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A functional genomics approach identifies novel genes involved in steroid-hormove induced programmed… Chittaranjan, Suganthi 2008

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A functional genomics approach identifies novel genes involved in steroid-hormone induced programmed cell death in Drosophila by SUGANTHI CHITTARANJAN B.Sc., Eastern University of SriLanka, 1985 M.P.M., Simon Fraser University, 2002 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Genetics) THE UNIVERSITY OF BRITISH COLUMBIA April 2008 © Suganthi Chittaranjan, 2008 ABSTRACT Programmed Cell death (PCD) is a highly conserved and genetically controlled event that plays important roles in animal development, homeostasis and disease. Our first objective was to discover and characterize new genes involved in PCD. Since many PCD genes are conserved in Drosophila, and steroid-induced PCD of larval salivary glands (SGs) is transcriptionally regulated with features of both apoptosis and autophagy, we used this exceptionally well-suited in vivo system and performed Serial Analysis of Gene Expression (SAGE) in three pre-death stages. SAGE identified 1244 expressed transcripts, including genes involved in autophagy, apoptosis, immunity, cytoskeleton remodeling, and proteolysis. Of the 1244 transcripts, 463 transcripts belonged to knownlpredicted genes and were 5-fold differentially expressed prior to cell death. Next, we investigated the role of differentially expressed genes from SAGE, in cell death or cell survival, by RNA interference (RNAi ) in l(2)mbn haemocyte Drosophila cells. l(2)mbn cells undergo morphological changes in response to ecdysone treatment, and ultimately undergo PCD. We used cell viability, cell morphology, and apoptosis assays to identify the death-related genes and determined their ecdysone dependency and function in cell death regulation. Our RNAi screen identified six new pro-death related genes, including SH3PXJ and Soxl4, and 21 new pro-survival genes including SoxN. Identification of Soxl4 as pro-death and SoxN as pro-survival suggests that these Sox box proteins may have opposing roles in ecdysone-mediated cell death. Our final objective was to elucidate the function of CG409], a Drosophila homologue of human TNF-alpha induced proteins 8 (TNFAIP8) we identified from SAGE. We created loss-of-function and overexpression mutants of CG4091 to study 11 gene function in vivo and employed immunoprecipitation and mass-spectrometry assays to identify proteins interacting with CG409] in vitro. We identified two proteins that are involved in n-fatty acid oxidation and several cytoskeletal proteins as interaction partners. Immunofluorescence based assays in vivo and in vitro revealed that CG409] is necessary for cytoskeletal remodeling. Further, defects in CG4091 expression affect cellular functions such as autophagy and lipid metabolism/trafficking that require an intact cytoskeleton. Together, our studies provided new insights into the molecular mechanisms involved in Drosophila SG cell death. 111 TABLE OF CONTENTS ABSTRACT .ii TABLE OF CONTENTS iv LIST OF TABLES vii LIST OF FIGURES viii LIST OF ABBREVIATIONS ix ACKNOWLEDGMENTS x CO-AUTHORSHIP STATEMENT xii CHAPTER 1. INTRODUCTION 1 1.1 FUNCTIONAL GENOMICS 1 1.2 PROGRAMMED CELL DEATH 1.3 APOPTOSIS 2 1.3.1 Biochemical and molecular signals in apoptosis 2 1.3.2 Apoptosis and diseases 3 1.4 AUTOPHAGY AND AUTOPHAGIC CELL DEATH 7 1.4.1 Background 7 1.4.2 Function and regulation of autophagy proteins 8 1.5 PROGRAMMED CELL DEATH IN DROSOPHILA DEVELOPMENT 13 1.6 STEROID-TRIGGERED AUTOPHAGIC CELL DEATH IN DROSOPHILA LARVAL SALIVARY GLANDS 14 1.7 GENE EXPRESSION PROFILING AND THE SAGE METHOD 15 1.8 THESIS RATIONAL, OBJECTIVES AND HYPOTHESES 18 1.8.1 Overall objectives 19 1.8.2 Objective 1 19 1.8.2.1 Rationale 19 1.8.2.2 Hypothesis 19 1.8.2.3 Summary research plan 20 1.8.3 Objective 2 20 1.8.7.3.1 Rationale 20 1.8.3.2 Hypothesis 20 1.8.3.3 Summary research plan 20 1.8.4 Objective 3 21 1.8.4.1 Rationale 21 1.8.4.2 Hypotheses 21 1.8.4.3 Summary research plan 21 1.9 REFERENCES 23 CHAPTER 2. A SAGE APPROACH TO DISCOVERY OF GENES INVOLVED IN AUTOPHAGIC CELL DEATH 37 2.1 INTRODUCTION 37 2.2 MATERIALS AND METHODS 39 2.2.1 Fly strains 39 2.2.2 Tissue dissection and RNA preparation 39 2.2.3 cDNA library construction and EST sequencing 39 2.2.4 EST Clustering 40 2.2.5 SAGE 41 2.2.6. Tag-to-gene mapping in Drosophila 42 2.2.7 Real-time RT-PCR 42 2.2.8 Atg-Iike genes 43 2.3 RESULTS 44 2.3.1 Tissue-specific Genome-wide Expression 44 iv 2.3.2 Tissue-specific ESTS .•:..44 2.3.3 SAGE Identifies Novel Transcripts in Drosophila. ... 45 2.3.4 Verification of SAGE data by real-time quantitative RT-PCR 46 2.3.5 SAGE identifies genes associated previously with salivary gland death 47 2.3.6 Many genes not associated previously with salivary gland PCD are differentially expressed. .50 2.3.7 Mutant analysis identifies E93 regulated genes in salivary gland cell death 57 2.4 DISCuSSION 61 2.5 REFERENCES 64 CHAPTER 3. STEROID HORMONE CONTROL OF CELL DEATH AND CELL SURVIVAL: MOLECULAR INSIGHTS USING RNA1 70 3.1 INTRODUCTION 70 3.2 MATERIALS AND METHODS 73 3.2.1.DSRNA DESIGN AND SYNTHESIS 73 3.2.2 Cell culture and ecdysone treatment 76 3.2.3 Quantitative RT-PCR 76 3.2.4 RNA interference (RNAi) and cell viability assays 77 3.2.5 TIJNEL assay 78 3.3RESULTS 79 3.3.1 Characterization of ecdysone-induced l(2)mbn cell death 79 3.3.2 RNAi screen identifies novel genes that affect cell survival and cell death 83 3.3.3 Candidate pro-survival genes act in an ecdysone-dependent or ecdysone-independent manner. 90 3.3,4 TUNEL assay distinguishes pro-survival genes that inhibit cell death 91 3.3.5 TUNEL assay validates genes with a prodeath function in ecdysone-mediated l(2)mbn cell death 97 3.4 DISCuSSIoN 97 3.6 REFERENCES 105 CHAPTER 4. CG4091, A MICROTUBULE DISRUPTING PROTEIN REQUIRED FOR CYTOSKELETAL INTEGRITY, ALTERS AUTOPHAGY AND LIPID METABOLISM 115 4.1 INTRODUCTION 115 4.2 MATERIALS AND METHODS 118 4.2.1 Probe preparation and embryo in situ hybridization 118 4.2.2 Probe preparation and salivary gland in situ hybridization 118 4.2.3 Real-time RT-PCR 119 4.2.4 Plasmid construction 120 4.2.5 Drosophila cell culture and transfections 121 4.2.6 Immunofluorescence (IF) 122 4.2.7. Co-IP and mass spectrometry 123 4.2.8 Western analysis 125 4.2.9 Construction ofpUAST-CG4091 and pUAST-l(2)dtl strains 126 4.2.10 CG4091 gain-of-function study 127 4.2.11 Construction of a CG4091 loss-of-function strain 127 4.2.12. MDC and Nile red staining 128 4.3RESULTS 129 4.3.1 Expression of CG4091 increases in larval salivary glands and midgut prior to cell death 129 4.3.2 Localization of CG409 I transcripts during embryogenesis 132 4.3.3 CG4091 facilitates microtubule remodeling and affects the size and distribution of autolysosomes 133 4.3.3.1 Loss-of-function study 133 4.3.3.2 Gain-of-function study 142 4.3.5 CG4091 co-localizes with actin and microtubules in Drosophila S2 cells 156 4.3.6 CG4091 is sufficient to increase the number of lipid droplets in Drosophila salivary glands. 162 4.4 DISCUSSION 168 4.5REFERENCES 181 V CHAPTER 5. CONCLUSIONS .191 5.1 OVERALL SUMMARY AND SIGNIFICANCE OF THE STUDIES 191 5.2 STRENGTHS AND LIMITATIONS OF THE STUDIES 194 5.2 FUTURE RESEARCH 199 5.3 REFERENCES 202 APPENDIX A. COPY OF ANIMAL CARE CERTIFICATE 204 APPENDIX B. COPY OF BIOHAZARD APPROVAL CERTIFICATE 205 Vi LIST OF TABLES Table 2.1 Differentially expressed genes associated with salivary gland autophagic cell death 51 Table 3.1 Candidate pro-death and pro-survival genes identified by RNAi and cell viability assay 84 Table 3.2. Comparison of RNAi data to SAGE data 86 Table 3.3 Ecdysone dependent and ecdysone independent death-related genes identified by the TUNEL assay 88 Table 4.1 Specific interaction partners of G4091 149 vii LIST OF FIGURES Figure 1.1 Simplified model of intrinsic and extrinsic apoptosis pathways 04 Figure 1.2 Simplified schematic diagram showing autophagic pathway 10 Figure 1.3 Schematic diagram of the SAGE method 16 Figure 2.1 Expression of known salivary gland cell death related genes in SAGE libraries 48 Figure 2.2 Comparison of fold-difference in expression in wild-type (OreR) and E93 mutant salivary glands 59 Figure 3.1 Overview of RNAi screen design 74 Figure 3.2 Ecdysone signaling and apoptosis genes are differentially expressed and required for cell death in ecdysone treated l(2)mbn cells 80 Figure 3.3 Cellular morphology of l(2)mbn cells after dsRNA treatment 92 Figure 3.4 TIJNEL assay identifies genes with cell death-related functions 95 Figure 4.1 Expression of CG409 1 in dying larval salivary gland and midgut and during embryogenesis 130 Figure 4.2 Genomic region of CG409 1 and description of its loss-of-function mutant 134 Figure 4.3 Salivary glands from CG4091-LOF mutants are abnormal and show defects in tubulin network 137 Figure 4.4 CG4091-LOF salivary glands show reduced autophagy in the enlarged cells 140 Figure 4.5 Overexpression of CG4091 is sufficient to disrupt the tubulin network in dying salivary glands 143 Figure 4.6 Salivary glands overexpressing CG4091 display large, aggregated autolysosomes 146 Figure 4.7 Co-IP Western confirms interactions between CG4091 and fatty acid beta- oxidation multi-enzyme complex proteins 151 Figure 4.8 Immunofluorescence assay showing possible sub-cellular localization of CG4091 and interaction partners CG4389 and CG4581 154 Figure 4.9 Drosophila S2 cells grown for more than 3 hrs on CC2 coated slides attach, flatten, spread and form short and long extensions 158 Figure 4.10 CG409 1 colocalizes with the cytoskeleton in S2 cells growing on CC2 coated slides 160 Figure 4.11 Nile red staining of wild type salivary glands 163 Figure 4.12 Overexpression of CG409 1 is sufficient to increase lipid droplets in larval salivary glands 166 Figure 4.13 A model for the role of CG409 1 in the Drosophila salivary gland PCD process 176 viii LIST OF ABBREVIATIONS APF after puparium formation CT cycle threshold EST expressed sequence tag PBS phosphate buffer saline PCD programmed cell death QRT-PCR quantitative reverse transcription PCR dsRNA double stranded ribonucleic acid SAGE serial analysis of gene expression WST 1 4- [3 -(4-iodophenyl)-2-(4-nitrophenyl)-2H-5 -tetrazolio] -1 ,3 -benzene disulfonate based cell proliferation assay ix ACKNOWLEDGMENTS I would like to thank the following people who were instrumental and supportive during my graduate studies. First of all, I would like to thank my supervisor, Dr. Marco Marra, who enthusiastically agreed to be my supervisor. His encouragement, support and advices were indispensable in accomplishing the work presented here and for my graduate life. Next, my special thanks to my committee member and co-supervisor Dr. Sharon Gorski whose support and advices helped me to grow in my scientific career. Her patience and openness for scientific discussions were extremely valuable during my graduate studies. I would like to thank my committee members Drs Thomas Grigliatti and Vince Duronio for their time, support and helpful suggestions throughout my studies. I like to thank present and past lab members of programmed cell death group at Genome Sciences Centre, BC Cancer agency, for making our lab, a wonderful friendly environment. My special thanks to Doug Freeman for his support and help with fly genetics and Ian Bosdet, Melissa McConecky, and Claire Hou for their support and friendship. I also like to acknowledge co-op/summer students James Wilton, Harpreet Sandhu, Ivy Ling and Lindsay Devorkin for their hard work that was put in this work. I like to thank Dr. G. B. Morin, and Dr. M. Kuzyk for collaborations in the proteomic study and Dr. G. Cheng, Heidi Hare, Dr. M. Hirst, and Carri-Lynn Mead for their suggestions and help. My additional thanks to Dr. S. Jones, Dr. E. Pleasance, Scott Zuyderduyn, Richard Varhol and Dr. G. Vatcher for their help with bioinformatic analysis and the Genome Sciences Centre Sequencing group for SAGE library and other sequencing activities. I like to thank Dr. Tom Pfeifer, UBC for advices on Drosophila cell culture and transfection techniques. x I like to thank Dr. Sam Aparicio for allowing us to use the confocal microscope and John Fe for training and technical support on the confocal microscope. Last but not least, I like to thank my family whose support was fundamental and essential in accomplishing this work. I like to thank my parents who always encouraged me to continue higher studies to this level. I like to thank my wonderful husband Chittaranjan, and my children Ramya and Sabrina for their very strong support, patience and understanding. xi CO-AUTHORSHIP STATEMENT Gorski 5, Chittaranjan S, Pleasance E, Freeman DJ, Anderson C, Varhol V, Coughlin 5, Zuyderduyn S, Jones S, Marra M. 2003. SAGE Approach to Discovery of Genes Involved in Autophagic Cell Death, Curr Biol 13: 358-363 I performed 90% of the experiments and QRT-PCR data analysis presented in this paper and assisted with EST and SAGE analysis. Experiments were designed in collaboration with Dr. S. Gorski. The manuscript was prepared by Dr. S. Gorski; I wrote part of Materials and Methods and assisted in the preparation of the manuscript. Chittaranjan S. McConechy M, Hou YC, Freeman JD, and Gorski SM. 2008. Steroid hormone control of cell death and cell survival: molecular insights using RNAi. Submitted in January 2008 to PLOS Genetics; under review. I performed 75% of the experiments presented in this paper. The RNAi screen was conducted in collaboration with Melissa McConechy. I prepared the manuscript in collaboration with Dr. S. Gorski. Chittaranjan S, Kuzyk M, Sandhu H, Wilton J, Devorkin L, Marra M, Morin GB, Gorski SM. 2008. CG409], a microtubule binding protein required for cytoskeletal integrity, alters autophagy and lipid metabolism. In preparation I performed 90% of the experiments presented in this paper. Protein interaction studies were conducted in collaboration with Dr. M. Kuzyk and Dr. G. B. Morin. Co-op students H. Sandhu, J. Wilton, and I. Ling assisted in creating loss-of-function and gain-of function mutants under my supervision. L. Devorkin assisted in Drosophila S2 immunofluorescence studies under my supervision. I prepared the manuscript in collaboration with Dr. S. Gorski. xii Chapter 1. Introduction. 1.1 Functional Genomics Functional genomics is a molecular biology approach that uses the data produced by genomic projects (e.g., genome sequencing projects) to describe gene functions and the interactions of gene products. Unlike genomics and proteomics, which focus on the relatively static aspects of the gene (e.g., DNA sequence, gene product structure, etc.), a functional genomics approach focuses on the dynamic aspects of a gene’s function (e.g., gene transcription, translation, and protein-protein interactions). In our study, we used functional genomics approaches that included large-scale transcriptional profiling, a medium-scale loss of function study and extensive characterization of one gene using a protein-protein interaction study and other molecular approaches to gain new insights into the process of PCD. 1.2 Programmed Cell Death. “Programmed cell death (PCD) is an expression that insinuates that cell death has been genetically programmed, as this is the case during development and aging”[l] . PCD is generally the opposite of non-programmed necrotic death, which is induced by pathological and unfavourable environmental stimuli [1]. There are two common forms of PCD [2,3] that were initially described during the development of vertebrate embryos and are strictly based on morphological characteristics [4]. Type I PCD is known as apoptosis, and cells undergoing apoptosis eventually fragment and form apoptotic bodies, which are engulfed by neighbouring cells in a process known as phagocytosis. Type II PCD is known as autophagic cell death, and during autophagic cell death, cells produce double-membrane vacuoles known as autophagosomes that engulf damaged organelles, 1 long-lived protein molecules and part of the cytoplasmic material. These autophagosomes fuse to lysosomes to become autolysosomes, which degrade the proteins and organelles inside by lysosomal activity [5]. 1.3 Apoptosis. 1.3.1 Biochemical and molecular signals in apoptosis. In mammals and invertebrates, two main biochemical pathways (intrinsic and extrinsic) lead to caspase (cystine aspartic acid-specific protease) activation and apoptotic cell death. In the intrinsic pathway, the Bcl-2 (B-cell lymphomalleukemia-2) family plays a crucial role at the apical stage of the pathway [6,7]. Both pro-and anti-apoptotic Bcl-2 family proteins regulate mitochondrial membrane permeability. During apoptosis, pro-and anti- apoptotic Bcl-2 family proteins trigger mitochondria to release pro apoptotic cytochrome c [6,7]. Cytochrome c leaks out of mitochondria and binds to the apoptosis-protease-activating factor known as Apaf-1, which triggers caspase 9 activation [8]. Caspase 9 activates other caspases, which initiates a cascade of proteolytic activity, In the extrinsic pathway, caspase recruitment is initiated at the plasma membrane by the binding of ligands to receptors such as Tumor Necrosis Factor (TNF) and Fas. These receptors contain a region known as the death domain (DD). Ligand-dependent receptor multimerization results in the recruitment of DD-containing cytoplasmic adaptors such as FADD (Fas-Associated Death Domain) through homophilic DD interactions [9]. Association of ligands such as Fas-L to their respective receptors initiates caspase-8 activity, which in turn switches on the downstream caspase activities that are hallmarks of apoptotic cell death. Under non-apoptosis inducing conditions however, the caspase 2 inhibitor of apoptosis (TAP) inhibits the activation of caspases [10,111 (See also Figure 1.1 for details). Several mammalian pro-apoptotic gene homologues have been identified in Drosophila. These include two Bcl-2 family members (dBorg-/ drob-]/debcl/dbok and dBorg-2/buf), a Apaf-1 homologue (ark), three long prodomain caspases (dcp-2/dredd, drone, and dream) and four caspases with short prodomains (dcp-], drice, decay and daydream) [9,12-21]. The pro-apoptotic genes reaper (rpr), head involution defective (hid) and grim were first identified in Drosophila [22] and their functional mammalian counterparts smac/DIABLO [23] and HtrA2/Omi [24] were identified later. The anti-apoptotic cell death inhibitors (TAP-i and IAP-2), which are homologues of the viral TAP baculovirus p35 [25], were also identified in Drosophila. In addition to TAP-i and TAP-2, deterin (a homologue of mammalian TAP survivin) and dBRUCE (a homologue of BRUCE) have been identified in Drosophila by sequence similarity searches [9]. 1.3.2 Apoptosis and diseases. In general, apoptosis related diseases can be divided into two groups: (a) diseases where apoptosis is inhibited (e.g., cancer), which increases cell survival; and (b) diseases with hyperactive apoptosis, which increases cell death (e.g., neurodegenerative diseases). Researchers have paid particular attention to studying the mechanisms of apoptotic control that underlie the pathophysiology of viral infections, autoinmiune diseases, neurodegenerative disorders, immunologic deficiencies, and cancers. 3 Figure 1.1. Simplified model of intrinsic and extrinsic apoptosis pathways. The key players of the apoptotic pathways are shown here. The extrinsic pathway (left) is activated by the binding of ligands such as TNF and FasL to their respective receptors. This binding recruits the adaptor molecules such as FADD and TRADD, which recruit caspase-8 to form the “death-inducing-signalling complex”. Activation of caspase-8 triggers the effector caspase cascade. The intrinsic pathway (right) is activated by the release of cytochrome c from mitochondria by the regulation of Bcl-2 proteins. Cytochrome c release triggers the formation of an apoptosome that includes Apaf-1 and caspase-9, which activates the effector caspase cascade. The TAP proteins can inhibit apoptosis by inhibiting initiator caspases. The pro-death proteins smac and Omi leak out of the mitochondria during apoptosis and bind to the TAP proteins, which release the intiator caspase. Activation of the caspase cascade triggers apoptotic cell death (adapted from [26,27]. 4 Figure 1.1 Bcl-2 Bax mitochondria Cytochrome c Apaf-1 smac/DIABLO Caspase 9 HtrA2/Omi pase) ‘\IA! nitiator effector caspase proteins eg. Caspase-3 TNF Cell FasL ‘as 1r FADD TRADD FADD / Caspase-8 (initiator caspase) ‘I, 5 Suppression of apoptosis during carcinogenesis is thought to play a major role in the development and progression of some cancers [28]. The proto-oncogene Bcl-2 was first discovered as the target gene present at the translocation site of the t( 14; 18) chromosomal translocation breakpoint in the tumor cells of approximately 80% human patients with follicular B-cell lymphoma [29]. Since Bcl-2 activity increases and confers drug resistance in many cancer cells [30], gene therapies are aimed at down regulation of Bc! 2 proteins. Similarly, increased activity of TAPs may facilitate cancer and promote resistance to therapy [31]. Several reports indicate that negative regulators of the extrinsic apoptosis pathway, including the FLIP (FLICE inhibitory protein) family of proteins, may also trigger tumorigenesis in certain cells [32,3 3]. DNA damage and genomic instability triggers apoptosis of cancer cells, primarily through p53 (atumour suppressor). Inability to express p53 under stress conditions will lead to cancer progression [34]. Caspase inactivation may support oncogenesis [35] however, some triggers of apoptosis may still induce cell death even when caspases are inhibited [36-39]. TRAIL (TNF-related apoptosis-inducing ligand), also called apo-2L, is a broadly expressed TNF-related ligand that can induce apoptosis in many human tumor cells without affecting most of the normal cells. [40]. TRAIL treatment of tumors has been successfully used in several in vivo models in combination with chemotherapeutics with very little toxicity [41]. These examples suggest that pro apoptotic genes are generally mutated or deleted in cancer and therefore are potential tumor suppressors. In contrast, anti-apoptotic genes are potential oncogenes and are generally overexpressed in cancers. 