.5563 -0.6381 0.00523 ENSMUSG00000022272 myosin X Myo10 0.6457 -1.5488 -0.6312 0.00165 ENSMUSG00000026843 far upstream element (FUSE) binding protein 3 Fubp3 0.6459 -1.5483 -0.6306 0.00249 ENSMUSG00000020935 kinesin-associated protein 3 Kifap3 0.6400 -1.5625 -0.6439 0.00151 ENSMUSG00000031714 post-GPI attachment to proteins 2 Pgap2 0.6403 -1.5618 -0.6432 0.00214 ENSMUSG00000015222 CD44 antigen Cd44 0.6404 -1.5614 -0.6429 0.00173 ENSMUSG00000045205 epoxide hydrolase 1, microsomal Ephx1 0.6410 -1.5601 -0.6417 0.00235 ENSMUSG00000039982 deltex 4 homolog (Drosophila) Dtx4 0.6472 -1.5452 -0.6278 0.00172 ENSMUSG00000008575 nuclear factor I/B Nfib 0.6478 -1.5437 -0.6264 0.01214 ENSMUSG00000046922 G protein-coupled receptor 6 Gpr6 0.6481 -1.5431 -0.6258 0.00151 ENSMUSG00000031760 metallothionein 3 Mt3 0.6482 -1.5426 -0.6254 0.00158 ENSMUSG00000028312 structural maintenance of chromosomes 2 Smc2 0.6494 -1.5398 -0.6228 0.00289 ENSMUSG00000015839 nuclear factor, erythroid derived 2, like 2 Nfe2l2 0.6501 -1.5382 -0.6212 0.03851 ENSMUSG00000029840 myotrophin Mtpn 0.6502 -1.5381 -0.6212 0.00190 ENSMUSG00000041685 FCH domain only 2 Fcho2 0.6507 -1.5368 -0.6199 0.01909 ENSMUSG00000038128 calcium/calmodulin-dependent protein kinase IV Camk4 0.6513 -1.5353 -0.6185 0.01782 ENSMUSG00000051379 fibronectin leucine rich transmembrane protein 3 Flrt3 0.6513 -1.5353 -0.6185 0.00217 ENSMUSG00000027884 chloride channel CLIC-like 1 Clcc1 0.6521 -1.5334 -0.6168 0.00807 ENSMUSG00000040481 bromodomain PHD finger transcription factor Bptf 0.6524 -1.5327 -0.6161 0.00162 ENSMUSG00000034317 tripartite motif-containing 59 Trim59 0.6526 -1.5324 -0.6158 0.01330 ENSMUSG00000031232 magnesium transporter 1 Magt1 0.6537 -1.5297 -0.6132 0.01243 ENSMUSG00000040759 CKLF-like MARVEL transmembrane domain containing 5 Cmtm5 0.6540 -1.5292 -0.6127 0.00771 ENSMUSG00000044477 zinc finger, AN1-type domain 3 Zfand3 0.6540 -1.5290 -0.6126 0.00283 ENSMUSG00000019923 ZW10 interactor Zwint 0.6542 -1.5285 -0.6122 0.04536 ENSMUSG00000026207 SPEG complex locus Speg 0.6544 -1.5281 -0.6117 0.00351 ENSMUSG00000021010 neuronal PAS domain protein 3 Npas3 0.6548 -1.5272 -0.6108 0.00211 ENSMUSG00000001036 epsin 2 Epn2 0.6555 -1.5256 -0.6094 0.00434 ENSMUSG00000035642 RIKEN cDNA 1810020D17 gene 1810020D17 0.6556 -1.5253 -0.6091 0.01144 Rik ENSMUSG00000001403 ubiquitin-conjugating enzyme E2C Ube2c 0.6565 -1.5232 -0.6071 0.00636 ENSMUSG00000030970 C-terminal binding protein 2 Ctbp2 0.6576 -1.5206 -0.6047 0.00196 ENSMUSG00000053907 methionine adenosyltransferase II, alpha Mat2a 0.6578 -1.5201 -0.6042 0.00169 ENSMUSG00000021794 glutamate dehydrogenase 1 Glud1 0.6600 -1.5151 -0.5994 0.00262 ENSMUSG00000033022 cysteine dioxygenase 1, cytosolic Cdo1 0.6600 -1.5151 -0.5994 0.02978 ENSMUSG00000024501 dihydropyrimidinase-like 3 Dpysl3 0.6603 -1.5145 -0.5988 0.00488

114

Ensembl ID Gene Title Gene Ratio Fold- log2Ratio p-value Symbol Change ENSMUSG00000054693 a disintegrin and metallopeptidase domain 10 Adam10 0.6603 -1.5145 -0.5988 0.00200 ENSMUSG00000018398 septin 8 Sept8 0.6615 -1.5116 -0.5961 0.00382 ENSMUSG00000074749 polo-like kinase 1 substrate 1 Plk1s1 0.6625 -1.5095 -0.5941 0.01019 ENSMUSG00000037725 cytoskeleton associated protein 2 Ckap2 0.6632 -1.5078 -0.5924 0.00644 ENSMUSG00000047832 cell division cycle associated 4 Cdca4 0.6633 -1.5076 -0.5922 0.00186 ENSMUSG00000060371 calneuron 1 Caln1 0.6635 -1.5072 -0.5918 0.02220 ENSMUSG00000027365 transient receptor potential cation channel, subfamily M, member 7 Trpm7 0.6637 -1.5066 -0.5913 0.00831 ENSMUSG00000044066 centrosomal protein 68 Cep68 0.6639 -1.5062 -0.5909 0.00415

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Up-regulated genes

Ensembl ID Gene Title Gene Ratio Fold- log2Ratio p-value Symbol Change ENSMUSG00000017978 Ca2+-dependent activator protein for secretion 2 Cadps2 1.498 1.498 0.583 0.002 ENSMUSG00000027313 ChaC, cation transport regulator 1 Chac1 1.498 1.498 0.583 0.005 ENSMUSG00000024256 adenylate cyclase activating polypeptide 1 Adcyap1 1.627 1.627 0.702 0.060 ENSMUSG00000023034 nuclear receptor subfamily 4, group A, member 1 Nr4a1 1.527 1.527 0.610 0.015 ENSMUSG00000037428 VGF nerve growth factor inducible Vgf 1.820 1.820 0.864 0.161 ENSMUSG00000021453 growth arrest and DNA-damage-inducible 45 gamma Gadd45g 1.843 1.843 0.882 0.163 ENSMUSG00000048482 brain derived neurotrophic factor Bdnf 2.018 2.018 1.013 0.183 ENSMUSG00000045903 neuronal PAS domain protein 4 Npas4 2.137 2.137 1.095 0.207 ENSMUSG00000026360 regulator of G-protein signaling 2 Rgs2 2.149 2.149 1.104 0.214 ENSMUSG00000021250 FBJ osteosarcoma oncogene Fos 2.849 2.849 1.510 0.405

Ratio/fold/log2 ko vs wt p_value paired

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B Primer efficiency

Table 6 Primer efficiency

Figure Appendix. Primer efficiency slopes Primer efficiency was determined in wt cortical neurons using increasing concentrations of cDNA. The slope values are shown in Table 6, and were used to calculate the efficiency.

117