6 In addition to proliferative cancer, inefficient apoptosis of auto-aggressive T cells can result in multiple autoimmune diseases such as autoimmune lymphoproliferative syndrome (ALPS) [42]. Many viruses interfere with various points in the host apoptotic pathways and have the ability to inhibit or promote apoptosis of host cells. Viral proteins such as LMPI from the Epstein-Barr virus, K13 from the Kaposi’s sarcoma herpes virus, and CrmA from the cowpox virus have been shown to inhibit host apoptosis [43-46]. Increased apoptosis levels may also be a feature of some conditions such as autoimmune diseases, neurodegenerative diseases, and ischemia-associated injury. Human immunodeficiency virus (HIV), the prototypic alphavirus and the Sindbis virus are all able to induce apoptosis [47,481. Alzheimer’s disease is a neurodegenerative condition that is presumably caused by mutations in certain proteins such as APP (amyloid precursor protein) and presenilins. Presenilins are probably involved in the processing of APP to amyloid 13. Deposition of amyloid f3 can lead to aggregated plaques, which are neurotoxic [49]. This condition can cause caspase 3 and 12 over- reactivity and induce apoptosis [50,5 1]. The polyglutamine repeats associated with Huntington’s disease induce neuronal cell death via caspase-8 [52]. 1.4 Autophagy and Autophagic Cell Death. 1.4.1 Background. There are three forms of autophagy, however, the most common and well studied form of autophagy is known as macroautophagy (hereafter referred to as autophagy). During the process of autophagy, vacuoles known as autophagosomes form in the cytoplasm and engulf cytoplasmic components such as damaged organelles or proteins. Autophagosomes have double-membranes, and in yeast are considered to derive from 7 pre-autophagosomal structures (PAS) of unknown origin. But studies in other organisms suggest that they derive from ribosome-free regions of the endoplamic reticulum or post Golgi membranes [53]. Autophagosomes eventually fuse to lysosomes and form autolysosomes, which are acidic in nature. Cytoplasmic components are then degraded in these autolysosomes by lysosomal activity [5]. The genes involved in macroautophagy in yeast, and their homologues in Drosophila, mammals and other organisms, have been identified [54]. To date, 31 yeast autophagy genes (hereafter referred to as Atg genes) [55], and at least seven human and 14 Drosophila homologues have been identified [54,56,57]. Currently, Drosophila loss- of-function mutants are available for 8 Atg genes [57] and knock-out mice are available for Atg4, Atg5, Atg 6 and Atg7 [58-61]. When cells or tissues that are triggered to undergo cell death show morphological features of autophagy, it is referred to as autophagic cell death. In several instances it is not clear whether autophagy is directly involved in initiation and/or execution of cell death, or if it represents a final attempt to preserve cell viability. Recent studies show that autophagy may play an active role in PCD, however, the conditions under which autophagy promotes cell death and/or cell survival remain to be resolved [62,63]. 1.4.2 Function and regulation of autophagy proteins. In yeast, under normal conditions, mTOR Ser/Thr kinase inhibits autophagy by phosphorylating autophagy protein-13 (Atgl3). During the autophagy process, dephosphorylated Atgl3 associates with Atgl kinase and Atgl7, which stimulates catalytic activity of Atg 1 and induces autophagy. The mammalian orthologue of the yeast Atgl 3 has not yet been identified. During the initial stage of vesicle nucleation, 8 mammalian Vps34, a class III P13-kinase (P13K) forms a multiprotein complex in which beclin-1, the mammalian orthologue of Atg6, UVRAG (UV irradiation resistance- associated tumour suppressor gene) and a myristylated kinase (Vpsl5, or p150 in humans) participates. This P13K complex phosphorylates phosphatidylinositol and generates phosphatidylinositol-3 -phosphate (PtdIns3P) by phosphorylation [53,54,64]. The next step of autophagy is vesicle elongation, which requires two ubiquitin-like conjugation systems. In one pathway, Atgl2 conjugates to Atg5 with the help of the El- like enzyme Atg7 and the E2-like enzyme Atg 10. In the second pathway, Atg8 (also known as LC3 in humans) is lipidated with phosphatidylethanolamine (PE), by the sequential steps of the protease Atg4, the El-like enzyme Atg7 and the E2-like enzyme Atg3. Lipid conjugation leads to binding of the soluble form of LC3 (named LC3-I) to the autophagosome to result in the autophagosome-associated form (LC3-II). LC3-II is used as a marker of autophagy due to its ability to localize to autophagosomes, which yields a shift from diffuse to punctate staining of the LC3-I1 protein and increases its electrophoretic mobility on gels compared with LC3-I [53,54,64]. Regulatory mechanisms of ecdysone induced [65,66] and starvation induced autophagy [66] in the fat body have been demonstrated in Drosophila. Most recently, the role of autophagy in larval salivary gland death in Drosophila has also been established [621. All three studies have clearly revealed the regulation of autophagy through down regulation of P13K (see also Figure 1.2 for details). 9 Figure 1.2. Simplified schematic diagram showing autophagic pathway. During the autophagy process, an isolation membrane is initially formed in the cytoplasm (step 1). The isolation membrane elongates (step 2), engulfs cytoplasmic material and forms double membrane autophagosomes (step 3). The autophagosomes fuse to a lysosome (step 4) and the engulfed materials are degraded by the lysosomal enzymes (step 5). Autophagy is stimulated initially by the inhibition of mTOR kinase which allows the dephosphorylated Atgl3 to associate with Atgl kinase and Atgl7. For the isolation membrane formation, Vps34 (a mammalian class III P13-kinase (P13 K) homologue) phosphorylates phosphatidylinositol to make phosphatidylinositol-3 -phosphate (PtdIns3P). This activation depends on the formation of a multiprotein complex in which Beclin-l, UVRAG and a myristylated kinase Vpsl5 participate. For membrane elongation, two ubiquitin-like conjugation systems are required. In the first conjugation system, Atgl2 conjugates to Atg5 with the help of the El-like enzyme Atg7 and the E2- like enzyme AtglO. Atg5-Atgl2 complex then binds to Atgl6. Conjugated Atg5 binds to the elongation membrane. In the second system, Atg8 (known as LC3 in human) is lipidated with phosphatidylethanolamine (PE), by the sequential steps of the protease Atg4, the El-like enzyme Atg7 and the E2-like enzyme Atg3. Lipidated Atg8 binds to the elongation membrane. Binding of both Atg5 and Atg8 are essential for completion of elongation of autophagosomal membrane and therefore, for the formation of an autophagosome (adapted from [53,54,64]). 10 Figure 1.2 Atgl3 / UVRAG Vps34 Beclin-1 Vps 15 P13K complex III Atg7 Atg4 Atgl7 Atgl3 Atgl 1. Isolation 2. Vesicle membrane elongation Atgl2 5. Degradation in autolysosomeformation 4. Lysosomal docking and fusion 11 1.4.3 Antophagy and diseases. Autophagy and autophagic cell death have been associated with neuronal culture models and human neurological diseases [67], tumorigenesis [68,69], cardiovascular diseases [70], aging [71,72], pathogen infections [73-76] and cytotoxic drug treatment [77]. There has been a recent increase in the number of studies focusing on the role of autophagy in tumurogenesis and neurodegenerative diseases have increased dramatically. Beclin-1, a mammalian homologue of the yeast autophagy gene Atg6 [69], was heterozygously deleted in 40-75% of sporadic human breast and ovarian cancers. Beclin 1 also promoted autophagy in MCF-7 breast carcinoma cells [5]. Beclinl—/— mice died early during embryogenesis and the aging beclinl+/— mice had an increased incidence of lymphoma and carcinomas of the lung and liver [61,78]. In addition, mammary tissue from beclinl+/— mice showed hyperproliferative, preneoplastic changes [78]. These observations suggest that autophagy has a tumor suppressor function in cancer. In contrast, similar to that shown in hematopoietic [79] and kidney epithelial cells [80,81], autophagy acts as a survival mechanism in mammary epithelial cells in response to metabolic stress, especially when apoptosis is disabled [82]. In mammary epithelial cells, concurrent inactivation of autophagy and apoptosis leads to accumulation of DNA damage and double-strand breaks when placed under metabolic stress, which enables gene amplification and thus creates a permissive environment for genomic instability and cancer progression [82]. Many late-onset neurodegenerative diseases are caused by the accumulation of mutated protein-aggregates that are toxic [83]. Non-aggregated wild-type proteins are efficiently cleared by proteasomes, but the aggregated proteins are a poor proteasome 12 substrate and autophagy becomes a major clearance route by default under these circumstances [84-87]. Inhibiting autophagy has deleterious effects in neuronal diseases, including enhancement of certain types of apoptosis [88,89] and formation of ubiquitinated inclusions [901. In mouse models, knockouts of autophagy genes Atg5 and Atg7 lead to early neonatal lethality [59,91]. Interestingly, mice with neuronally confined autophagy-gene knockouts develop intraneuronal aggregates and neurodegeneration [58,91]. Though recent studies have shown the importance of autophagy in cancer, neurodegenerative diseases and other diseases, there are still a number of controversies including the pro-survival and/or pro-death role of autophagy in diseases and therefore, whether autophagy should be suppressed or enhanced under disease conditions. Before autophagy modulation can be therapeutically used, it will be important to determine whether autophagy has a pro-death or a survival role in diseases in vivo. 1.5 Programmed cell death in Drosophila development. Both apoptosis and autophagic cell death mechanisms are necessary for the normal development of Drosophila. The process of apoptosis has been well characterized in embryonic development, where it occurs in the anterior head region, posterior region and in the embryonic central nervous system [92]. In addition, apoptosis has been observed during the development of numerous other tissues such as the eye, wing, and oocyte [93,94]. During metamorphosis, 20-hydroxyecdysone triggered the autophagy associated cell death of larval midgut and salivary glands [95]. The Drosophila developmental system uses both types of PCD that are spatially and temporally controlled, and more mammalian cell death genes are conserved in 13 Drosophila than in other model organisms like C. elegans. This makes Drosophila an excellent in vivo system to study the molecular mechanisms of cell death. 1.6 Steroid-triggered autophagic cell death in Drosophila larval salivary glands. Drosophila larval salivary glands initiate as two ventrolateral plates of approximately 100 cells each in the presumptive posterior head region of the developing embryo. During salivary gland differentiation, these 100 cells do not undergo additional cell divisions but increase in size. Mature salivary glands consist of two types of cells, namely, secretory cells and ductal cells. The secretory cells initiate multiple rounds of DNA replication and create polytene chromosomes [96]. During the development of Drosophila and other insects, steroids, particularly 20- hydroxyecdysone (2OHE), trigger distinct cellular responses, including cell differentiation and PCD [97]. In Drosophila, during metamorphosis, successive pulses of 2OHE at the 3rdinstar larval stage and 10-12 hr After Puparium Formation (APF) trigger autophagic cell death of the larval midgut and salivary glands, respectively, and initiate the cell differentiation and morphogenesis of imaginal discs to give rise to the adult tissues [95]. The second ecdysone pulse triggers a transcriptional hierarchy in the larval salivary glands. Some of the genes involved in this hierarchy have been identified [95,98-101]. In response to the ecdysone pulse at the pre-pupal stage (i.e., 10-12 hr APF), the ecdysone receptor complex, a heterodimer protein complex formed by proteins encoded by EcR (ecdysone receptor) and usp (ultraspiracle) genes, binds to DNA and activates transcription of transcription factors encoded by the Broad-Complex, (BR-C), E74A, E93 and E75 genes. At a pre-death stage of salivary glands (12-13 hr APF at 25°C; determined to be equivalent to 23 hrs APF at 18°C in our laboratory), the 14 transcription factors BR-C, E74A, and E93 are required for the maximal induction of rpr and hid. The transcription factor E75B is sufficient to repress transcription of the inhibitor of apoptosis protein 2 gene, diap2 [98], while EcR and the CREB binding protein (CBP) transcriptional cofactor are required for diap] down regulation [102]. Functional studies have shown that EcR, E93, BR-C, hid, ark, dronc, CBP (CREB binding protein), Fkh (Fork head), and AP- 1 (heterodimer of c-Jun and c-Fos) are required for Drosophila salivary gland cell death [95,102-110]. In the most recent report, inhibition of salivary gland cell death has been demonstrated by maintaining growth by expression of either activated Ras or positive regulators of the class I phosphoinositide 3-kinase (P13K) pathway [111]. In addition, developmental degradation of salivary glands is also inhibited in autophagy gene (Atg) mutants even in the presence of active caspases. Combined inhibition of both autophagy and caspases increased suppression of salivary gland degradation [1111. These findings suggest a role for autophagy and autophagy-related genes, in addition to apoptosis, in salivary gland cell death. 1.7 Gene Expression profiling and the SAGE method. Gene expression is the process by which genetic information at the DNA levels is processed into functional gene products such as non-coding mRNA, and coding mRNA that are translated into proteins later. Gene expression profiling methods identify and quantitate genes that are active in a tissue or cell(s) in any given time and therefore, potentially create a global picture of cellular function. Expressed Sequence Tags (ESTs) [112], Serial Analysis of Gene Expression (SAGE) [113] (see Figure 1.3) and microarray [114] methods are frequently used to profile mRNA expression levels. 15 Figure 1.2. Schematic diagram of the SAGE method. Double-stranded cDNA is synthesized from mRNA using biotinylated oligo dT primers that are attached to streptavidin magnetic beads (step 1). The cDNA is cleaved at CATG sequences with an anchoring enzyme (e.g. Nialli) and the most 3’ portion of the cDNA is isolated with streptavidin beads using a magnet. Therefore, a unique site on each transcript that corresponds to the restriction site located closest to the 3’ polyadenylation site is generated (step 2). The isolated cDNA pooi is then divided in half and ligated to linkers A and B (primers A and B) containing a type uS restriction site (tagging enzyme; eg. BsmFI) (steps 3, 4). Depending on the tagging enzyme used, cDNAs are cleaved to generate 13-26 bp tags [1 l3,115-117j and the tags are pooled together and ligated to form ditags (step 5). Ditags are PCR amplified (step 5), then cleaved with the anchoring enzyme (NlaIII), concatemerized (step 6) and cloned into a vector. Cloned concatemerized ditags are then sequenced and the tag sequences are matched to reference sequences (eg. previously sequenced genome, cDNA etc.) and each tag type is quantitated using bioinformatic tools. (step 7) Each tag type corresponding to transcripts can then be compared between samples tested.(step 8) (modified from [113]) 16 Figure 1.3 Transcript A 1. RNA Isolation and ____________________ 1J cDNA synthesis on Transcript B streptavidin beads Unique site for 4, transcript A ________ 2. Cleavage with anchoring enzyme (eg. N1aHI)atCATG(.e4) 3. Divide in half and ligate to linkers (primer A and),.Z” s.% ‘ICut with tagging enzyme erB-4+M N 5.Ligate and PCR amplify with primers A and B I Ditag Primer A Primer B Primer A Primer B 6. Cleave with anchoring enzyme 4 and concatermerize ditags Tag 7. Bioinformatics: correlate tags to gene + (or genome) and quantitate tags CT6GATCC1GCCA 81 1718 1006 36522748205 0 N 1 gene C67592 CTGATFTTCTTAFI 39 1554 1001.92253982357 0 N 1 gene C67224 Gene ID CT6TATGTflT6 50 504 235 59927942045 1,75773844389143e—104 N 1 gene Cpi CTGACT6TGI6 2316 437 664 222606521449 7÷44267685712638e—291 N 1 gene Eigll CATGTCFIAFIGG 22 404 224,779926862102 8,99238134517476e—I00 N 1 gene C615505 4, 8. Expression comparison stage I stage 2 C 00 C 1000 0 C 00 n ,, I — riJ, Genes identified Genes identified 17 Although correlations between mRNA expression levels and protein levels vary, there is generally relevancy for abundantly differentially expressed genes that are transcriptionally regulated [118-120]. While microarray techniques rely on cDNAs or oligonucleotides of knownlpredicted genes, the SAGE method is an extremely powerful, efficient, and comprehensive approach for analyzing gene expression profiles of predicted and unpredicted genes. Therefore, in addition to expression profiling, the SAGE method can also be utilized in novel gene, gene transcript and pathway discovery. Advantages and disadvantages of using the SAGE method are discussed in chapter 5. 1.8 Thesis rational, objectives and Hypotheses. Although several core genes involved in apoptosis, autophagy and autophagic cell death mechanisms have been identified and their roles in various diseases have been determined, there were no examples that have comprehensively studied, at genomic levels, the molecular mechanisms of PCD that involves both apoptosis and autophagy. In addition, the extent of the connection of autophagic cell death to cancer is still controversial. In general, apoptosis is compromised in cancer cells, therefore, a better understanding of the role of autophagy and autophagic cell death in relation to apoptosis is very important for future therapeutic considerations. Since Drosophila offers excellent genetic tools, and steroid-induced cell death of larval salivary gland is transcriptionally regulated with morphological features of both apoptosis and autophagy, I chose to use this exceptionally well-suited in vivo metazoan system for studying the complex mechanisms involved in steroid induced PCD. 18 1.8.1 Overall objectives. Overall, the objectives of my studies were to first identifi, verify and catalogue genes that are transcriptionally regulated during steroid-induced PCD in Drosophila salivary glands; then to identify the genes with pro-death and pro-survival function in ecdysone induced programmed cell death; and finally, to explore in detail the function of a novel gene potentially involved in PCD. This approach was chosen to elucidate some of the novel genes involved in apoptosis and autophagy and to provide more insight into the regulatory mechanisms involved in these forms of PCD. Since both autophagy and apoptosis processes are associated with cancer and other diseases, the possibility exists that the cell death associated genes that I identified in my study may play roles in human disease processes. 1.8.2 Objective 1. To identify, verify and catalogue genes that are transcriptionally regulated during steroid- induced PCD in Drosophila salivary glands. 1.8.2.1 Rationale. The Drosophila larval salivary glands undergo PCD in a precise stage-specific manner, during which known pro-death genes are up regulated and pro-survival genes are down regulated [93]. 1.8.2.2 Hypothesis. Expression profiling studies of larval salivary glands undergoing PCD may identify new pro-death genes that are expressed at elevated levels and pro-survival genes that are down regulated prior to cell death. 19 1.8.2.3 Summary research plan. To identify genes associated with autophagic cell death, I employed the Drosophila larval salivary glands as a model system and conducted gene expression profiling studies using serial analysis of gene expression (SAGE) [101]. A subset of the SAGE data was verified by real-time Quantitative RT-PCR (QRT-PCR) analysis. 1.8.3 Objective 2. To identify the genes with pro-death and pro-survival function in ecdysone-induced programmed cell death. 1.8.3.1 Rationale. The Drosophila tumorous blood cell line l(2)mbn undergoes ecdysone-induced PCD with increased expression of known pro-death genes. Knock-down of known pro-death genes using RNA interference (RNAi) inhibits PCD induced by ecdysone. 1.8.3.2 Hypothesis. Knock-down of potential pro-death genes by RNAi (i.e., genes up-regulated in objective 1), will result in inhibition of ecdysone-induced l(2)mbn cell death. Knock-down of potential pro-survival genes (i.e., genes down-regulated in objective 1), will result in increased cell death. 1.8.3.3 Summary research plan. To identify new pro-survival and pro-death genes related to the ecdysone signaling network, an RNA interference screen was performed in Drosophila l(2)mbn cells. I screened a total of 460 genes from objective 1 using RNAi and a cell viability assay. I further screened positive hits using a second set of non-overlapping dsRNA+cell viability assay, cell morphology and TUNEL apoptosis assays. 20 1.8.4 Objective 3. To explore, in detail, the function of a novel gene involved in PCD. 1.8.4.1 Rationale. The Drosophila gene CG4091 was selected for detailed study based on the following criteria: (a) CG4091 expression increased more than 100-fold in the SAGE libraries at the prior-to cell death stage, which was confirmed by QRT-PCR in an independent experiment in salivary glands. (b) Deduced protein sequence of this uncharacterized gene, CG4091, has strong similarities to the TNF-c induced proteins GG2-1 [121] and SCC-S2 [122], now known as TNFAIP8. In mammals, the TNF-induced pathway is associated with PCD. Therefore, it is possible that CG4091 plays a role in PCD in Drosophila. (c) QRT-PCR experiments indicated that CG4091 is also up-regulated prior to death in the larval midgut, which also undergoes steroid-induced PCD. 1.8.4.2 Hypotheses. Hypothesis 1: If CG409] function is associated with PCD in larval salivary glands, CG4091 loss-of-function and/or gain-of-function would affect PCD in this tissue. Hypothesis 2: CG4091 encodes a cellular protein that interacts with other salivary gland cell death associated proteins. 1.8.4.3 Summary research plan. For in vivo loss of function studies, I utilized a P-element mutant strain of CG409] (EY06821) and imprecisely excised the P-element to generate CG409] loss-of-function alleles. To examine the effects of overexpression of CG409], I created mutant strains with P-UAST-CG409] and used the tissue specific drivers using UAS-GAL4 system to overexpress CG4091 in salivary glands. To identify the proteins that interact with the CG4091 protein in an in vitro system, I used Drosophila S2 cells. I expressed N- and C 21 terminally FLAG tagged CG4091 fusion protein, in S2 cells and performed immuno affinity purification (IP) and tandem mass spectrometry (MS/MS) fragmentation based assays. 22 1.9 References 1. Kroemer G, El-Deiry WS, Goistein P, Peter ME, Vaux D, et al. 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A SAGE Approach to Discovery of Genes Involved in Autophagic Cell Death’ 2.1 Introduction Programmed cell death (PCD) is a critical process by which obsolete cells or tissues are removed during normal development of multicellular organisms. Damaged cells are also removed by PCD, providing a crucial means preventing diseases such as cancer and autoimmunity [1]. Cell death can be divided into several subtypes based on morphological criteria [2,3]. Type I cell death, or apoptosis, is associated with collapse of the cytoskeleton, condensation and fragmentation of chromatin and cytoplasm, preservation of organelles, and phagocytosis by neighbouring cells or macrophages (heterophagy). Type II cell death, or autophagy associated cell death (hereafter referred to as autophagic cell death), is characterized by the formation of autophagosomes that engulf cytoplasm and organelles. Subsequent fusion of autophagosomes with lysosomes results in formation of autolysosomes where self-degradation occurs. The process, termed autophagy, is a major pathway for cellular degradation and turnover and has been studied in yeast where it can be induced under starvation conditions [4]. Under certain conditions, autophagy appears to comprise the initial phase of autophagic cell death degradation and is followed by late chromatin condensation, nuclear degeneration, and macrophage removal of cellular remnants [5]. A version of this chapter has been published. Gorski S, Chittaranjan S, Pleasance E, Freeman DJ, Anderson C, Varhol V, Coughlin S, Zuyderduyn 5, Jones S, Marra M. 2003. SAGE Approach to Discovery of Genes 1nvolved in Autophagic Cell Death, Curr Biol 13: 358-363 37 While both autophagic and apoptotic cell death are associated with normal development and with human disease, apoptotic cell death has received much more attention during the past decade. As a result, many molecules associated with apoptosis pathways have been discovered and studied extensively, and are now being investigated as potential therapeutic targets. Autophagic cell death, however, remains less well characterized and its associated molecules and mechanisms in multicellular organisms require elucidation. During Drosophila metamorphosis, the larval salivary glands undergo cell death displaying characteristics of apoptosis and autophagy [6,7] that is regulated by a transcriptional cascade induced by the steroid hormone 20-hydroxyecdysone (ecdysone) [7]. Following a pulse of ecdysone at the prepupal-pupal stage transition, the transcription of several known ecdysone-induced and cell death genes is upregulated [8- 10]. Notably, molecules that are known to be regulated post-translationally such as Ark (the Drosophila Apaf- 1 homolog) and Dronc (a Drosophila caspase) are also regulated transcriptionally in pre-death-stage salivary glands. Subsequently, the entire larval salivary gland undergoes cell death in a rapid, stage-specific, and virtually synchronous manner. These features combine to make the Drosophila salivary gland death an ideal system for analysis of gene expression associated with autophagic cell death. In general, three genome-scale methods are employed to measure mRNA abundance. These are Expressed Sequence Tags (ESTs)[1 1], Microarray [12] and SAGE [13]. Microarray methods use either eDNA or oligonucleotide-based chips containing probes designed from previously identified gene sequences and employ hybridization techniques. Typically, such arrays have not been used for gene discovery. In contrast, the EST and SAGE methods offer advantages for new gene identification. In addition, 38 SAGE analysis is quantitative and therefore, an excellent method for gene expression profiling. Here we report the first comprehensive description of gene expression associated with autophagic cell death during normal metazoan development in vivo. Using both SAGE and EST approaches, we analyzed gene expression in Drosophila salivary glands dissected from multiple developmental stages leading up to cell death. Differential gene expression was validated by quantitative RT-PCR and differentially expressed genes were associated with biological annotations. 2.2 Materials and Methods 2.2.1 Fly strains. The wild-type Drosophila melanogaster strain used was OreR, obtained from the Bloomington Drosophila stock center. To reduce possible sequence variability, a single pair mating from the OreR stock was used to construct an OreR line. For E93 mutant analyses, non-Tubby pupae were selected from progeny of a cross between E93’/TM6B and w, Df(3R)93P’2/TM6B,Hu, Tb,e (a gift from Dr. E Baehrecke, University of Maryland). Stocks were maintained at room temperature and then shifted to 18°C following collection of white prepupae (time 0 hours APF). 2.2.2 Tissue dissection and RNA preparation. Salivary glands were dissected into PBS and then transferred immediately to RNAlater (Ambion). Tissue was stored in RNAlater at 4°C overnight and then transferred to —20°C. Total RNA was extracted using Trizol (Invitrogen). 2.2.3 cDNA library construction and EST sequencing. Five hundred pairs of salivary glands from mixed stage (16-24 hrs APF, 18°C) animals were dissected, which yielded 204 ig of total RNA. MessageMaker reagent 39 (Life Technologies/Invitrogen) was used to extract 1 ig of mRNA that was then used to construct an oligo-dT-primed directional cDNA library (Superscript Plasmid System for cDNA Synthesis and Plasmid Cloning; Life Technologies/Invitrogen) as described by the manufacturer. The 3’ ends of cDNAs were sequenced using —21 Ml 3 Forward primer and either an ABI PRISM 3700 DNA Analyzer or MegaBACE 1000 DNA Sequencing System (Molecular Dynamics/Amersham). 2.2.4 EST Clustering. ESTs were trimmed for vector using cross_match (P. Green, unpublished) and for poor quality sequence using Phred [14]. Remaining sequences were masked for low complexity and repetitive regions using Dustn (NCBI toolkit release 6.1) and RepeatMasker (A. Smit, unpublished) (version available 04042000; Drosophila library from Repbase [15] Update vol. 7 no. 2, March 2002, option —dr). Clustering was based on cross_match alignments between all possible EST pairwise comparisons and required at least 95% identity over 80 bp with no greater than a 10 bp sequence end overhang. A BLASTN [16] (v. 2.0.14) comparison to genes revealed 3 chimeric sequences that were removed from further analyses. Representative EST sequences were chosen as: (i) the longest sequence from a cluster or (ii) any singleton EST sequence that aligned to genomic sequence by BLASTN with at least 95% identity over 80 bp. Comparisons were then conducted between representative EST sequences and all Drosophila predicted genes [17] (14,350 including mitochondrial genes; GadFly release 2), enhanced to include UTRs [18] and all Drosophila expressed sequences [19] (total of 259,620 as of May 14 2002) using BLASTN with a minimum requirement of 95% identity over 80 bp. 40 2.2.5 SAGE. Salivary gland stages (16, 20, and 23 hrs APF @18°C; equivalent to 8.5, 11 and 12.5 hrs APF at 25°C) were chosen for SAGE library construction based on acridine orange staining and expression profiles of known cell death genes. At 24 hrs APF (18°C) we detected acridine orange staining in all nuclei of salivary gland cells and occasional degradation of tissue indicating that the death process had begun. Quantitative RT-PCR (below) was used to examine transcript levels of an anti-apoptotic gene iap2, and pro- death genes reaper, and hid in salivary glands dissected at 16, 18, 20, 22, 23, and 24 hrs APF (18°C). Similar to a previous report [8], expression levels of iap2 decreased from 16 to 24 hrs, and expression levels of genes reaper and hid peaked at 23 hrs APF. Relative levels of reaper expression were greater than that of hid. SAGE libraries were constructed with the Invitrogen I-SAGE kit following the manufacturer’s protocol. The starting material was 20 jig of OreR salivary gland total RNA (from 30 to 40 salivary gland pairs) that was DNAse-treated. Four SAGE libraries were prepared from salivary glands dissected at three different time points: two libraries from 16 hrs APF (SG16), one from 20 hrs APF (SG2O) and one from 23 hrs APF (SG23). Twenty-seven to 30 PCR cycles were used to amplifr ditags during library construction. Sequencing was conducted on an ABI PRISM 3700 DNA Analyzer using BigDye primer cycle sequencing reagents (ABI). Sequences were processed using Phred [14,20] and vector sequences were detected using cross_match (P. Green, unpublished). Fourteen base pair tags were extracted and an overall quality score for each tag was derived based on the cumulative Phred score. Duplicate ditags, linker sequences, tags with less than 95% quality, and singletons (i.e., tags observed only once) were removed 41 from the analyses. SAGE libraries were compared pairwise and statistical differences between tag abundance was determined using the methods of Audic and Claverie [21]. 2.2.6. Tag-to-gene mapping in Drosophila. SAGE tags were first compared to Drosophila predicted gene sequences [17] (GadFly release 2) that were enhanced to include UTRs [1 8]. If no match to a predicted gene was found, the tags were compared to ESTs (BDGP and salivary gland) and BDGP full-length cDNAs [19] (total of 259,620 as of May 14, 2002). Matches to multiple ESTs were resolved to a single representative if all ESTs overlapped in their alignment to genomic sequence. Matches to multiple ESTs were resolved to a gene if one of the ESTs overlapped a gene, or the clone partner (i.e., corresponding 5’ EST) of one of the ESTs overlapped a gene. Remaining tags were mapped to genomic sequence (GadFly release 2) as well as ESTs and predicted genes in the reverse orientation. Reverse EST matches were also resolved to a single representative if all ESTs overlapped in their alignment to genomic sequence. 2.2.7 Real-time RT-PCR. Primers were designed using Primer Express V software (Applied Biosystems). Reactions were performed (n=3) using the SYBR Green One-step RT-PCR reagent kit on an Applied Biosystems 7900 Sequence Detection System. Each 15 p1 reaction included 50 ng of DNAse-treated total RNA and 0.1 1iM of each primer. Melting curve analysis was performed for each run to ensure there was a single major product corresponding to the predicted melting temperature. Results were calculated using the Comparative CT Method with Drosophila rp49 as the reference sample and values were normalized to the 16 hr APF timepoint (User Bulletin #2, ABI Prism 7700 Sequence Detection System, 42 Applied Biosystems, 2001). Drosophila rp49 showed no significant difference in expression at the timepoints studied. To demonstrate that efficiencies of target and reference samples were approximately equal, validation experiments (User Bulletin #2, ABI Prism 7700 Sequence Detection System, Applied Biosystems, 2001) were performed for six different samples (reaper, iap2, CG]643, CG409], CG2023, Nc; concentration range of 25 to 100 ng total RNA from 23 hr APF salivary glands). In all six cases, the absolute value of the slope of log input amount vs. ACT was <0.1. E93 mutant salivary glands were dissected at 16 hrs, 23 hrs, and 30 hrs APF (18°C). The latter timepoint was later than that used for OreR to account for any possible effects due to the delayed development observed in the E93 genetic background [101. The correlation coefficient between fold-difference values determined by SAGE and fold-difference values determined by RT-PCR was calculated using the Correl method in Microsoft Excel. All genes with 0 tags at the 16 hr or 23 hr timepoint were excluded from the calculation. Also excluded were the five genes that were not concordant with respect to the direction of change in expression. Fold-difference values for the remaining genes (63 in total) were used to calculate the correlation coefficient. The fold-difference values between SAGE timepoints were computed by comparing SAGE tag library numbers that were normalized to SG23, the SAGE library with the fewest number (27, 086) of total tags. 2.2.8 Atg-Iike genes. Yeast Atg gene sequences were used to search the Drosophila genome sequence using tBLASTX. E values greater than 1 0 were considered insignificant. SAGE tags and/or ESTs were detected corresponding to CG8866 (Aig] -like), CG]241 (Atg2-like), 43 CG6877 (Atg3-like), CG6]94 (Atg4-like), CG]643 (Atg5-like), CG5429 (Atg6-like), CG]534 (Atg8-like), and CG3 615 (Atg9-like). RT-PCR also indicated salivary gland expression of CG10861 (Atgl2-like). Quantitative RT-PCR indicated no increase in expression at 23 hrs for CG8866, CG12334 (Atg-8-like), CG6877, and CG3615. 2.3 Results. 2.3.1 Tissue-specific Genome-wide Expression. To identify genes involved in autophagic cell death, we performed Drosophila salivary gland SAGE [13] and EST [11] profiling, two methods ideally suited for discovery of new genes. For SAGE, we chose three developmental timepoints for examination, (16, 20, and 23 hrs APF; at 18°C), based on acridine orange staining (a vital dye that permeates dying cells and binds chromatin) of staged salivary glands and expression profiles of known cell death genes. Following SAGE library processing, more than 30,000 SAGE tags from each of the three library timepoints were available for analysis. These tags represent a total of 4,628 different transcripts, with 3,126; 3,034 and 2,963 different transcripts detected at the 16, 20 and 23 hr timepoints, respectively. At each timepoint, the majority of transcripts (>50%) were observed between 2 tolO times, while relatively few transcripts (1.2 - 1.4%) were observed more than 100 times. This latter group of abundant transcripts accounts for about one-half (53%, 53%, and 47% from 16 hr, 20 hr, and 23 hr, respectively) of the total number of tags detected in each library. 2.3.2 Tissue-specific ESTs. As part of our gene discovery strategy and to facilitate the mapping of our salivary gland SAGE tags to genes, we generated salivary gland specific ESTs. Results of other 44 Drosophila tissue-specific EST projects, e.g., in the testes and brain, indicated that the Drosophila predicted gene set is not complete [22,23]. We generated 3’ end ESTs since SAGE tags correspond to the 3’ —most Nia III site of their associated transcripts. A total of 5,181 high quality salivary gland 3’ EST sequences were clustered and found to represent 1,696 different transcripts. A total of 1,280 of these transcripts matched both Drosophila predicted genes [17] and Berkeley Drosophila Genome Project (BDGP) ESTs and/or full-length cDNAs [19] (Methods), 145 matched only BDGP ESTs/full length cDNAs but no predicted genes, 75 matched BDGP predicted genes only, and 196 matched no predicted genes and no BDGP ESTs/full-length cDNAs. In the latter class, 16 of the transcripts corresponded to EST clusters of two or more transcripts and 180 were present as singletons, all of high sequence quality (see Methods). These 196 transcripts, 11.5% of all unique transcripts represented by the salivary gland ESTs, likely represent previously unannotated genes but it is also possible that they represent novel splice variants or 3’ ends of already predicted genes. Overall, our salivary gland EST data confirmed expression of predicted genes and also aided in gene discovery and gene annotation in Drosophila. 2.3.3 SAGE Identifies Novel Transcripts in Drosophila. To identify genes corresponding to SAGE tags, we utilized a Drosophila tag-to-gene mapping computer program [18) that incorporated our salivary gland specific 3’ EST data. Tag-to-gene mapping was conducted for the tags corresponding to all 4,628 detected salivary gland transcripts (see Methods). 2,866 (61.9%) of the tags were mapped to known or predicted Drosophila genes, 289 tags (6.2%) were mapped to genomic DNA and ESTs not associated with a predicted gene, 1170 (25.3%) were 45 mapped to genomic DNA andior the reverse strand of an EST or predicted gene, and 303 (6.5%) could not be matched to existing sequence data. Tags mapped only to genomic DNA may represent a novel gene or a novel 3’ end or splice form of an already predicted gene. In 225 cases where a tag matched both genomic DNA and the reverse strand of an EST, the tag mapped to a single genomic location and all matching ESTs also corresponded to the same location. Thus our data suggests the existence of at least 225 (4.9% of all tagged transcripts) previously unpredicted transcripts that likely represent divergently transcribed overlapping gene sequences. The unrnapped tags could be due to sequence polymorphisms, common sequencing errors, or to lack of representation in the available sequence resources. It is also possible that unmapped tags span two exons that are currently not represented in the EST or cDNA data set. A complete list of salivary gland SAGE tag sequences, frequency, and mappings can be found in [24]. Additional data are required to verify the existence of potentially novel genes identified by SAGE tags. We were able to verify 168 novel gene-associated SAGE tags since they mapped specifically and unambiguously to our novel salivary gland ESTs, thus demonstrating the complementarity of a tissue-specific 3’ EST and SAGE approach. Additional novel gene-associated SAGE tags of interest can be verified by quantitative RT-PCR. 2.3.4 Verification of SAGE data by real-time quantitative RT-PCR. To independently verify differential expression of individual genes, we conducted real-time RT-PCR analyses for 78 genes upregulated and 18 genes downregulated between the 16 and 23 hr timepoints. We selected genes representing a range of abundances and fold-differences in expression. The fold difference in expression 46 achieved by SAGE and real-time RT-PCR was compared. Results were concordant with respect to the direction of change in expression for 9 1/96 (95%) of the genes tested and we observed a positive correlation (correlation coefficient = 0.48) between fold- difference measurements in the two data sets. Hence, our real-time RT-PCR experiments confirm the observed salivary gland SAGE data. 2.3.5 SAGE identifies genes associated previously with salivary gland death. SAGE tags corresponding to known cell death and ecdysone-induced genes associated previously with salivary gland cell death [9,10,25] were detected in our SAGE libraries (Figure 2.1). BR-C, E74 and E75 are general ecdysone-induced primary response genes shown previously to regulate salivary gland expression of cell death genes. E93 is a stage and tissue-specific ecdysone-induced primary response gene required in prepupal salivary glands for maximal expression of both ecdysone-induced and cell death genes [10]. Consistent with a previous report [7], we detected increased expression from 16 to 23 hrs APF of the pro-death genes ark, drone and crq. Genes detected but expressed at low levels (E93, rpr and iap2) were analyzed further by quantitative RT-PCR and this indicated expression profiles consistent with previous studies [9,101 (Figure 2.1). In general, the gene expression profiles generated by SAGE are consistent with previous reports and can temporally distinguish known upstream transcriptional regulators from downstream death effector molecules. 47 Figure 2.1. Expression of known salivary gland cell death related genes in SAGE libraries. Observed number of SAGE tags corresponding to known salivary gland death related genes (X axis) were converted to frequencies (Y axis) for purposes of comparison. SG16, SG2O and SG23 refer to the 16 hr, 20 hr, and 23 hr SAGE libraries, respectively. The inset of a simplified cell death pathway indicates the relative timing of expression for the genes indicated [9,10]. Real-time quantitative RT-PCR analyses indicated a 14.4-fold increase in expression for E93 between the 16 and 20 hr and timepoints (n 3) and a 14.0-fold increase in expression between the 16 and 23 hr timepoints. For rpr, a 35.1-fold increase in expression was detected between the 16 and 23 hr timepoints (n = 3) and for iap2, a 2.7-fold decrease in expression was detected between the 16 and 23 hr timepoints (n 3). 48 (L N T ag F re qu en cy (ta g c o u n tlt ot al ta gs ) o p a a o a 0 0 CD C,) 2.3.6 Many genes not associated previously with salivary gland PCD are differentially expressed. To identify and characterize additional genes expressed differentially prior to salivary gland PCD, we conducted pairwise comparisons between SAGE libraries and associated the differentially expressed genes with biological annotations. In the 16 hour versus 23 hour comparison, we found 522 (12.1%) transcripts upregulated significantly (P 0.05) and 331 (7.7%) transcripts downregulated significantly (P 0.05). Together, these transcripts account for almost 20% of all transcripts expressed in the salivary glands during these two stages. In the 16 hr versus 20 hr and 20 hr versus 23 hour comparisons, we found 288 (7.0%) and 459 (11.2%) transcripts significantly upregulated as well as 255 (6.2%) and 287 (7.0%) transcripts significantly downregulated. Table 2.1 includes a subset of the differentially expressed genes annotated previously [26], sorted here by functional category. Molecular function annotations use controlled vocabulary Gene Ontology (GO) terms [25]. These terms, along with protein domains [27] were obtained from FlyBase [26], except where otherwise indicated. In Table 2.1, emphasis is placed on genes sharing the expression profile describing the majority of known cell death genes (i.e., upregulated between 16 and 23 hrs AND not downregulated between 16 and 20 hr), and descriptions below refer to the 16 versus 23 hr timepoints unless otherwise noted. Since some of the known cell death related genes, e.g., reaper, were detected at low levels in our libraries, we also conducted direct searches of all SAGE tags and ESTs for genes demonstrated or predicted previously to play a role in autophagy and/or cell death. Relative expression levels were analyzed by quantitative RT-PCR (Table 2.1). Below is a summary of selected classes of differentially expressed genes included in Table 2.1, that are associated with autophagic cell death. 50 Table 2.1. Differentially expressed genes associated with salivary gland autophagic cell death Ta Sequence Protein Synthesis ATATTGTCAA AGCAGGGGGA ATGAAAAACA TGGGAGGATG# TGGGAGGATG# ACCCACGAGC GGGTGTCTCT ATGAGCTATG TTTGAATAAC Ecdysone/hormone AACTGTAATG AACGAGGGAT AGACGGATTC GGTTTATTGT TAGCAACTAG AGTCAAAAGG GATCCAGCCA TGGA1TCATA GCCGAATCTG translation elongation factor translation termination factor translation initiation factor translation initiation factor translation initiation factor translation initiation factor translation initiation factor translation initiation factor translation initiation factor ecdysone- induced protein ecdysone-induced protein ecdysone-induced protein SG16 SG23 p-value Gene GO Id GO Molecular Function 11 24 8.34E-03 Eflgamma 3746 1 9 5.69E-03 CG5605 8079 1 25 5.82E-08 CG3845 3743 0 10 4.12E-04 CG8277 3743 0 10 4.12E-04 eIF-4E 3743 4 15 4.35E-03 CG9769 3743 0 5 I.95E-02 CG10192 3743 0 4 4.22E-02 CG7439 3743 60 81 7.70E-03 eIF-5A 3743 65 0 3.28E-18 Eig7IEd 1103 38 1.99E-239 E1g7]Ef 1371 540 3.09E-58 Eig7JEj 2 36 1.79E-l0 Hr78 4879 2 8 3.64E-02 Hr78 4879 32 532 2.32E-135 CG15505 121 2339 0.OOE+00 CG7592 2 *11 6,83E-03 Eip63F-1 1 *7 2.50E-02 Ep7JCD ligand-dependent nuclear receptor ligand-dependent nuclear receptor 5509 calcium binding 8113 protein-met-S-oxide reductase 51 Ta Sequence SG16 SG23 p-value Gene GO Id GO Molecular Function Transcription Factors TTAAGTTCGT 1 *6 4.79E-02 bun 3702 RNA poi II transcription factor TAGCTGGTGT 1 *8 1.30E-02 EP2237 16563 transcriptional activator TCCAATTCCG 0 *5 2.16E-02 CG9954 3700 transcription factor GAGCAGGAGT 0 *11 2.34E-04 CG3350 3700 transcription factor Signal Transduction CGAATAATCC 3 67 3.03E-19 Akap200 5079 protein kinase A anchoring AGAATCCAAC 0 5 1.95E-02 Trafi TGTACACTTC 0 33 8.IOE-12 Doa 4674 protein serine/threonine kinase CTGCGCTTGT 0 5 1 .95E-02 Doa 4674 protein serine/threonine kinase TAAATAAAGG 2 14 8.24E-04 sktl 16308 l-PI-4-phosphate 5-kinase AGAAGATAAA 0 4 4.22E-02 Ptpmeg 4725 protein tyrosine phosphatase CAAGTAACCA 0 10 4.12E-04 PR2 4713 protein tyrosine kinase TAGCTCTTAG 0 5 l.95E-02 CG16708 17050 D-erythro-sphingosine kinase TGAACGAGGA 1 9 5.69E-03 CG8655 4702 receptor signaling SIT kinase Cell Death EST/RT-PCR 1 8 Dcp-I 4207 effector caspase TTCCGCATAT 4 13 L32E-02 emp 5044 scavengerreceptor GCTTTCGTGT 1 7 2.21E-02 CG12789 5044 scavenger receptor CCCGTTCCAC 2 8 3.64E-02 CG3829 5044 scavenger receptor GGCACCAGTC 4 *0 8.35E-02 debcl 16506 apoptosis activator EST/RT-PCR 1 *4 buf’,5’ 16506 apoptosis activator RT-PCR 1 3 sickle 16506 apoptosis activator 52 Ta Sequence SG16 sc p-value Gene GO id GO Molecular Function Autophagy TAGCGCTTAG 0 30 8.02E-1 1 CG6 194 Atg4/aut2-like; cystrine protease EST/RT-PCR 1 7 CG1643 Atg5; conjugate with AtgI2 ESTIRT-PCR 1 7 CG5429 Atg6/beclinl; binds Atgl4 EST/RT-PCR 1 10 CG10861 Atgl2; ubiquitin type modifier TAAAATTGCT 7 12 1.44E-01 Rab-7 3928 RAB small monomeric GTPase GATCCAGCCC 0 4 4.22E-02 CG11159 3796 lysozyme CATCATCATC 19 566 3.86E-160 CG3132 4565 beta-galactosidase GTTTCTTCCG 3 15 l.53E-03 CG10992 4213 cathepsin B GGCAACGATC 8 43 2.23E-08 caihD 4192 cathepsin D AAATAAATTG 66 240 1.04E-30 CG17283 4193 cathepsin E TTCTTCAACC 0 4 4.22E-02 CG12163 16946 cathepsin F ATGGCAGAGA 5 15 l.04E-02 Cpl 4217 cathepsin L TATGATATAG 58 620 2.63E-139 CpJ 4217 cathepsin L The 16 hr and 23 hr columns indicate the number of tags detected in the corresponding SAGE libraries. An * indicates that the tag number corresponds instead to the 20 hr APF SAGE library. P value refers to the probability that the observed difference in tag numbers is due to random fluctuation [21]. Gene name, Gene Ontology (GO) id, and GO Molecular Function [25] are from FlyBase [26]. Where no GO id is indicated, molecular function information is from FlyBase [26] or Klionsky and Emr [4]. In instances where EST/RT-PCR is indicated in place of tag sequence, the corresponding transcript was detected at insignificant levels in SAGE and/or identified by salivary gland ESTs. In these cases, the values shown represent fold-difference in expression as determined by quantitative RT-PCR analysis. The # symbol identifies an ambiguous tag-to-gene mapping. Genes listed twice (Hr78, Doa, Cpl) were associated with two different SAGE tags corresponding to alternate 3’ ends. 53 Protein Synthesis: Our findings are consistent with the notion that autophagic cell death requires active protein synthesis. We found significant upregulation of one translational elongation factor, one translation termination factor and at least six different translation initiation factors (Table 2.1). Ecdysone-induced and hormone-related genes: We detected multiple ecdysone-induced genes, in addition to those already described, which were differentially expressed prior to salivary gland death. Highly abundant were L71, or Eig71E, members of the late gene family. The functions of the L 71 genes have not been established but they are reported to be induced in late third instar larvae [28]. Their abundance at 16 hr APF and decline by 23 hr APF is consistent with a role during the early larval ecdysone pulse. Eip63F-1, a calcium binding EF-hand family member, and Eip7 1 CD (or Eip28), a protein methionine-S-oxide reductase, both peaked in gene expression at 20 hr APF, similar to the profile we observed for E74 and E75. While Eip63F-1 has been implicated in calcium-dependent salivary gland glue secretion during earlier stages of salivary gland development [28], a role for Eip63F-l or Eip71CD in salivary glands at the prepupal — pupal stage transition has not been described. Similarly, a role for Hormone-receptor-like in 78 (Hr78) at this stage has not been characterized. Transcription factors: Our findings indicate that transcriptional regulators other than the known ecdysone-induced factors may be involved in autophagic cell death regulation. Transcription factors with an expression profile similar to E74 and E75 (Figure 2.1) include bunched (bun), a RNA polymerase II, and EP2237, a transcriptional activator 54 implicated previously in sensory organ development [29]. Also upregulated was Drosophila maf-S, a gene similar to a v-maf musculoaponeurotic fibrosarcoma oncogene family member in humans [26]. Another upregulated transcription factor, CG3350, has no previous associated function. Signal Transduction: We detected increased abundance of genes implicated in multiple different signal transduction pathways, emphasizing the likely complex interplay of signaling pathways in autophagic cell death. One highly induced gene was A kinase anchoring protein 200 (akap200). In general, Akaps function in cyclic AMP-dependent protein kinase (PKA) signal transduction [301. Another transcript significantly upregulated was encoded by Darkener of apricot (Doa), a dual specificity LAMMER kinase [311 that is involved in the differentiation of a wide variety of cell types. Our findings indicate that Doa, in addition to several other differentially expressed kinases and phosphatases identified (Table 2.1), may also be involved in regulating autophagic cell death. Cell Death related genes: Our findings further validate the notion that autophagic cell death utilizes, at least in some contexts, components of apoptotic cell death pathways [7,10,32]. In addition to the cell death genes described previously in the salivary gland (Figure 2.1), we identified additional genes associated, in other tissues, with apoptotic cell death. A second caspase, dcp-], was upregulated transcriptionally in pre-death stage salivary glands. In addition to the CD3 6-related scavenger receptor crq, we detected upregulation of three other CD3 6-related scavenger receptor genes whose function has 55 not yet been characterized. The expression of additional cell death-related genes, death executioner Bcl-2 homologue (debcl or dborg-1), buf/dborg-2, iap-J, dredd and sickle, was detected in salivary glands and showed low level changes or no changes in expression levels (Table 2.1 and Web Supplementary Material). It is possible that these genes play a role in salivary gland death but are regulated primarily at the protein level. Autophagy associated genes: Our results suggest that autophagy associated genes can be regulated transcriptionally and that this regulation is likely integral to the mechanism of autophagic cell death. Known genes involved in autophagy have been defined largely by genetic screens in yeast and include at least 31 autophagy (Atg) genes [33]. Based on other reports [26,32,34,35] and our own BLAST analyses, we identified putative Drosophila orthologs of at least 10 of the Atg genes, and found evidence of expression for at least nine of these genes (Table 2.1). Strikingly induced prior to cell death was CG6 194 (Table 2.1), one of two Drosophila genes similar to Atg4, a yeast gene encoding a novel cysteine endoprotease required for autophagy [36]. Recently, CG6 194 was demonstrated to encode a functional homolog of Atg4 and shown to interact genetically with several members of the Notch signaling pathway [35]. Results of real-time RT-PCR analyses indicated upregulated expression of other Atg genes including CG1 643 (Atg5) and CG10861 (Atg]2). Also upregulated was CG5429, similar to yeast Atg6 and human beclin 1, the latter shown to both induce autophagy and inhibit tumorigenesis [37]. In addition to Atg genes, we found evidence for upregulated expression of Drosophila rab-7, one of several rab gene family members implicated in autophagy in yeast and humans [4]. 56 The terminal phase of autophagy involves autolysosome formation by fusion of the autophagosome with a lysosome, and subsequent degradation of sequestered cellular components. Lysosomal components with upregulated transcripts in pre-death stage salivary glands include lysozyme, beta-galactosidase, and cathepsins B, D, E, F, and L. Our analyses indicate that multiple components involved in autophagy are conserved in Drosophila and likely play a role in ecdysone-induced autophagic cell death in the salivary glands. Unknown genes: In addition to assigning a possible new role to genes already annotated functionally, we have implicated in the autophagic cell death process more than 732 differentially expressed genes with unknown function. Of these, 377 genes were unpredicted and 48 of these genes are represented solely by our salivary gland ESTs. A major challenge is to identify which genes, both previously described and newly discovered, are likely to play an important role in the autophagic cell death process. Below we describe results of one pilot screen aimed at further annotating differentially expressed genes and identifying candidate genes for future functional studies. 2.3.7 Mutant analysis identifies E93 regulated genes in salivary gland cell death. To identify the genes with differential expression that are most likely associated with the autophagic cell death process, we analyzed E93 mutants. E93 expression appears to specifically foreshadow steroid-induced cell death [37] and E93 mutant salivary glands fail to undergo PCD, displaying morphological features indicative of a block in the early stages of autophagic cell death [7]. Further, the ecdysone-induced genes, BR-C, E74, and E75, and the cell death genes, rpr, hid, crq, and drone, are all transcribed at reduced 57 levels in E93 mutant salivary glands [10]. E93 encodes a novel nuclear protein that binds to multiple specific sites on larval salivary gland polytene chromosomes [10]. The map position of crq correlates with an E93 binding site [10] and it may thus be regulated directly by E93. To identify other genes that may be regulated transcriptionally by E93 in salivary gland death, we screened all differentially expressed genes for those with a map position corresponding to E93 binding sites. We identified 43 upregulated genes and 41 downregulated genes corresponding to 39 of the 65 known E93 binding sites (data not shown). To test further whether these genes may be regulated directly by E93, we analyzed their transcription profiles in E93 mutant salivary glands. Since previous studies indicate a role for E93 as a positive regulator of cell death gene expression, we tested genes upregulated significantly at 23 hrs APF. Of 20 confirmed upregulated genes tested, all but one (Soxl4) exhibited a reduction in relative levels of transcription in the E93 mutant background compared to control genes (Figure 2.2). These results indicate that these 19 genes may be regulated by E93, indirectly or directly, and that their expression is thus likely associated specifically with autophagic cell death events. 58 Figure 2.2. Comparison of fold-difference in abundance in wild-type (OreR) and E93 mutant salivary glands. Fold-difference in gene expression between early (16 hr APF) and late (23 hr APF for OreR and 30 hr APF for E93) pre-death stage salivary glands was determined by real-time quantitative RT-PCR. The 30 hr time point was used for E93 mutants to account for any possible effects due to delayed development in this genetic background [101 .Values were normalized to the 16 hr APF time point using Drosophila rp49 as the reference sample (Experimental Procedures). The ark gene was used as a control since recent evidence indicates that ark is not substantially downregulated in salivary glands in the E93 mutant background [38]. The asterisks indicate that the fold difference values for CecB, CG4091, and CecAl in OreR are off the scale (2,766, 206, and 178 fold difference between 16 and 23 hr APF, respectively). 59 Fo ld di ff er en ce in a bu nd an ce 0 0 P. 3 C. ) - 01 0) — I 0 0 0 0 0 0 r — a a a a * * * 0 0 s o— I ‘7 0Q 0c 9 0 G 90 6 ’ lb S @ 0 4 ( n e c ? 9 ‘ 0 0 00 4) 7 1 % n o • — Q T y ’ eQ 9 % 10 99 C -s Ct I EE F n o . ON C 2.4 Discussion. Our study represents the first comprehensive analysis of genes associated with autophagic cell death in vivo. In addition to providing important clues to the molecules involved in this important process, we have also made discoveries that contribute significantly to our knowledge of the Drosophila genome. With respect to the latter, we have provided evidence for the previously undetected expression of more than 1,000 transcripts, including at least 225 overlapping and divergently transcribed transcripts. Our detection of these 225 transcripts is not surprising because current gene finding programs are unable to readily detect overlapping genes [39]. In total, 1,244 different transcripts were expressed differentially prior to salivary gland cell death, and 377 of these did not correspond to predicted genes. Detection of these transcripts illustrates the advantage of the SAGE and EST methods, and demonstrates that these tools are well suited for the discovery of new transcripts. Genes known to be expressed during salivary gland PCD but not detected in our libraries were Ecr, USP, BFTZ-F1 and hid (Figure 2.1 inset). All of these genes possess putative Nia III recognition sites and thus theoretically can be associated with a SAGE tag. However, Ecr, USP and BFTZ-F] act upstream of the primary response genes (i.e., BR-C, E74, E75, E93) and thus may be expressed maximally prior to 16 hrs APF. This interpretation is consistent with Northern analysis of BFTZ-F] [9]. Alternatively, these genes may be expressed at very low levels. Failure to detect hid was not surprising because other detection methods (see Methods) indicate that it is expressed at levels lower than rpr, which was detected only two times at the 23 hr timepoint. Examination of the differentially expressed genes revealed several fundamental properties of the autophagic cell death process. We found that autophagic cell death 61 involves the induction of genes that participate in protein synthesis, transcription, and multiple signal transduction pathways. Several putative novel regulators of cell death, including akap200, were identified in this study. Akaps function in cyclic AMP- dependent protein kinase (PKA) signal transduction, targeting bound PKA to docking sites in organelles or the cytoskeleton [30]. Genetic studies in Drosophila have also implicated akap200 as a negative regulator of Ras pathway signaling [40]. Since Ras pathway signaling has been shown to negatively regulate the expression of hid during PCD [41,42], it is possible there is a relationship between akap200, the Ras pathway and hid during cell death. The embryonic expression of akap200 suggests that such an interaction could exist in the developing embryo. The possible role of akap200 in regulating cell death awaits detailed functional investigation. The degradation phase of autophagic cell death appears to utilize components of the machinery required for autophagy. While autophagic cell death was shown previously to share morphological features with autophagy, there has been no prior connection between the molecules involved in these two processes. We detected upregulated expression of genes similar to those involved in two ubiquitin-like pathways required for autophagy in yeast [43]. Particularly highly induced was a gene similar to Atg4 which encodes a novel cysteine protease. In yeast, Atg4 processes and activates Atg8, a ubiquitin-like protein [43]. Multiple lysosomal enzymes, including cathepsins, were also ugregulated prior to autophagic cell death. Earlier reports suggest a role for Drosophila cathepsin L (Cp]) in digestion [44] and also in haemocytes, where presumably it plays a role in phagocytic degradation [45]. In addition to the salivary glands and embryo haemocytes (data not shown), we detected expression of Cp] in the central nervous system prior to cell death. 62 This observation indicates that cathepsins, in addition to caspases, may be involved more generally in developmentally regulated cell death in Drosophila. There is evidence that, in some systems, cathepsins are specifically translocated to the cytosol and play a non lysosomal role in cell death [46]. The location(s) of cathepsin activity during Drosophila cell death awaits further study. Our analyses showed that multiple genes involved in apoptotic cell death are also expressed during autophagic cell death, supporting the view that these two processes can utilize common pathways or pathway components [7,10,32]. It is reasonable to expect, then, that some of the novel autophagy associated genes identified in this study may also be associated with apoptotic cell death. In addition to similarities, we also revealed likely differences between these two morphological forms of cell death. In particular, genes similar to those involved in autophagy were upregulated in dying salivary gland cells, and these may prove to be useful molecular markers for the autophagic cell death process. We do not expect that these genes would be specifically induced in cells undergoing apoptosis only because the bulk of cellular degradation occurs within a macrophage or neighbouring cell. 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Leist M, Jaattela M (2001) Triggering of apoptosis by cathepsins. Cell Death Differ 8: 324-326. 47. Reed JC (2002) Apoptosis-based therapies. Nat Rev Drug Discov 1: 111-121. 69 Chapter 3. Steroid hormone control of cell death and cell survival: molecular insights using RNAi2 3.1 Introduction Steroid hormones are small hydrophobic signaling molecules that bind to their receptors to control gene expression and initiate the regulation of growth, development, homeostasis and programmed cell death (PCD) [1]. Components of the steroid-regulated PCD transcriptional regulatory cascades in insects and mammals have been well characterized. For example, in vertebrates, steroid hormone glucocorticoids regulate the removal of excess thymocytes during T-cell maturation [2,3]. In insects, the transcriptional cascade induced by the steroid hormone 20-hydroxyecdysone (ecdysone) has been implicated in the activation of PCD in larval intersegmental muscle [4-6], newly eclosed adult central nervous system [7,8], larval salivary glands [9], and larval midgut [10]. Deregulation of the hormonal control of PCD in humans has been associated with various pathological conditions, including cancer and the degenerative disorder Alzheimer’s Disease [1,11,12]. Given the functional conservation of many genes in humans and Drosophila, experiments to identify the genes required for hormonal control of Drosophila PCD will provide not only a better molecular understanding of the process itself, but may also be valuable in the context of human disease treatment and diagnostics. 2 A version of this chapter will be submitted for publication. Chittaranjan S, McConechy M, Hou YC, Freeman JD, and Gorski SM. 2008. Steroid hormone control of cell death and cell survival: molecular insights using RNAi. Submitted in February 2008 to PLOS Genetics; under review. 70 During metamorphosis of Drosophila, two stage-specific sequential pulses of ecdysone activate first the transformation of larvae into prepupae, and then the transformation of prepupae into pupae. The ecdysone pulses regulate the destruction of obsolete larval tissues, and the differentiation and morphogenesis of adult tissues that arise from small clusters of progenitor cells [7,8,13-16]. The first ecdysone pulse occurs at the late third instar larval stage and triggers puparium formation. In addition, the larval midgut undergoes histolysis and is replaced by adult midgut tissue [9,10]. A second ecdysone pulse occurs 10 hrs after puparium formation (APF) and triggers the death of larval salivary glands [9]. Previous studies have identified some of the components involved in the transcriptional cascade upstream of PCD of salivary glands in Drosophila. The ecdysone receptor is a heterodimer of the nuclear receptors ecdysone receptor (EcR) and ultraspiracle (USP) [17]. The heterodimer complex binds to the steroid hormone ecdysone and induces the transcription of the early genes E93 (DNA binding protein), BR-C (zinc finger transcription factor), E74 (ETS-domain transcription factor), and E75 (orphan nuclear receptor) [13,18-22]. The EcR:USP complex and E93, BR-C and E74 proteins in turn activate transcription of several pro-death genes including reaper (rpr), head involution defective (hid) and grim which function similarly to mammalian SMAC/DIABLO, the AFAF-] homologue ark, the initiator caspase drone, and the CD36 receptor homologue croquemort (crq) [14,21,23-30]. The transcription factor E75B is sufficient to repress transcription of the inhibitor of apoptosis protein 2 gene, diap2 [21], while EcR and the CREB binding protein (CBP) transcriptional cofactor are required for diap] downregulation [31]. Functional studies have confirmed that at least EcR, E93, 71 BR-C, hid, ark, drone, CBP (CREB binding protein), Fkh (Fork head), and AP-] (heterodimer of c-Jun and c-Fos) are required for Drosophila salivary gland cell death [9,22,27,31-37]. While the upstream ecdysone signaling cascade and some cell death genes thus have a demonstrated function in this death process, the results of genome scale expression studies [23,24,3 8] suggest that there are many more potential effectors of ecdysone-regulated cell death and cell survival. The Drosophila cell line l(2)mbn [39], derived from tumorous haemocytes, is well suited for studying steroid hormone induced programmed cell death for several reasons. First, treatment of l(2)mbn (also known as mbn2) cells with ecdysone was shown to induce cell death with morphological features of apoptosis (DNA fragmentation, apoptotic bodies) and autophagy [40]. Second, ecdysone treatment induced the expression of the transcription factor BR-C and the caspases Dronc and Drice [41,42] in l(2)mbn cells. And, third, following ecdysone treatment, the knock-down of E93, BR-C and caspases by RNA interference (RNAi) reduced l(2)mbn cell death [41,42], while the knockdown of E74B, E75A, and E75B by RNAi enhanced cell death [42]. These features indicate that ecdysone mediated cell death in l(2)mbn cells is akin, at least in part, to dying larval stage Drosophila salivary glands and midgut. Treatment of cultured Drosophila cells with dsRNA targeting specific genes depletes their corresponding transcripts and has been used as an efficient tool for genome-wide loss of function phenotypic analyses [43-52]. Recent microarray, SAGE and proteomics studies [23,24,38] have identified hundreds of transcripts and proteins that are differentially regulated in Drosophila larval salivary glands immediately prior to ecdysone-induced cell death, but their functions in this process remain untested. Here we 72 analyze the function of 460 of these gene products using RNAi in ecdysone treated l(2)mbn cells, and report the identification of many novel players in the ecdysone signaling network governing cell death and cell survival. 3.2 Materials and Methods 3.2.1 dsRNA design and synthesis. For the initial screen, individual PCR products approximately 700-800 bp in length containing coding sequences for the transcripts to be knocked-down were generated by RT-PCR using 500 ng of total RNA and Superscript one-step RT-PCR kit with platinum taq (Invitrogen). Each primer used in the RT-PCR contained a 5’ T7 RNA polymerase binding site (TAATACGACTCACTATAGG) followed by sequences specific for the targeted genes (see Supplementary Material). RT-PCR products were ethanol- precipitated and the entire product from each reaction was used as template for in vitro transcription reactions. In vitro transcription reactions were carried out using either Megascript T7 transcription kit (Ambion) or T7 RiboMax Express RNAi systems (Promega) according to the manufacturer’s instruction. Synthesized dsRNAs were incubated at 65°C for 30 mm followed by slow cooling to room temperature. The dsRNAs were ethanol precipitated and resuspended in 50 j.il nuclease free water. A 5 jil aliquot of 1/100 dilution was analysed by 1% agarose gel electrophoresis to determine the quality of dsRNA. The dsRNAs were quantitated using a picogreen assay (Invitrogen) and concentrations adjusted to 100 ng/il with nuclease free water. Experimental design is shown in Figure 3.1. 73 Figure 3.1 Overview of RNAi screen design. A set of 460 genes which included known transcription factors, cell death and autophagy genes, as well as genes associated transcriptionally with ecdysone-induced cell death of the Drosophila salivary gland were chosen for this functional study. In our initial screen, cells were treated with ecdysone and dsRNA corresponding to each of these genes. A viability assay (WST-1) was used to identify genes with potential pro-death or pro-survival functions, and microscopy was used to visualize cell morphology. For the reproducible positive hits, a second dsRNA was used to confirm the viability phenotype. The screen identified 7 potential pro-death and 21 pro-survival genes. The RNAi/WST-l screen was repeated with and without ecdysone to determine ecdysone dependency for the 28 identified genes. Lastly, TUNEL/DAPI assays were performed to identify bona fide cell death-related genes in the ecdysone signaling pathway. 74 Figure 11 Prepare dsRNA in 96 well format. Add dsRNA directly to l(2)mbn cells. Add ecdysone (1OiM final). Incubate 72 hours WST-l colorimetric assay (cell viability) Microscopy (cell morphology) 4, For dsRNAs with an effect, repeat with a second non- overlapping dsRNA Phenotype confirmed Identification of genes with potential pro-death (seven genes) and pro-survival effects (21 genes) RNAi screen with ecdyson,,)c. RNAI screen without ecdysone Ecdysone dependent Ecdysone independent potential pro-death and potential pro-death and pro-survival genes pro-survival genes TUNEL1DAPI— Assay Identification of ecdysone dependent and independent genes with cell death related function 75 We generated an additional dsRNA to confirm the observed effects on cell viability. Of the 22 genes that we confirmed by this method, 21 were represented by two dsRNAs that were non-overlapping. One additional gene confirmed by this method, RpLJ3A (CG]475), was represented by two dsRNAs that overlapped by 2lbp. Analysis of this 2lbp by the Off-Target Search Tool [53] indicated no potential secondary targets. The gene CG]3 748 was also included in final genes though it was tested with a single dsRNA due to its relatively small size (342 bp). Using the Off-Target Search Tool, we determined that our dsRNA sequence for CGJ3 748 had 0 potential secondary targets. 3.2.2 Cell culture and ecdysone treatment. 1(2)mbn cells [40] were grown in Schneider’s (Invitrogen) medium supplemented with 10% FBS, 50 units/mi penicillin and 50 jig/mi streptomycin (Gibco-BRL) (hereafter referred to as Schneider’s medium+10%FBS) in 25 cm2 suspension flasks (Sarstedt) at 25°C. All experiments were carried out 3 days after passage and the cells were discarded after 25 passages. 20-Hydroxyecdysone (ecdysone) was obtained from Sigma-Aldrich and resuspended in 95% ethanol at a concentration of 10mM. 3.2.3 Quantitative RT-PCR. Three days after passage, cells were adjusted to 1x106 cells/mi in ESF921 serum free media (Expression systems) and 3x105 cells (333 jil) were seeded into each well of a 24 well plate. After a one hour incubation, 667 jil of Schneider’s medium+10%FBS and ecdysone (10 jiM final) (Sigma) was added to yield 1 ml culture in each well. Treated cells were incubated at 25°C for 24, 48, or 72 hours and 1 ml cultures were transferred to RNAse free eppendorf tubes (Ambion) and cells were pelleted at 1000 rpm for 10 mm. Cell pellets were lysed in I ml Trizol (Invitrogen) and total RNA was extracted according 76 to manufacturer’s instructions. Isolated RNA was treated with RNAse free DNAse and 50 ng of total RNA was used in 15 pl QRT-PCR reactions. QRT-PCR reactions were carried out using the one-step SYBR green RT-PCR Reagent kit (Applied Biosystems) on an Applied Biosystems 7900 Sequence Detection System. Expression levels were calculated using the Comparative CT Method (User Bulletin #2, ABI Prism 7700 Sequence Detection System, Applied Biosystems, 2001) with Drosophila rp49 as the reference sample. To determine the fold change in expression levels of known ecdysone signaling and cell death related genes following ecdysone treatment of l(2)mbn cells, the CT values for each gene were compared to the CT values for the same gene from untreated control cells. Similarly, for the RNAi experiments, CT values for each gene from ecdysone plus dsRNA-treated cells were compared to the CT values from cells treated with ecdysone plus control human dsRNA, and the knock-down efficiency was calculated using the following formula: Knock-down efficiency 100-[(Fold expression of targeted gene in dsRNA+ecdysone treated cells/Fold expression of targeted gene in ecdysone treated cells x 100)]. 3.2.4 RNA interference (RNA1) and cell viability assays. A 33 ti volume of ESF92I media containing 3x104 cells was seeded into each well of a 96 well plate for RNAi screens. Into each well, 500 ng of dsRNA in a 5 pi volume was added, and incubated for one hour at room temperature. The untreated control cells received 5 tl of nuclease free water. After a one hour incubation, the cells received Schneider’s medium+10% FBS containing ecdysone (10 j.tM final) to yield a final 100 pi volume. Cells were incubated for 72 hours at 25°C and 10 il of WST-1 reagent (Roche 77 Scientific) was added. A450-A650 readings were taken after overnight incubation using a 96 well spectrophotometer (VersaMax; Molecular Devices). A450-A650 readings of experimental samples were always compared to A450-A650 reading from cells treated with human dsRNA to control for any non-specific RNAi effects. All samples were analyzed at least in triplicate. In some cases, cell viability was assessed by Trypan blue exclusion assay as well. 3.2.5 TUNEL assay. For the TUNEL assay, RNA1 experiments were carried out as described above except the cells were seeded into each well of 16-well CC2 coated chamber slides (Nunc). After 72 hours of respective treatment, cells received 100 pi of hypotonic solution (75 mM KCI) for 3-5 mm. at 25°C. Cells were then fixed with 3:1 methanol:acetic acid solution and air dried. Cells were washed with lXPhosphate buffer saline (Sigma) and processed with TUNEL using the DeadEnd fluorometric tunel system (Promega). Cells were mounted with Slowfade antifade reagent with DAPI (Invitrogen) and viewed using a Zeiss Axioplan 2 microscope. Images were captured using a cooled mono 12 bit camera (Qimaging) and Northern Eclipse image analysis software (Empix Imaging Inc.) and the number of TUNEL positive cells (green) and number of DAPI positive cells (blue nuclear stain) were visually counted. All samples were analysed with at least two biological replicates, and three images from each replicate were taken using a 40x objective for counting the TUNEL and DAPI positive cells. Percent TUNEL positive cells were calculated as: (TIJNEL positive cells/Total number of cells) X 100. Statistical analyses: Probability p-values were calculated with Student’s t-test using a two-tailed distribution and two-sample equal variance. 78 3.3 Results: 3.3.1 Characterization of ecdysone-induced 1(2)mbn cell death. To validate our experimental system, we conducted cell viability, cell death, transcription and RNAi assays in ecdysone-treated l(2)mbn cells using known ecdysone signaling and apoptosis genes. First, to verify previous findings [40-42] of ecdysone treatment effects on Drosophila l(2)mbn cells, we employed multiple assays over a time course of ecdysone treatment. To assess cell viability, we used the trypan blue exclusion [54] and WST-l cell viability (Roche Diagnostics) assays. Both assays indicated that the majority of cells were non-viable by 72 hours following treatment with 10 uM ecdysone (Figure 3.2A and 1D). To specifically measure cell death, nuclei were stained with DAPI and the percent TUNEL positive cells were determined 72 hours following ecdysone treatment. Our results showed that the control and ecdysone treated cells had 11% and 54% TUNEL positive cells (Table 3.3) respectively, indicating that the reduced cell viability is due, at least in part, to increased cell death. In addition, we used electron microscopy (EM) to examine morphological features of l(2)mbn cells following ecdysone treatment. Consistent with previous reports [40], we observed features representative of apoptosis, autophagy and phagocytosis in the ecdysone treated cells (data not shown). To determine the expression profile of representative ecdysone regulated transcription factors and apoptosis genes in l(2)mbn cells, we employed quantitative reverse transcription PCR (QRT-PCR) and measured transcript levels following 24, 48 and 72 hrs ecdysone treatment. Since we observed features of autophagy after ecdysone treatment, we also quantitated the expression levels of several autophagy genes to determine if their expression was ecdysone regulated in our experimental system. 79 Figure 3.2. Ecdysone signaling and apoptosis genes are differentially expressed and required for cell death in ecdysone treated 1(2)mbn cells. (A) l(2)mbn cells treated with 10 jiM ecdysone showed a >70% reduction in live cells after 72 hours. Dead cells were identified by trypan blue staining and percent live cells were calculated in comparison to untreated control cells. (B) QRT-PCR expression profiling showed that the ecdysone induced genes E75, Br-C, E93, rpr, hid and Drone had elevated levels of expression (at least a 4-fold increase) in ecdysone treated (10 jiM) l(2)mbn cells relative to untreated control l(2)mbn cells. The autophagy genes, DmAtg4b (CG6194), DmAtg6 (CG5429), and DmAtg5 (CG]643), did not show differential expression following ecdysone treatment. Dotted line indicate, fold-expression value for E93 is off the scale (126 and 371 fold expression at 48 hrs and 72 hrs respectively) (C) QRT-PCR analysis of gene transcripts following treatment with the indicated dsRNAs and ecdysone. As shown here, the knockdown ranged between 63% and 90% for the representative gene transcripts tested following 72 hr dsRNA and ecdysone treatment compared to ecdysone treatment alone. (D) Cells treated with dsRNA corresponding to BR-C, EcR, Drone, rpr, and hid showed significantly (pO.O5) increased levels of cell viability and those treated with dsRNA corresponding to diap-] and E75 showed significantly (p<0.05) reduced levels of cell viability compared to cells treated with ecdysone and human dsRNA NM 138278 (negative control). Cell viability was measured by the WST-1 assay (A450- A650). Dotted line indicate, WST- 1 value for EeR is off the scale (OD value of 1.036). WST-1 reading for the control cells without ecdysone treatment was 1.172 in this experiment (not shown). The error bars represent the SD of dsRNAs tested in triplicate. 80 Figure 3.2 A B 60 55120 50 0201-ETreatrrm Q 45 - 100 40Q 356) 60 > 25— 60 4-b 20 40 - 15 -1o 20 u_b 001- 0 24 48 72 Hours of treatment Genes tested C D !BnOdSRNA I do RNA treatment 100 n o 35-I- • 7880 ..g 69/b 1-70 • 633’• 301- 73% 6024 50 45 T 90 / LPeb000t knock-down I 90t 402015-I- -ø I v-I }2010t Q L_ ±30 <u5t BR-C Drone rpr Hid diapi Genes • 24 hrEcd 48hrEcd 72 hr Bed U) 9 @3 t U 03 c_bN — a 2- r C 03 C_ba U) a 2 a a (_) Ci 0 R 0 W a dsRNA 0. ‘0 81 Our QRT-PCR results (Figure 3.2B) indicated that the early transcription factors Br-C and E75 had the relatively highest expression levels at 24 hrs (10- and 13-fold increase in expression, respectively, compared to untreated control cells) and then decreased after 48-72 hours (at 48 hours, 2- and 7.9-fold increase in expression, respectively, compared to control cells). As demonstrated in Figure 3.2B, E93, reaper, drone and hid demonstrated elevated expression levels by 24 hrs (58-, 5.8-, 3.4-, and 2.3- fold increase, respectively), which remained elevated or continued to increase at 48 and 72 hours (at 48 hours, 126-, 36-, 4.4- and 4.7-fold increase in expression, respectively). These observations suggested that the transcriptional cascade for the representative ecdysone signaling and apoptosis genes was similar between ecdysone-treated l(2)mbn cells and dying Drosophila larval salivary glands. Although we detected expression of autophagy genes in l(2)mbn cells, we observed no significant differential expression compared to untreated cells (i.e., below the arbitrarily chosen 2-fold cut-off level) (Figure 3.2B) up to 72 hrs following ecdysone treatment, indicating that the autophagy genes tested were not transcriptionally regulated in this system at these timepoints (Figure 3.2B). To test the sensitivity of our RNAi strategy, we treated l(2)mbn cells with dsRNA corresponding to representative ecdysone signaling (EcR, BR-C and E75) and apoptosis (drone, rpr, hid and diap-]) related genes. First, to determine the knock-down efficiency of RNAi for the genes described above, we measured their expression levels at 72 hrs by QRT-PCR in ecdysone-treated cells with or without dsRNA. For all the genes tested, the transcript knock-down ranged between 62-90% (for examples, see Figure 3 .2C). Next, the WST-1 assay was used to measure cell viability following RNAi and ecdysone 82 treatment. We found that treatment of l(2)mbn cells with ecdysone and dsRNAs corresponding to EcR, BR-C, dronc, reaper and hid resulted in increased cell viability (p0.05) compared to cells treated with a negative control, a human dsRNA NM_i 38278 [55] (Figure 3.2D; Table 3.1). Treatment of l(2)mbn cells with dsRNA corresponding to either E75B or diap-] decreased cell viability significantly (pO.OO1) as assayed by WST-1. We confirmed that the change in viability of the l(2)mbn cells treated with ecdysone and RNAi was due to alterations in cell death by employing the TUNEL and DAPI assays for selected genes (Table 3.3). 3.3.2 RNAi screen identifies novel genes that affect cell survival and cell death. To identify additional genes that functioned in ecdysone-mediated cell death or cell survival, we conducted an RNAi screen. Based on genome-wide transcript and protein expression studies conducted previously in Drosophila larval salivary glands [23,24,38], there are a large number of genes and proteins that could affect ecdysone-mediated PCD but have not been tested functionally. Here, we conducted a systematic study of 460 of these genes, including mainly those genes that showed a significant (p 0.05 and 5-fold difference) increase or decrease in expression levels in salivary glands immediately prior to PCD. These 460 genes included 18 control genes that have been previously associated with either apoptosis or autophagy but were not detected in our SAGE libraries. The WST- 1 assay was used as a primary screen to assess effects of the 460 dsRNAs on cell viability (data not shown). Using this assay, we identified five genes already reported to have a pro-survival role based on a previous RNAi screen [45,47,56]; Table 3.1). In addition, we identified and validated another 23 genes with corresponding dsRNAs that significantly increased or decreased cell viability (Table 3.1, Table 3.2). 83 Table 3.1. Candidate pro-death and pro-survival genes identified by RNA1 and cell viability assay. XR000922. I Sox4,ll,22 (Sox4) RPS6 RPLP1 RPS5 SNX9 Rp13 7 SIN3B RPS6KB 1 PSMD1; RYR2 PSMC1 HRAS p-value HGNC Symbol: Ortholog in compared to Ecdysone human Gene targeted ils dependency predicted/known function (mouse) Control pro-death genes ecdysone receptor, transcription EcR 7.E-05 dependent factor activity NR1H3 Hid 3.E-03 dependent apoptosis BR-C 2E-02 dependent transcription factor activity ZBT12 Nc (Dronc) 2.E-02 dependent caspase activity reaper 1 .E-02 dependent apoptosis Candidate pro-death genes nucleic acid binding, 60S RpLI3A 6.E-05 dependent ribosomal protein L13a Soxl4 7.E-04 dependent transcription factor activity nucleic acid binding, 40S RpS6 b 2.E-03 dependent ribosomal protein S6 nucleic acid binding, 60S acidic RpLPI a 3.E-03 dependent ribosomal protein P1 nucleic acid binding, 40S RpS5 6.E-03 dependent ribosomal protein S5 SH3PXI Li 2.E-02 dependent intracellular protein transport nucleic acid binding, 60S RpL37 5.E-02 dependent ribosomal protein L37 Control pro-survival genes th(diap-1) a 9.E-04 independent anti-apoptosis DNA binding; steroid hormone E75 7.E-04 independent receptor activity Pro-survival genes ATP binding; transcription factor sin3A 3.E-04 independent activity ATP binding; positive regulator of S6K C 6.E-04 independent cell growth Rpn2 a 8.E-04 independent endopeptidase activity ATP binding; endopeptidase Pros26.4 a 9.E-04 independent activity GTP binding, G-coupled Ras85D 2.E-03 dependent signaling, anti-apoptotic NRI Dl 84 HGNC Symbol: p-value OrthoIo in compared to Ecdysone human Gene targeted Hs dependency predicted/known function (mouse) Pro-survival genes Smr a 2.E-03 independent DNA binding; protein binding NCORI Vps32 a 3.E-03 independent carrier activity; CHMP4B ATP binding; endopeptidase Tbp-1 a 4.E-03 independent activity PSMC3 CG13784 6.E-03 dependent unknown protein kinase activity, cell growth, FRAP1, Tor C 6.E-03 independent autophagy mTOR calcium ion binding; ATPase CG33087 7.E-03 dependent activity; LDL receptor activity LRPI tricarboxylic acid transporter Indy 7.E-03 independent activity SLCI3A2 Kap-x3 a 7.E-03 independent protein carrier activity KPNA3 CG7466 9.E-03 dependent receptor binding; cell-cell adhesion MEGF8 Cp 1 1 .E-02 dependent cathepsin L activity; proteolysis CTSL serine-type endopeptidase inhibitor CG13748 I .E-02 dependent activity cpo a 2.E-02 independent mRNA binding RBPMS CG32016 2.E-02 dependent unknown HmgDa 2.E-02 independent DNA binding activity CG15239 4.E-02 dependent unknown transcription factor activity; SoxN 4.E-02 independent protein binding SOX1,2,3 Gene symbols, CG numbers, and functions are from Flybase [57]. The indicated Ortholog symbols are from the HUGO Gene Nomenclature Committee (HGNC). P-values were calculated by comparing the WST-1 reading (A450-A650) of RNAi of the gene of interest to the WST-1 reading of RNAi of the human (Hs) negative control (NM_138278). Ecdysone dependent means that the observed viability effects of RNA1 depended on the presence of ecdysone. Each RNAi treatment had three replicates and the assay was conducted at least twice. Superscript symbols a, b, and c indicate that these genes were identified in other related RNAi screens: a [47]; b [45]; c [56]. 85 Table 3.2. Comparison of RNAi data to SAGE data. Candidate pro-death genes Soxl4 ACCTGCACGC SH3PX1 GCGACGACGA RpS5 GCCGAAGTTG RpLI3A ATCCCACACA RpS6 TCCGTGCTGG RpL37 GCTAATAAAT Control pro-survival genes th(diap- 1) TCTAAAAAGA Pro-survival genes S6K CAATTTAAAA AGAACAACTA TGGGAGCGTG GAAATGTAAA TTTTTCAACT GATTGTGATG 2 1 9 o 2 1 o 0 0 o 0 7 o 0 3 o 4 8 o o 0 o 0 0 o o 6 o o 5 o 0 0 ND death death death ND Ig Gene targeted Sequence Control pro-death genes EcRa Hid BRCa Nc (Dronc) reaper GACATACTTG CATATTCAAG TTTGGAAGCT CAACAACCAC TACCAGCGTT CAGACAGGTG AGCCAACCCA SG16 SG16 SG23 5 0 1 2 1 0 o o 0 3 4 5 3 4 2 8 36 15 o i 15 o i 2 o 1 7 o 2 11 16 14 1 17 19 1 23 24 3 80 151 156 Prediction based on SAGE death death survival survival survival death Survivall death based on RNAi death death death death death death RpLpla GGCTTCGGTC 94 109 204 TCCACCAAAG 0 4 1 57% of the genes predicted to be pro-death’ based on SAGE were by RNAi. E75 death death identified as candidate ‘pro-death’ genes Rpn2 Ras85D Tbp-1 Tor CG33087b Indy CG7466 CG13748b CG32016a Pros26.4 Kap-cL3 sin3A survival survival survival survival survival survival survival ND death death TACACCTTGA TTTGAATTTT CATTAAACCA AAAACGATAA GCATTGGGCT ND survival 0 1 1 19 23 0 1 7 5 1 7 10 2 0 1 ND survival death death ND survival survival survival survival survival 86 Prediction Survivall based on death based Gene targeted Sequence SG16 SG16 SG23 SAGE on RNAI Pro-survival genes Vps32a AAGCCTCTCG 4 2 7 ND survival AGCAAAAGTA 0 1 5 survival AAGCAGCTTT 1 0 1 survival SoxN GCGCAAGGCA 4 1 0 survival survival Smr CAAATCCAAA 7 5 0 survival survival CG13784 CAAACATACC 8 0 0 survival survival HmgD CTGTGGCTCA 8 5 0 survival survival cpo CGAGAAGTAA 9 1 1 survival survival Cpl TATGATATAG 51 24 620 death survival CG15239b 0 0 0 ND CG4091* GGT’PTAAGGA 1 1 102 death no effect 43% of the genes predicted to be ‘pro-survival’ based on SAGE were identified as candidate ‘pro-survival’ genes by RNAi.. First column shows the genes that had potential pro-survival or pro-death effects determined by RNAi and the WST-1 assay. The second column indicates the SAGE tag sequences identified in the SAGE libraries (chapter 2); genes with more than one observed tag (at least in some cases due to alternative splicing) are indicated by symbol a Columns 3, 4, and 5 show the number of SAGE tags observed in the 16, 20 and 23 hr SAGE libraries, respectively. Column 6 indicates our SAGE-based functional prediction and column 7 indicates the actual potential death or survival function of the gene determined by RNAi. A comparison of the SAGE-based functional prediction and observed RNAi screen-based function, where possible, showed that 10/21 genes (48%) behaved as predicted. b indicates that the annotation for these genes has changed since our SAGE analysis in 2003 [24] and, therefore, no SAGE tag sequence data is available. ND indicates that predictions were not made due to no or low numbers of SAGE tags. CG409]* (characterized in chapter 4) exhibited a greater than 100 fold expression difference in the SAGE libraries prior to death but showed no significant effect in our RNAi screen. 87 Table 3.3. Ecdysone dependent and ecdysone independent death-related genes identified by the TUNEL assay. Gene Targeted Ecdysone treatment No ecdysone treatment % dead TUNEL % dead TUNEL Treatment controls cells * Assay p-value cells * Assay p-value No ecdysone; no dsRNA 11 Ecdysone; no dsRNA 54 + NM 138278 56 9 Control Pro-death genes BR-C 13 ++ 4.E-05 Hid 13 ++ 3.E-05 EcR 9 ++ 5.E-03 Nc (Drone) 24 + 3.E-02 Control Pro-survival gene th (diap-1) 77 ++ 4.E-06 Candidate Pro-death Genes RpLP1 34 ++ 1.E-04 RpLI3A 38 ++ 3.E-04 RpL37 29 ++ 5.E-03 RpS5 44 ++ 8.E-03 Soxl4 37 + 3.E-02 S1-I3PXI 47 + 3.E-02 RpS6 54 - 4.8E-O1 88 Gene Targeted Kap-a3 85 ++ 4.E-05 73 ++ 3.E-03 72 ++ 6.E-03 65 ++ 1.E-02 Smr 69 + 2.E-02 Group B (Increased TUNEL positive cells in the absence or cpo 84 ++ 4.E-05 S6K 72 + 2.E-02 Pros26.4 65 + 4.E-02 Group C (Increased TUNEL positive cells only in the absence Tor 62 - 5.E-02 sin3A 64 - 1.3E-01 Cpl 58 - 5.7E-01 17 21 11 17 presence 67 21 of ecdysone) 23 20 27 * Percent dead cells=Number of TUNEL positive cells/Number of DAPI positive cells x 100. P values were calculated by comparing the percent dead cells of each RNAi treatment to the human control (NM 138278) RNAi treatment (++= significant effect with p 0.01; + significant effect with p 0.05; — no significant effect). Ecdysone treatment No ecdysone treatment % dead TUNEL % dead TUNEL Treatment controls cells * Assay p-value cells * Assay p-value Pro-survival Genes Group A (Increased TUNEL positive cells only in the presence of ecdysone) 14 - 1.2E-01 SoxN CG32016 Ras85D - 1.7E-01 - 5.E-02 - 4.5E-0l 1.E-01 of ecdysone) ++ + 8.E-07 5.E-02 3.E-0431 ++ ++ 2.E-03 + 3.E-02 + 4.E-03 89 Twenty-one of these 23 genes were validated with completely non-overlapping dsRNAs and one gene was validated with minimally overlapping (21 bp) dsRNAs (see Materials and Methods). One additional gene, CG]3 748, was also included in our final data set (Table 3.1; see Materials and Methods). In total, our final gene set for further analyses consisted of 21 genes with corresponding dsRNAs that resulted in reduced viability (hereafter referred to as pro-survival genes) and 7 genes with corresponding dsRNAs that resulted in increased viability (hereafter referred to as candidate pro-death genes). Interestingly, our SAGE-based prediction and RNAi screen results comparison (Table 3.2) showed that 48% (10/21) of the genes behaved as predicted. Overall, 6% of the genes from SAGE (28/442; 460 genes tested included 18 control genes not from SAGE) were identified by RNAi to play a potential role in ecdysone induced cell death or cell survival (discussed further in Chapter 5). 3.3.3 Candidate pro-survival genes act in an ecdysone-dependent or ecdysone independent manner. To determine which genes are regulated by the ecdysone signaling pathway, we investigated whether the decreased cell viability phenotype caused by RNAi knock-down of the 21 pro-survival gene products was ecdysone dependent. We treated the cells with dsRNA and assessed cell viability with and without ecdysone treatment. This analysis resulted in the identification of eight ecdysone dependent pro-survival genes (Table 3.1). dsRNAs corresponding to these eight genes reduced cell viability only in the presence of ecdysone and did not affect viability of l(2)mbn cells in the absence of ecdysone. Of the eight genes identified (CGJ3 748, CG33087, CG7466, CGJ3 784, CG15239, CG320]6, Ras85D, Cp]), six were uncharacterized previously. Of these six genes, three (CG]3784, CG15239, CG32016) do not have any recognizable protein domain or predicted gene 90 function (FlyBase) [57]. Two previously characterized genes, Cysteine proteinase-1 (Cpl) and Ras oncogene at 85D (Ras85D), known to play a role in proteolysis and cell survival, respectively, were also identified here as ecdysone dependent pro-survival genes (Table 3.1). dsRNA corresponding to 13 other genes (Table 3.1) reduced the viability of l(2)mbn cells following ecdysone treatment. However, this phenotype, as assessed by WST-l, was also observed in the absence of ecdysone. We initially categorized these 13 genes as ecdysone independent pro-survival genes. However, among this group of genes, dsRNAs corresponding to Kap-a3 and SoxN resulted in different phenotypes, as assessed by cell morphology (Figure 3.3) in the absence and presence of ecdysone. In the absence of ecdysone, Kap-a3 and SoxN dsRNAs did not result in detectable apoptotic bodies (up to 72 hrs), but in the presence of ecdysone and as early as 48 hrs following treatment, the same dsRNAs resulted in a dramatic increase in apoptotic bodies compared to controls (Figure 3.3). This result indicates that while the overall survival effect of these gene products may be ecdysone independent, their mechanism of action differs depending on the presence or absence of ecdysone. 3.3.4 TUNEL assay distinguishes pro-survival genes that inhibit cell death. To determine whether the decreased viability of cells treated with ecdysone and dsRNA corresponding to the pro-survival genes is due to increased cell death, we performed the TUNEL/DAPI assay for representative genes from this category. We treated cells with dsRNA of three ecdysone dependent (CG32016, Cpl and Ras85D) and eight ecdysone independent (Kap-a3, Pros26. 4, Smr, cpo, SoxN, Sin3A, S6K, and Tor) genes in the presence and absence of ecdysone and quantified the percent TUNEL positive cells. 91 Figure 3.3. Cellular morphology of !(2)mbn cells after dsRNA treatment. Cellular phenotypes were visualized 3 days after dsRNA treatment in the presence or absence of ecdysone. The l(2)mbn cells with no ecydsone and no dsRNA (No treatment) were round and uniform in size and shape. l(2)mbn cells treated with ecdysone (not shown) or ecdysone + human dsRNA NM1 38278-negative control changed in shape from round to spindle forms with extensions (t2), large cells with phagocytosed material (c), and apoptotic bodies [examples are indicated by (a’)], RNAi of EcR, Drone and Sox]4 each increased viability of the ecdysone treated cells, but their resulting morphologies were distinct. RNAI of EcR inhibited spindle shape formation, cells remained rounded, and no apoptotic bodies were found. RNAi of Drone inhibited apoptotic body formation, but cells became spindle shaped. Also, signs of necrosis such as inflated and seemingly empty cells and cell fragments were observed (). RNAi of Sox]4 showed few apoptotic bodies and few spindle-shaped cells. RNAi of diap] resulted in formation of numerous apoptotic bodies within 24 hr. RNAi of Rpn2 showed numerous apoptotic bodies in the presence and absence of ecdysone. RNAi of Kap-a3 and SoxN showed a dramatic increase in apoptotic bodies in the presence of ecdysone compared to no ecdysone. 92 (t N o E cd ys on e E cd ys on e E cd ys on e N o Ec dy so ne Ec dy so ne Ec dy so ne Ec dy so ne RNAi of eight genes (CG320] 6, Ras85D, Kap-a3, Pros26. 4, Smr, cpo, SoxN, and 86K) increased significantly the percentage of TUNEL positive cells (p 0.05) in the presence of ecdysone (Groups A and B, Table 3.3), defining a death inhibitory pro-survival role. RNAi of Cp], Sin3A and Tor did not significantly (p 0.05) increase the percentage of TUNEL positive cells in the presence of ecdysone, indicating that their pro-survival effects in this context are likely not due to an inhibition of cell death (Group C, Table 3.3). However, RNAi of these same three genes did result in an increase in percent TUNEL positive cells in the absence of ecdysone compared to the controls (Table 3.3). In contrast, our TUNEL/DAPI assay indicated that knock-down of Kap-a3, SoxN and Smr by RNAi increased TUNEL positive cells only in the presence of ecdysone (Group A, Table 3.3). This result is in agreement with the previously observed increase in apoptotic bodies found only in the presence of ecdysone (Figure 3.4). The reduced viability caused by RNAi of Kap-a3, SoxN and Smr in the absence of ecdysone appears not to be death-related and may instead be due to inhibition of cell growth, differentiation or cell proliferation. RNAi of Pros26. 4, cpo, and 86K increased TUNEL positive cells (p 0.05) both in the absence and presence of ecdysone, confirming them as ecdysone independent negative regulators of cell death. The TUNEL/DAPI assay also confirmed the ecdysone dependent death inhibitory role of CG32016, and Ras85D (Group A, Table 3.3). In summary, based on WST-1 and TUNEL/DAPI assays, we conclude that CG32016, Ras85D, Kap-a3, Smr, SoxN, are ecdysone dependent pro-survival genes that inhibit cell death, and Pros26. 4, 86K, cpo, Tor, Sin3A, and Cpl are ecdysone independent pro-survival genes that inhibit cell death. 94 Figure 3.4. TUNEL assay identifies genes with cell death-related functions. DAPI staining and TUNEL assays were performed 3 days after addition of dsRNA and ecdysone to l(2)mbn cells. The cells with no ecdysone and no dsRNA (No treatment) showed a background level of 9 % TUNEL positivity (Panel A). Ecdysone (not shown) or ecdysone plus the human dsRNA NM_l 38278-negative control resulted in an increase in TUNEL positive cells (56%; Panel B). dsRNA corresponding to diap] (control gene) increased TUNEL positive cells without (not shown) or with ecdysone treatment (77%; Panel C). Ecdysone plus RNAi of Soxl4 (Panel D) or EcR (Panel E) resulted in decreased TUNEL positive cells (37 % and 9%, respectively), whereas ecdysone plus RNAi of a novel gene CG320] 6 (Panel F) increased TTJNEL positive cells (72%) compared to the negative control. 95 N o T re at m en t - o - I C z m CD I m C) m 3.3.5 TUNEL assay validates genes with a pro-death function in ecdysone-mediated l(2)mbn cell death. Our RNAi study identified seven candidate pro-death genes, comprising two 40S ribosomal genes (RpS5 and RpS6), three 60S ribosomal genes (RpLJ3A, RpL37 and RpLPJ), one transcription factor Sox box protein (Soxl4) and one sorting nexin-like gene (SH3PXJ). To determine whether their potential pro-death effects were ecdysone dependent, we performed RNAi assays with and without ecdysone. Consistent with observations [47], dsRNAs corresponding to the ribosomal genes had the opposite effect in the absence of ecdysone, resulting in a significant reduction in cell viability (p 0.000 1) when compared to control cells (data not shown). To confirm the putative pro- death role of the ribosomal genes observed in the presence of ecdysone in l(2)mbn cells, we employed the TTJNEL/DAPJ assay as described above. Knock-down of all ribosomal genes tested, with the exception of RpS6, resulted in a decrease in the percent TUNEL positive cells (Table 3.3) following ecdysone treatment, indicating that Rp85, RpLJ3A, RpL37 and RpLPJ have a pro-death related function in l(2)mbn ecdysone-mediated death. The TUNEL/DAPI assay also indicated that the transcription factor Soxl4, and the sorting nexin-like gene SH3PX] act as pro-death genes (Table 3.3). Therefore, our RNAi study, which employed both cell viability (WST- 1) and cell death T{JNEL/DAPI assays, identified six new genes (RpS5, RpL]3A, RpL37 and RpLPJ, SH3PXJ, Soxl4) required for ecdysone-mediated cell death. 3.4 Discussion We performed an RNAi screen to gain new molecular insights into ecdysone induced cell death and cell survival signaling pathways. We enriched for the identification of ecdysone-dependent genes by targeting genes that were differentially expressed in 97 Drosophila larval salivary glands immediately prior to ecdysone-induced cell death [23,24]. In total, we verified functionally the pro-death effects of six genes and the pro- survival effects of 21 genes, and further characterized their functions on the basis of ecdysone dependency and cell death regulation. Potential off-target effects can be a significant issue in any RNAi screen especially when long dsRNAs are used [58,59]. Although Drosophila does not have interferon responses as observed in mammals, short dsRNAs (19 nt) produced by Dicer processing that are perfect matches to non-target specific transcripts are the likely source of off- target effects [58-61]. To eliminate potential false positives due to off-target effects or experimental noise, we designed a second dsRNA, completely non-overlapping with the first dsRNA in most cases, and repeated our viability assay. For a gene to be considered further, both of its dsRNAs had to produce an effect in the same direction with a p-value of 0.05. These stringent criteria enabled us to produce a highly reliable final list of candidate genes for further study. Knock-down of many genes, including autophagy genes, did not have a significant effect on cell viability. It is possible that these genes do not have an essential death or survival related role under the conditions we tested. However, alternate possibilities include insufficient knockdown by RNAi, long half-life of gene products, and/or the unsuitability of the chosen viability assay (WST-1) to identify the role of these genes. Since our screen was optimized to detect effects of genes that are dependent on ecdysone regulated transcription, we cannot rule out the possibility that additional genes impacting ecdysone-mediated PCD may be detected under different experimental conditions. 98 Our screen was validated by identification of known genes and biochemical complexes with previously established cell survival or cell death phenotypes. For example, Ras85D promotes cell survival in Drosophila by down-regulating hid expression and activity [62,63] in vivo. Consistent with these findings, we discovered that decreased Ras85D transcripts resulted in reduced cell survival in an ecdysone dependent manner, while knockdown of hid resulted in a phenotype of increased cell survival. These results suggest that Ras pathway mediated inhibition of Hid activity may exist in the ecdysone signaling pathway. We also identified Smr, a co-repressor, and dSin3A, a transcriptional regulator, that associate with each other to mediate the transcriptional silencing of the EcR:USP complex. Addition of ecdysone completely dissociates Smr from the EcR:USP heterodimer complex and activates EcR:USP mediated transcription. Elimination of repression by Smr/Sin3A on EcR:USP activity resulted in lethality in vivo [64]. Based on these observations, we predicted that reduced expression of either Smr or Sin3A or both by RNAi in our system would release, as with ecdysone, the repression caused by these gene products on the EcR:USP complex, resulting in increased EcR:USP activation and subsequent increased cell death. As we expected, our cell viability/TUNEL assays indicated clearly that knock-down of Smr transcripts resulted in increased cell death in an ecdysone dependent manner (Table 3.3). The identification of such known ecdysone signaling complexes demonstrates that our assay is a viable method for functional verification and initial characterization of genes involved in ecdysone-mediated deathlsurvival pathways. The predicted or known function of several pro-survival genes identified in our screen (Pros26.4, Rpn2, Tbp-] and Cpl) was associated with protein degradation 99 processes. Under stress conditions, down regulation of gene products associated with protein degradation processes could impair energy production and, therefore, reduce the survival of the cell/organism. The 26S proteasome complex, a major site of protein degradation, is made up of two multi-subunit sub complexes, namely the 20S Proteasome and PA700 (1 9S complex). The identified pro-survival genes, Pros26. 4, Rpn2, and Tbp 1 all belong to the PA700 subunit of the 26S proteasome complex. Proteasome function is required for cell proliferation [65] and silencing the expression of gene products belonging to the PA700 complex by RNAi reduced cell proliferation and induced apoptosis in S2 cells [47,66]. Consistent with these previous findings, our results indicated that Pros26. 4, Rpn2, and Tbp-1 knockdown led to reduced viability of l(2)mbn cells both in the presence and absence of ecdysone. Our TUNEL assay indicated that Pros26. 4 is a death related pro-survival gene while the pro-survival gene Cpl is not cell death related (Table 3.3). In our RNAi screen, the pro-survival genes that were associated previously with protein degradation (as above) or protein transport (Kap-ct) were significantly up-regulated prior to larval salivary gland histolysis [24]. During PCD, anabolic processes are reduced and, therefore, a replenishable source of carbohydrates is unavailable for energy production. Thus, it is possible that ecdysone may activate protein degradation processes in salivary glands to produce energy to complete the death process. Our RNAi screen identified six previously uncharacterized genes (CGJ3 748, CGJ3 784, CG15239, CG32016, CG33087, and CG7466) as ecdysone dependent pro survival genes. The products of CGJ3 748 (serine-type endopeptidase inhibitor activity), CG33087 (calcium ion binding; ATPase activity; low-density lipoprotein receptor 100 activity) and CG7466 (receptor binding; cell-cell adhesion) have predicted functions based on protein domains but CG]3 784, CG]5239, and CG32016 have no sequence characteristics suggesting function. We further characterized CG32016 in l(2)mbn cells by the TUNEL assay in both the presence and absence of ecdysone. Knock-down of CG320] 6 resulted in increased TUNEL positive cells only in the presence of ecdysone, indicating a cell death-related, ecdysone-dependent pro-survival role. We are the first to associate a function with these previously uncharacterized gene products (CG13748, CG13784, CG15239, CG32016, CG33087, and CG7466); additional studies will be required to elucidate their specific positions and functions in response to ecdysone. Based on our TUNEL/DAPI assay, the death related survival function of the pro- survival genes we studied can be grouped into 3 different categories. RNAi of Group A genes (Kap-a3, SoxN, CG320]6, Ras85D and Smr) increased cell death only in the presence of ecdysone, indicating that these genes have a clear death related pro-survival function in the ecdysone signaling pathway. RNAi of Group B genes (cpo, S6K, and Pros26. 4) increased cell death both in the presence and absence of ecdysone treatment. Knockdown of genes belonging to Group C (Tor, sin3A, and Cp-]) increased cell death only in the absence of ecdysone, indicating an alternate gene function, though still related to pro-survival, when ecdysone is present. Further characterization of these genes in relation to ecdysone signaling may provide a greater understanding of the steroid hormone control of PCD. Of the 28 genes that were identified in our screen, seven genes (Table 3.1) were identified as potential pro-death genes. Of these seven genes, five were ribosomal genes. In Drosophila, 38 small (40S) and 49 large (60S) ribosomal proteins have been identified 101 [671; the small ribosomal subunits belong to the eukaryotic pre-initiation complex and the large ribosomal subunits are usually involved in translation. We tested five ribosomal genes in our RNAi screen that were differentially expressed in the Drosophila larval salivary glands immediately prior to PCD [24]. RNAi of both small ribosomal genes (RpS5, RpS6) and large ribosomal genes (RpL]3A, RpL37 and RpLPJ) resulted in increased cell viability of ecdysone treated cells, indicating that these genes may have a pro-death role in the presence of ecdysone. Ecdysone treatment induces transcription of pro-death genes such as BR-C, dronc, rpr and hid, and ribosomal gene products are required for their translation. Thus, knocking down ribosomal gene products by RNAi may affect efficient translation of pro-death genes leading to the observed phenotype of increased viability. However, in the absence of ecdysone, RNAi of these same ribosomal genes had the opposite effect (i.e., reduced viability; data not shown) on l(2)mbn cells, supporting a pro-survival role under this condition. This pro-survival effect is similar to that reported in S2 and Kc cells by others [45,47]. A pro-survival function of ribosomal proteins in the absence of ecdysone is in agreement with the key role they play in protein- synthesis and, therefore, in cell growth and cell proliferation. Our screen identified two additional gene products required for ecdysone-mediated cell death: (i) dSH3PX1, which is involved in intracellular protein transport and resembles a sorting nexin with an NH2-terminal SH3 domain and a central phox homology (PX) domain [68,69], and (ii) Sox box protein 14 (Soxl4), a high mobility group (HMG) box-containing transcription factor related to the mammalian sex determining factor, SRY [70]. dSH3PX1 acts as a binding partner for the non-receptor Cdc-42 associated kinase (ACK) in Drosophila [71]. A similar interaction between 102 ACK2 and SH3PXI (also called SNX9) occurs also in mammals, where further studies showed that phosphorylation of SH3PX1 by ACK2 regulates the degradation of EGF receptor [72]. Thus, it is possible that the knockdown of dSH3PX1 by RNAi in l(2)mbn cells results in decreased cell death through enhanced EGF receptor-mediated cell survival signaling. Alternatively, the role of dSH3PX1 in cell death may be related to its associations with proteins involved in receptor trafficking and/or cytoskeletal rearrangements [731. Our study also identified for the first time a pro-death role for the transcription factor Soxl4. Previously [24] we determined that of 19 genes tested, just two genes, Sox]4 and ark, were independent of E93 regulation in dying larval salivary glands. This previous finding indicates that Sox 14 may act in parallel to E93 or may be acting upstream of E93 in the ecdysone induced cell death pathway. A recent microarray study conducted during Drosophila pupariation further supports this view, as Sox]4 was identified as an ecdysone primary-response regulatory gene [74]. Our preliminary in vivo studies indicate that Soxl4 mutants are embryonic lethal, but tissue-specific analyses using a Soxl4-RNAi construct support a pro-death role for Sox]4 during Drosophila salivary gland cell death (unpublished results). Based on comparison of the HMG box region, Drosophila Soxl4 is most similar to mouse Sox4 and human Sox4, 11 and 22 [70,75,76]. Sox proteins regulate multiple downstream targets and are involved in numerous developmental processes. In particular, human Sox 4 has been implicated in both the positive [77,78] and negative [79] regulation of apoptosis. In contrast to the pro-death role elucidated for Drosophila Sox]4, we found that Drosophila SoxN had an anti-death pro-survival role in l(2)mbn ecdysone-mediated cell death. SoxN has been associated previously with 103 development of the Drosophila central nervous system [801 and axonal patterning [811 In addition, a recent report demonstrating a role for SoxN in the negative regulation of the Wingless signaling pathway in the embryonic epidermis provides precedence for SoxN mediated repression of gene expression [821. We propose, therefore, that Soxl4 and SoxN may function antagonistically to determine cell death or cell survival in response to ecdysone. In summary, we developed an RNAi-based screening system to identify genes that are required for ecdysone-mediated cell death and survival pathways. Our screen identified known and novel components of the ecdysone signaling network that act as pro-death or pro-survival genes. In particular, we have shown that in some cases the function of a gene is dependent on ecdysone, or its mechanism of action is variable depending on the presence or absence of ecdysone. 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CG4091, a microtubule disrupting protein required for cytoskeletal integrity, alters autophagy and lipid metabolism 4.1 Introduction Programmed cell death (PCD) is essential for maintaining homeostasis in all higher organisms, as it provides a means of removing obsolete and damaged cells [1]. Two major forms of PCD have been observed in multicellular organisms [2,3]. Type I cell death, also known as apoptosis, is associated with condensation and fragmentation of chromatin and cytoplasm, activation of caspases, collapse of the cytoskeleton, externalization of phosphatidylserine, the blebbing of membranes, formation of apoptotic bodies, and phagocytosis by neighbouring cells or macrophages [4]. Type II, or autophagy associated cell death (also referred to as autophagic cell death), is characterized by the formation of autophagosomes that engulf cytoplasm and damaged organelles. The autophagosomes subsequently fuse to lysosomes to form autolysosomes where self-degradation occurs by the lysosomal enzymes [5]. Type I and Type II cell death may occur in the same tissue, as was observed in the fungus Dictyostelium discoideum during starvation-induced sorocarp formation [6], in histolysing larval tissues during insect metamorphosis [7-9] and in human diseases such as Alzheimer’s Disease, Parkinson’s Disease [10,11] and cancer [12]. A version of this chapter will be submitted for publication. Chittaranjan S, Kuzyk M, Sandhu H, Wilton J, Devorkin L, Marra M, Morin GB, Gorski SM. 2008. CG4091, a microtubule binding protein required for cytoskeletal integrity, alters autophagy and lipid metabolism. In preparation 115 Intact cytoskeletal arrangement is important for cell integrity, cell division, trafficking of organelles and macromolecules and regulation of important cellular processes such as cell signaling, translation and metabolism. Rearrangement and/or depolymerization of cytoskeletal components such as microfilaments (e.g., actin), microtubules (e.g., tubulin), or intermediate filaments (e.g., cytokeratins and nuclear lamins) have been observed during initial and executional steps of apoptosis [13-28]. In contrast, autophagy depends on intermediate filaments and microfilaments for the initial formation of autophagosomes (for a review, see [13]) and on microtubules (MTs) for the fusion of autophagosomes with endosomes and lysosomes [13,14]. Treatment of starved Chinese Hamster Ovary (CR0) cells with vinbiastine, and primary rat hepatocytes with vinbiastine or nocodazole (two microtubule depolymerizing agents), inhibited fusion of autophagosomes to lysosomes[14,15], indicating the importance of MTs in the process of autophagy. Another cellular process that requires an intact MT network is fatty acid (FA) metabolism. A large-scale proteomics study in plant cells identified several proteins involved in peroxisomal FA metabolism as Tubulin-binding proteins [161. One 72 kDa peroxisomal 13-oxidation protein identified was a hydroxyacyl-CoA dehydrogenase that is concentrated on MTs and facilitates regulated import into peroxisomes [17-191. In another example, MT integrity differentially modified saturated and unsaturated FA metabolism in cultured Rep G2 human hepatoma cells. In this cell type, depolymerization of MTs with vinbiastine, nocodazole, or colchicine but not perturbation of microfflaments (eg. actin) with dihydrocytochalasin B, reduced the conversion of saturated FA into their monoenoates by affecting the activities of FA desaturases [20]. 116 Also, lipid droplets have been observed actively moving along MTs in the cells of Drosophila, fish and mammals, but the functional significance of this motion is unclear [21-24). During the development of Drosophila, the steroid hormone 20-hydroxyecdysone (2OHE) triggers distinct cellular responses, including cell differentiation and programmed cell death [25]. In Drosophila, during metamorphosis, successive pulses of 2OHE at the 3rd instar larval stage and 10-12 hr After Puparium Formation (APF) trigger Type II PCD of larval midgut and salivary glands, respectively [26). The second ecdysone pulse triggers a transcriptional hierarchy in the larval salivary gland. The genes involved in this hierarchy have been identified, and a detailed description of both the hierarchy and the genes involved in histolysing larval salivary glands can be found in several reviews [25,27-29]. During PCD of Drosophila larval salivary glands, extensive rearrangement and depolymerization of the cytoskeletal network has been observed. Two comprehensive studies on the changes in the cytoskeletal arrangements during salivary gland cell death showed reorganization of actin filaments and rearrangement and eventual depolymerization and disintegration of tubulin and nuclear lamins [30-32]. Here we characterize a new gene involved in cell death-associated cytoskeletal rearrangements in the Drosophila salivary gland. We describe an annotated but previously uncharacterized Drosophila gene, CG409], that shows more than a 100-fold increase in expression immediately prior to death in histolysing larval salivary glands and has sequence similarity to human Tumour Necrosis Factor-alpha Induced Protein 8 (TNFAIP8). In Drosophila S2 cells, CG4091 interacts with 13-oxidation proteins that appear to be involved in peroxisomal 13-oxidation, and binds to the cytoskeleton directly 117 or indirectly. We also demonstrate the function of CG4091 in MT depolymerization in the Drosophila salivary gland and its role in MT dependent processes such as autophagy and lipid metabolism. 4.2 Materials and Methods 4.2.1 Probe preparation and embryo in situ hybridization. In situ hybridization to whole-mount embryos using digoxigenin-labeled (Roche) single-stranded RNA probes was performed essentially as described [331 except the embryos were pre-treated with 1:1 mixture of xylene: ethanol for 60 mm after fixing and dehydrating the embryos. Template for RNA probes was generated from a full-length cDNA clone of CG409] (Genome Sciences Centre, BCCA) constructed into pSPORT vector (Invitrogen) using primers with T7 and T3 promoter sequences (CG4091-43F40: TAATACGACTCACTATAGGGCGCAGAAGAAGATCCTCTCA and CG409 1- 557R39: AATTAACCCTCACTAAAGGTTCCATGGCTGCGTTTATGT). Single- stranded anti-sense and sense RNA probes (control) labeled with digoxigenin were synthesized by in vitro transcription using either T7 or T3 polymerase (Roche) as per manufacturer’s instructions. Hybridization was performed in a water bath at 54°C overnight. After hybridization, embryos were mounted in 70% glycerol, viewed using a Zeiss Axioplan 2 microscope, and images were captured using a cooled mono 12 bit camera (Qimaging) and Northern Eclipse image analysis software (Empix Imaging Inc.). 4.2.2 Probe preparation and salivary gland in situ hybridization. The larval salivary glands were dissected from pupae incubated at 18°C for 16 and 23 hrs APF. Salivary glands were fixed immediately with 4% paraformaldehyde (PF) and subjected to whole-mount in situ hybridization with digoxigenin labeled DNA 118 probes. DNA probes were synthesized by a first round of PCR amplification (60°C annealing for 30 sec and 72°C extension for 1 mm) using CG4091-43F40 and CG4091- 557R39 primers. Gel purified PCR product was used to prepare single stranded DNA probes, complementary to anti-sense (control) and sense (experimental) RNA strands, using a second round of PCR in the presence of digoxigenin labeled dTTP with either CG4091-43F40 or CG4091-557R39 primers in separate reactions. Hybridization was performed in a water bath at 43°C overnight. Hybridized salivary glands were mounted in glycerol and viewed and photographed as for the embryo in situ hybridizations. 4.2.3 Real-time RT-PCR. Salivary glands were dissected from animals at 16, 20, and 23 hrs APF at 18°C, placed in Trizol (Invitrogen) reagent, homogenized, centrifuged at 12,000g and immediately processed or stored at -80°C for not more than two weeks. Mid guts were collected from 3” instar wandering larvae, 0, 3, and 5 hrs APF at 25°C and processed immediately using Trizol reagent. Trizol extractions of RNA were carried out as per manufacturer’s instructions (Invitrogen). Primers were designed using Primer Express V software (Applied Biosystems). Reactions were performed in triplicate using the SYBR Green One-step RT-PCR reagent kit on an Applied Biosystems 7900 Sequence Detection System. Each 15 il reaction included 50 ng of DNAse-treated (Invitrogen) total RNA and 0.1 tM of each primer. Melting curve analysis was performed for each run to ensure there was a single major product corresponding to the predicted melting temperature. Results were calculated using the Comparative CT Method with Drosophila rp49 as the reference sample and values were normalized to the 16 hrs APF timepoint (User Bulletin #2, ABI Prism 7700 119 Sequence Detection System, Applied Biosystems, 2001). Drosophila rp49 showed no significant difference in expression at the timepoints studied. 4.2.4 Plasmid construction. Plasmids were constructed using the GATEWAY system (Invitrogen) as follows: A PCR product of the open reading frame (ORF) of CG4091 was amplified from a full length eDNA construct of CG4091 using primers containing AttB land AttB2 sequences. For CG4389 and Thiolase, PCR products of ORFs were amplified from total RNA by reverse transcription using superscript III (Invitrogen) and oligo dT18 (Invitrogen) and then by PCR using proof reading enzyme platinum Pfx polymerase (Invitrogen). PCR products containing AttB land AttB2 sites were cloned into an entry clone, pDONRTM221, (Invitrogen) containing AttP sites. The entry clones were sequenced to verify and confirm that the construct was in the correct orientation, in-frame and had no base pair change during PCR amplification. The entry clones were then used to shuttle the protein-coding region of the genes into GATEWAY expression vectors containing either N-or C-terminal FLAG or N-terminal Myc (Drosophila Genomics Resource Center), which have a constitutive actin promoter to drive the expression of the fusion proteins. Expression of the correct size proteins was confirmed by Western blotting (described below). Primers used: CG409 I PaIl-72F-C-terminal: GGGGACAAGTTTGTACAAAAAAGCAGGCTTCACCATGGCGGACAATGTCTT’CAAGTC CG4091 Pall-644R-C-terminal: GGGGACCACTFGTACAAGAAAGCTGGGTCGATATCTCCCGTTTCCATGGCTG 120 P-CG409 laIl-72F-N-terminal: GGGGACAAGTTTGTACAAAAAAGCAGGCTTCGCGGACAATGTCTFCAAGTCGC P-CG409 lall-644R-N-terminal: GGGGACCACTTTGTACAAGAAAGCTGGGTCTCAGATATCTCCCGTflCCATGGC P-Thiolase_5 5F-N-terminal: GGGGACAAGT’FTGTACAAAAAAGCAGGCTTCAGCCTTCAAAATGTCTGCCGCAAG P-Thiolase46R-N-terminal: GGGGACAAGTTTGTACAAAAAAGCAGGCTTCTCCACGAATCCCGCACCGGT P-CG43 89-51 F-N-terminal: GGGGACAAGTTTGTACAAAAAAGCAGGCTTCTCCACGAATCCCGCACCGGT P-CG43 89-48R-N-terminal:: GGGGACCACTTTGTACAAGAAAGCTGGGTCCTACAACTTCGAGGAGCC 4.2.5 Drosophila cell culture and transfections. S2 cells (Invitrogen) were grown in ESF921 serum free (Expression systems) medium in 25 cm2 suspension flasks (Sarstedt) at 25°C. All experiments were carried out 3-4 days after passage and the cells were discarded after 25 passages. For transfection experiments, 3 .tg of plasmid DNA and 10 p1 of ceilfectin (Invitrogen) were combined in 200 p1 of serum-free Grace medium (Invitrogen) for 30 mm. Immediately prior to transfection, 3 x 106 cells in 800 tl of Grace medium were prepared and incubated with the transfection medium (a total of 1 ml culture) overnight in a 24 well suspension culture plate (Sarstedt). Cells were divided equally into two wells, and received 1 ml of ESF921 serum-free medium. Cells were incubated for another 24 hrs before immunoprecipitation or immunofluorescence experiments. For large scale transfection experiments, the volumes of reagents were increased accordingly but the final concentrations remained the same. 121 4.2.6 Immunofluorescence (IF). Approximately 75-100 t1 of transfected S2 cells were placed into 8 well CC2 coated chamber slides (Nunc) and incubated for at least 30 mm - 4 hrs as required. Cells were either fixed immediately with 4% paraformaldehyde for at least 20 mm or received their respective treatment before fixing. To view mitochondria, cells were incubated in 500 nM MitoTracker red (Invitrogen) in ESF921 media for 30 mm before fixing and the slides were processed the same day. For actin and microtubule disruption experiments, 10 1iM latrunculin B (Calbiochem) for 15 mm or 50 jiM vinblastine sulfate salt (Sigma) for 35 mm were employed, respectively. Fixed cells were washed several times with 1X Phosphate buffer saline (lOX PBS, pH7.4 from Invitrogen) and permeabilized with 0.2% Tx 100 for 5 mm. A standard immunofluorescence protocol with primary and secondary antibody was followed thereafter. Cells were either incubated for 3 hrs at room temperature or overnight at 4°C in primary antibodies anti-Flag mouse (Sigma), anti-Flag rabbit (Sigma), anti-mouse Myc (Roche), or anti-13-tubulin (Hybridoma bank) in a humidified chamber. Incubations in the secondary antibodies anti-mouse Alexa 488 (Jackson ImmunoResearch Laboratories), anti-mouse CY3 (Jackson ImmunoResearch Laboratories), anti-rabbit Alexa 488 (Jackson ImmunoResearch Laboratories) or anti- rabbit CY3 (Jackson ImmunoResearch Laboratories) were always carried out at room temperature for two hours. For phalloidin staining, cells were incubated for 15 mm in a 1:250 dilution (from 6.6 jiM stock) of phalloidin-rhodamine (Invitrogen) just before mounting. After incubations with antibodies, cells were mounted in Slowfade mount (Invitrogen) and viewed with a confocal microscope (Nikon confocal microscope Cl). Images were analysed with EZ-C1 Ver 3.00 software. 122 For tissue IF, salivary glands were dissected into 4% paraformaldehyde and fixed for at least 30 mm at room temperature. Salivary glands were then permeabilized with 1% Triton 100, pre-incubated in 1X PBS (Invitrogen) containing 0.2% Triton and 1% BSA for 1 hour at room temperature. Salivary glands were then incubated in anti-J3-tubulin mouse antibody (E7; Hybridoma bank) at a 1:100 dilution in 1X PBS containing 0.2% Triton and 1% BSA overnight at 4°C in a humidified chamber. A secondary anti-mouse CY3 antibody was used to detect tubulin protein. Mounting and confocal microscopy were conducted as described above for the S2 cell immunofluorescence. 4.2.7 Co-IP and mass spectrometry. For large scale IP experiments, 9 ml of the transfected cultures from 10 flasks (T-25) per expression construct were combined into a 50 ml Falcon tube. IP experiments were carried out at 4°C. Cells were washed with 1X cold PBS and were resuspended in 10 ml (1 ml/flask) of lysis buffer (20 mM Tris pH 7.5, 150 mM NaC1, 1 mM EDTA, NP-40 (0.1, 1, 5 and 10%), 10 mM 3-glycerophosphate, 2 mM Sodium orthovanadate, 10 jig/mL leupeptin, 2 tg/mL aprotinin, 1 mM AEBSF, 10 jig/mL pepstatin A, 10 .tg/ml Leupeptin, 10 ig/m1 Aprotinin). Cells were disrupted by passing through a 21G syringe needle 5 times and the lysates were incubated for 30 minutes on a nutator mixer. Cell extracts were clarified by centrifugation at 20,000 x g for 15 mm followed by passing the supernatant through a 0.45 jLm nylon syringe filter. Clarified extracts were incubated with 100 jtl of a 50% slurry of sepharose 4B (Sigma) per 10 ml lysate to each tube and rocked for 1 hour at 4°C. Lysate preparations with sepharose 4B were centrifuged and the supernatants were transferred to new tubes. To each tube containing supernatant, 40 p1 of 50% anti-FLAG M2 agarose (Sigma) was added and incubated for 3 hrs or overnight 123 at 4°C. Anti-FLAG agarose resin containing immunoprecipitated complex was centrifuged and the beads were washed at least 6X with lysis buffer and once with 50 mM ammonium bicarbonate. FLAG-tagged protein complexes were eluted twice for 30 and 15 mm, respectively at 4°C with 50 il each of 400 jg/ml FLAG peptide (Sigma). Eluates were combined, vacuum dried, resuspended in protein sample buffer (1X MES buffer + 1X protein loading buffer, Invitrogen) and were separated by SDS-PAGE on a 10-20% NuPAGE gradient gel (Invitrogen). Protein bands were visualized by colloidal Coomassie stain and each lane was cut into approximately 12 slices. The slices were transferred into a 96 well plate, reduced with 10 mM dithiothreitol (DTT), S-alkylated with 100 mM iodoacetamide [34,35] and then subjected to in-gel trypsin digestion with 20 iI of 20 ng/p.l per each well overnight at 37°C. Resulting peptides were extracted under basic and acidic (50% v/v acetonitrile, 5% v/v formic acid) conditions. Peptide mixtures were subjected to LC-MS/MS analysis on a Finnigan LCQ (PTRL West) or 4000QTRAP (Applied Biosystems) ion trap mass spectrometers via reversed phase FIPLC nano-electrospray ionization. All MS/MS spectra were queried against Drosophila Ensembi release sequence databases using search engines, Mascot (Matrix Sciences, London, UK) or X!tandem algorithms [36-38]. An in-house web-based database called SpecterWeb was developed to store and process raw mass spectrometric protein identifications (Sun M, Kurzyk, M, and Morin GM, unpublished). We repeated the IP experiment four times with N- and three times with C-terminally flagged CG409 I protein as baits, for a total of seven experiments. Nonspecifically binding proteins that were found in the IPs from cells transfected with vectors only (negative control) were subtracted using SpecterWeb software from the proteins that were identified in the cells 124 transfected with CG409 1 bait constructs. Stringent criteria were employed to assign MS/MS spectra to peptide sequences. Protein identifications had to have 2 or more unique peptides assigned to high quality (at least e-value <-3), manually validated MS/MS spectra. We considered the protein CG4389 as a candidate interaction partner of CG4091 even though it did not meet all of our inclusion criteria. CG4389 peptides were detected in the vector-only negative controls; however, they were observed at greatly reduced abundance compared to the experimental samples, and were observed only in the negative control IPs when a high detergent concentration (10% NP40) was used. For Co-IP Western blot experiments, transfected cells were grown in 3 X 9 ml cultures for each expression construct and the cultures were combined to total 27 mls of culture. Centrifuged cells were lysed with 3 ml lysis buffer (with 0.1 and 1% NP-40) and processed as described above. After elution of immunoprecipitated protein complexes, samples were dried, resuspended in sample buffer (50 mM Tris pH 7.5, 150 mM NaCl, 5 mM EDTA, 1% SDS) and the total eluate in sample buffer was separated by SDS-PAGE using a 10% NUPAGE pre-cast polyacrylamide gel (Invitrogen). Protein bands were analysed by Western blot analysis. 4.2.8 Western analysis. Approximately 25-3 0 jig of total proteins were loaded onto 10% NUPAGE pre-cast polyacrylamide gel (Invitrogen), unless otherwise specified, and separated by electrophoresis using 1X MOPS buffer (Invitrogen). Proteins were transferred to Immobilian PVDF transfer membrane (Millipore) for detection. Blots were processed as described in the LI-COR manufacturer’s protocol: Blots were pre-incubated in Odyssey blocking buffer (LI-COR) and incubated with primary antibodies (anti-FLAG rabbit or 125 anti-Myc mouse; Sigma) dilutions overnight at 4°C with shaking. Blots were then incubated in the secondary antibodies, anti-mouse goat-infrared 800 (IR) (Rockland Immunochemicals) andior anti-rabbit goat IR 700 (Rockland Immunochemicals) for 1 hr at room temperature in the dark. Protein bands were detected using Odyssey Infrared Imaging System (LI-COR Biosciences). 4.2.9 Construction ofpUAST-CG4091 and pUAST-!(2)dii strains. A full length CG4091 cDNA clone constructed in pSPORT vector plasmid (Invitrogen) was digested with Sail and XbaI (New England Biolabs; NEB) and ligated into a pUAST vector (a gift from Dr. Tom Grigliatti, Vancouver, Canada) that was restriction digested with XhoI and XbaI (NEB). A full length cDNA clone of l(2)dtl in pOT2 was obtained from the Drosophila Genomics Resource Center and restriction digested with EcoRl and XhoI. The digested ORF region was ligated with a pUAST vector that was restriction digested with XhoI and EcoRI. Ligated constructs were transformed into DHl0BTlR chemically competent cells (Invitrogen). Transformed cells were grown in 25 ml cultures and the plasmid DNA was prepared using HiPure plasmid purification kit (Invitrogen). Purified plasmid was combined with pTurbo helper plasmid (a gift from Dr. Tom Grigliatti, Vancouver, Canada) at 5:1 ratio to a total of 1 jig/jil (in 5 mM KCI, 0.1 mM NaPO4, pH 6.8) and ethanol precipitated as instructed by the micro injection facility (CBRC Transgenic Drosophila Fly Core, Massachusetts). These plasmid DNA preparations were sent to the CBRC facility for injection into fly embryos. Transgenic flies with red eyes were identified by crossing the injected flies with white eyed w11’8. The red-eyed flies were established as stocks and the chromosome insertion was mapped by crossing with w”8/Dp(1;Y)/; CyO/nub’ b’ noc& lt’ stw3; 126 MKRS/TM6B, Tb’. Initially, 72 strains for l(2)dtl and 60 strains for CG4091 were generated. All the studies were conducted subsequently using the pUAST-l(2)dtl 423 strain for l(2)dtl gene and pUAST-CG4091 or the pUAST-CG4091 29-9 strain, which showed highest levels of expression by QRT-PCR experiments (data not shown). 4.2.10 CG4091 gain-of-function study. For salivary gland tissue-specific ectopic expression, we crossed the D59-Ga14 strain (salivary gland II chromosome driver [39]; kindly provided by Carl Thummel) or w”8; P(GawB)c 729 (salivary gland III chromosome driver; Bloomington stock center) with either pUAST-CG4091 or pUAST-CG4091 29-9 strains, and analyzed the pupal salivary glands from the Fl progeny. 4.2.11 Construction of a CG4091 loss-of-function strain. A fly strain containing a transposable P element in the 3 ‘UTR region of the CG4091 gene was identified and obtained from the Gene Disruption project [40], (now available from the Bloomington Drosophila Stock Center at Indiana University) (y’ w67C23; P(EPgy2)CG4O9]’°6821). The female flies from this strain were crossed with males of genotype y’ w CyO, H(PDelta2-3)HoP2. 1/Bc’, which provides active transposase to excise the P element in fertilized eggs. Female progeny were crossed to male yw; Gla/CyO flies (a gift from Dr. N. Harden, Vancouver, Canada) and male progeny with white and glass (Gla) eyes or male or female progeny with white eye and curled wings (CyO), indicating excision of P elements, were established as stocks (CG4091 */CyO; here * indicates excision of the P element and potential deletion in the CG4091 region). A total of 538 stocks were established and a single fly from each stock was screened by genomic PCR using primers flanking the insertion site (CG4091-1136R: 127 AAGGTTACCGACCCCTTGGA and l(2)dtl 2723R: GCCGGCACACTGCTACTTCT primers). This genomic PCR screen identified a deletion strain Df-C23 (Df-C23/CyO; MKRS; TM6B) whose PCR product was approximately 1.2 Kb (wild type band is approximately 6Kb). Both the CG4091 and l(2)dtl coding regions were deleted in this strain and the Df-C23/Df-C23 flies were lethal at the embryonic stage. This strain was rescued for the l(2)dtl gene by crossing it to several pUAST-l(2)dtl strains. One pUAST l(2)dtl 423 strain rescued the Df-C23 animals based on the observation that the progeny Df-C23/Df-C23; pUAST-l(2)dtl 423/ pUAST-l(2)dtl 423 and Df-C23/Df-C23; pUAST l(2)dtl 42.3/ TM6B were viable. The Df-C23/Df-C23; pUAST-l(2)dtl 423/TM6B strain was confirmed as a null mutant for CG4091 by QRT-PCR analysis for the expression of CG4091 and l(2)dtl. These mutants had no expression of CG409] but did express the l(2)dtl gene; this strain is referred to as CG4091-LOF. To rescue the CG4091 gene (ie. to created a control strain for loss of function studies) in the CG4091-LOF strain, Df-C23; pUAST-l(2)dtl 423/CyO-TM6B strain and Df-C23; pUAST-CG4091’5’/CyO-TM6B flies were crossed and the progeny Df-C23/Df-C23; pUAST-l(2)dtl 423/ pUAST-CG4091’5’ (non-Tubby) were analyzed. This strain is referred to as ‘wild type rescue’ strain. QRT PCR analysis confirmed the expression of CG4091 and l(2)dtl in the ‘wild type rescue’ strain. 4.2.12. MDC and Nile red staining. Salivary glands were dissected in Schneider’s medium (Invitrogen) or ESF921 serum-free medium and were incubated in medium containing 1 j.ig!ml MDC for 30 mm at 25°C. The salivary glands were washed once with medium, mounted in medium and viewed using the Axioplan microscope (filter sets with 365 nM excitation and 397 nM 128 emission). We photographed and analyzed the images as described in the in situ hybridization section. For Nile red staining, salivary glands were dissected in 2% paraformaidehyde and quick fixed for 3 mm or first dissected in ESF921 serum-free medium and quick fixed for 3 mm. Salivary glands were then transferred into 1X PBS containing 0.1% Tween 20 and Nile red (Invitrogen) at 1:500,000 dilution of 1 mg/mi for 3-4 mm, and mounted in the same buffer containing Nile red stain. Lipid droplets were viewed using filter sets with 45 0-490 nM excitation and 515 nM emission in the Axioplan microscope. Images were captured and accumulated lipid droplets were quantitated manually. At least 8 salivary gland images from 8 animals per timepoint were captured using 63X magnification at a nuclear focal plane (i.e., the image was focused on the nucleus). From each image, 3 salivary gland cells were chosen randomly and the fat droplets were counted manually. Measurements of fat droplets per cell were averages calculated analyzing 3 cells from each salivary gland from every animal. 4.3 Results 4.3.1 Expression of CG4091 increases in larval salivary glands and midgut prior to cell death. To quantitate the expression levels of CG409] in larval salivary glands and midgut undergoing PCD, we employed quantitative reverse transcription PCR (QRT-PCR) and measured transcript levels in wild type OreR salivary glands (16, 20 and 24 hrs APF at 18°C; equivalent to 8.5, 11 and 13 hrs APF at 25°C) and in midguts (3rd instar wandering larvae, 0, 3, and 5 hrs APF at 25°C). As demonstrated in Figure 4. 1A, in salivary glands, CG4091 showed elevated expression levels by 20 hrs APF (9-fold increase) and continued to increase dramatically in expression immediately prior to death at 24 hr APF (185-fold increase in expression). 129 Figure 4.1. Expression of CG4091 in dying larval salivary gland and midgut and during embryogenesis. Scale bars in B and D-I equal 100 microns. QRT-PCR results show that CG4091 expression increased dramatically (approximately 185 fold) prior to the death stage (23 hr APF) in larval salivary glands (A). In-situ hybridization of larval salivary glands confirms that CG4091 is not expressed at 16 hr APF but is expressed at the death initiating stage, 23 hrs APF (e.g., arrow head) (B). No staining was detected with the control probe at 16 hr APF or at 23 hr APF (not shown). In larval midgut, CG4091 expression increased when cell death initiated at 0 hrs APF and remained elevated until 5 hrs APF (C). A lateral view of Drosophila embryos at stages 9-10 shows strong expression of CG4091 in the midgut (MG) and cephalic region (D, E; arrow). Lateral view of embryos (F-G) at late stages 13-16 also show expression of CG4091 in the brain (BR), midgut (MG) endoderm and its precursors, and fat body (FB) (G; dotted area). Dorsal view (H-I) at stages 13-16 show staining in brain (BR), midgut (MG), and also oenocytes (OE; arrow heads). H’ shows staining of one oenocyte (OE) cluster from H. The sense strand RNA control probe showed no hybridization to embryos at any stage (not shown). 130 Figure 4.1 C CG4091 expression in midgut z 5 ! riLE1J1 3rd instar 0 hrs APF 3 hrs APF 5 hrs APF wandering Stages B IF of salivary glandsA CG4091 expression in SGs 200 0 1150 50 0 0 l6hi-sAPF 2OhrsAPF 23hrsAPF Stages 131 QRT-PCR experiments indicated that CG4091 is also up-regulated prior to cell death in the larval midgut (Figure 4.1 C). We also verified the expression of the CG4091 gene by in situ hybridization analysis in the larval salivary gland. In accordance with the QRT PCR results, CG409] expression was not detected at 16 hr APF but was detected at 23 hr APF (Figure 4.1 B), correlating with the timing of larval salivary gland histolysis. These observations are compatible with the notion that CG409] plays a role in the PCD of these larval tissues. 4.3.2 Localization of CG4091 transcripts during embryogenesis. To examine the spatial distribution of CG4091 expression during embryogenesis, in situ hybridization analyses were performed on wild type OreR whole-mount embryos using digoxigenin-labeled (Dig labeled) RNA probes. During mid-embryogenesis at stages 9-10, we observed strong expression of CG409] in the midgut and cephalic region (Figure 4.1D-E). In the late stages (stages 13-16), in addition to expression in the midgut endoderm and its precursors, we also observed expression in the developing fat body and oenocytes (Figure 4.1 F-I). No specific signal was detected using the sense strand probe (data not shown). Expression of CG4091 throughout midgut development during embryogenesis suggests a possible role for this gene in the morphogenesis of this structure. In addition, the expression of CG409] in the fat body cells and oenocytes during late embryogenesis suggests that this gene may have a potential role in the development and/or function of the structures that are involved in lipid metabolism. 132 4.3.3 CG4091 facilitates microtubule remodeling and affects the size and distribution of autolysosomes. 4.3.3.1 Loss-of-function study. To determine the function of CG4091 during development, we created a loss-of- function mutant by imprecise excision of P element. Our strategy involved mobilization of a P transposon insertion, EY06821, residing in the 3’UTR of the CG409] gene (Figure 4.2). P element mobilization resulted in a deficiency strain Df-C23, which was identified as a null mutant for CG4091 by genomic PCR and validated by sequence analyses. The neighbouring gene, l(2)dtl, was also found to be deleted in this deficiency strain (Figure 4.2). Homozygous Df-C23 animals are lethal at the embryonic stage and embryonic lethality of l(2)dtl has been previously reported [41]. Therefore, the observed lethal phenotype was probably due to the deletion of the l(2)dtl gene in the Df-C23 strain. To replace the essential l(2)dtl function and thereby create a loss-of-function mutant strain specific for CG4091, we created a pUAST-l(2)dtl 42-3 expression strain which expressed l(2)dtl protein at a basal level (‘leaky’ expression; no Ga14 driver), and used this to produce the following strain, which was viable and developed normally: Df-C23/Df-C23; pUAST- l(2)dtl 423/TM6B (hereafter referred to as CG409]-LOF). We confirmed the expression of l(2)dtl and the loss of CG4091 transcripts in this mutant strain by QRT PCR both in adult flies (Figure 4,2B) and at late pupal stage (not shown). The l(2)dtl expression level in this strain was similar to that detected in the wild type strain w1118. We also created a rescue strain of Df-C23 for both the l(2)dtl and CG4091 genes; Df C23/Df-C23; pUAST-l(2)dtl423/pUAST-CG409]’54(hereafter referred to as ‘wild type rescue” strain) as a control. 133 Figure 4.2: Genomic region of CG4091 and description of its loss-of-function mutant. As shown in A, the CG4091 gene has three transcripts (RA, RB, RC) that encode two proteins. CG409 1 -CDS-RA and CG409 1 -CDS-RB encode the same protein (188 aa) however CG4091-CDS-RC encodes a protein that is slightly larger (210 aa). The CG4091 and l(2)dtl genes are separated by a 78 bp region. The strain EY06821 contained a P element inserted in the 3 ‘UTR region of CG4091 (arrow head). Broken lines indicate the genomic region deleted in the Df-C23 strain generated by the imprecise excision of EY06821. Primers l(2)dtl 2723R and CG4091 1 136R were used to detect the deletion PCR product of Df-C23. The Df-C23 strain has a deletion in both l(2)dtl and CG4091 gene coding regions. As shown by QRT-PCR experiments (B), the rescue strain for the l(2)dtl gene (Df-C23 combined with pUAST-l(2)dtl by genetic crosses; see methods) expresses l(2)dtl transdripts similar to wild type w1118 strain. Fold expression shown is relative to expression in OreR females using rp49 as the reference RNA. 134 Figure 4.2 CG4091-CDS-RC CG4091-CDS-RB CG4091-CDS-RA P-element start start A .4.— Primer:CG4091-1136R 1 Kb B 1(2)dli and CG4091 expression in CG4091-LOF females 2.5 .2 2 C’, U, x 1 0 U- ____ A Primer: L(2)dtl-2723R - : Df-C23 deficiency OreR female W1118 female Fold Expression CG.4091 Fold Expression l2dtl Li CG4091 - LOF-non Tubby CG4091 - LO F-Tubby flies tested 135 Basal level expression of CG4091 (similar expression levels of l(2)dtl and CG409] compared to wild type w’118 in late pupae, based on CT values of QRT-PCR experiment; not shown) bypUAST-CG409]’5was enough to rescue the CG4091-LOF phenotype. Since we were interested in finding the role of CG409] in larval salivary gland cell death, we dissected out salivary glands at various timepoints prior to death and analyzed them for any morphological changes and salivary gland persistence (i.e., survival of salivary glands past the wild type death stage). The salivary glands from CG4091-LOF persisted similarly to wild type (OreR) salivary glands for up to 25-26 hrs APF and histolysed afterwards. However, all of the CG4091-LOF salivary glands dissected and examined visually between 31(1 instar larvae until 26 hrs APF appeared morphologically abnormal (Figure 4.3 B) and some of the salivary gland cells appeared grossly enlarged. The enlarged cells appeared as large ‘empty bubbles’ at lower magnification (xlO). At least 70% of the salivary glands from the ‘wild type-rescue’ strain appeared normal (Figure 4.3D) similar to wild type salivary glands (4.3 C). The remaining 30% of animals showed varying degrees of abnormality in salivary gland appearance and showed defects in the tubulin network as detected by anti-beta tubulin antibody staining. Since the salivary glands appeared grossly abnormal in the CG4091-LOF mutants, we asked whether the cytoskeletal arrangement was disrupted. To examine MTs, we stained the tubulin network of Drosophila salivary glands from wild type OreR, CG409]-LOF and ‘wild type-rescue’ strains with tubulin antibody. Wild type (4.3C) and ‘wild type-rescue’ strains (figure 4.3D) showed a continuous tubulin network. 136 Figure 4.3. Salivary glands from CG4091-LOF mutants are abnormal and show defects in tubulin network. Scale bars shown in A-B and C-E are 100 and 50 microns respectively. Images A-F were captured with a Zeiss fluorescence microscope at xlO (A B) and x63 (C-E) objectives. Salivary glands from ‘wild type-rescue’ strain appear normal (A). CG409]-LOF mutant salivary glands (B) stained for tubulin with anti-beta tubulin antibody, appeared abnormal with some cells grossly enlarged (arrows). The enlarged cells appeared as large ‘empty bubbles’ at lower magnification (xlO objective). At 25 brs APF, the microtubule network of the wild type w’118 (C) and ‘wild type-rescue’ strain (D) is still intact and continuous. In contrast, the CG4091-LOF salivary glands showed a very different microtubule network pattern; most of the cells showed a compacted tubulin network with long microtubules that appeared as fibers (E, arrows) but in some enlarged cells, very little microtubule was observed (F; arrow head). 137 Figure 4.3 C 25 hrs APE; ‘wild type- W1118’ D 25 hrs APF; ‘wild type-rescue’ F - A 23 hrs APF; CG4091-LOF 138 In contrast, the CG4091-LOF salivary glands showed a very different microtubule network pattern; in some enlarged cells, very little microtubule organization was observed (Figure 4.3 F) but most of the cells showed a compact tubulin network with long microtubules that appeared as fibers (Figure 4.3E). These observations suggest that CG409] may be involved in microtubule organization. Since autophagy depends on microtubules for the fusion of autophagosomes with endosomes and lysosomes [13,14], we wanted to determine whether autolysosomes appeared normal (as in wild type) in the CG4091-LOF salivary glands. We confirmed in a previous report [42] that the acidotropic dye, monodansylcadaverine (MDC), which detects autolysosmes, overlapped with the signal derived from GFP-LC3 [43], a transgenic marker of autophagy, in histolysing Drosophila larval salivary glands at 24-26 brs APF (equivalent to 13-14.5 hrs APF at 25°C). We stained salivary glands from wild type, CG4091-LOF and ‘wild type-rescue’ strains at 25-26 hrs APF and observed the MDC-stained structures. In wild type (Figure 4.4A) and ‘wild type-rescue’ strains (Figure 4.4B), MDC positive autolysosomes appeared as punctate structures throughout the cells. In CG4091-LOF salivary glands MDC positive autolysosomes appeared indistinguishable from wild type in most cells; however, in some cells, there appeared to be reduced numbers of autolysosomes (Figure 4.4C). Since the salivary glands were abnormal and the cell membranes could not be defined clearly, we could not reliably quantitate MDC positive autolysosomes per cell in this mutant background. 139 Figure 4.4. CG4091-LOF salivary glands show reduced autophagy in the enlarged cells. Scale bars in A-C are 50 microns. Images A-C were captured with a Zeiss fluorescence microscope and a x63 objective. In wild type OreR (A) and ‘wild type rescue’ (B) salivary glands, MDC positive autolysosomes appear as punctate structures throughout the cells. In the CG4091-LOF mutant, most cells show normal MDC positive autolysosomes (left half of panel C). However, some enlarged cells show dramatically reduced MDC positive autolysosomes (right half of panel B; arrow head) and large vacuole-like structures (arrow). 140 Figure 4.4 141 4.3.3.2 Gain-of-function study. To examine the effects of overexpression of CG4091 in vivo, we used the UAS GAL4 system [44] and ectopically expressed CG409 1 protein in Drosophila salivary glands (hereafter referred to as CG4091-GOF). The CG4091-GOF salivary glands appeared indistinguishable from wild type controls and histolysed in a manner similar to the wild type salivary glands after 25-26 hrs APF at 18°C. We harvested salivary glands from both wild type and CG4091-GOF strains at 20, 23, 25 and 26 hr APF and examined the tubulin network by antibody staining. The tubulin network on the surface of the wild type salivary glands was still intact and continuous up to 23 hr APF (Figure 4.5A), but thinner and less regular at 25 brs APF (Figure 4.5B). In contrast, salivary glands from CG409]-GOF animals showed an irregular and discontinuous tubulin network as early as 23 hr APF (Figure 4.5C) and in some cases, small holes in the tubulin network were also observed (Figure 4.5C). At 25 hr APF, extensive disruption, possibly due to depolymerization of the tubulin network, with clusters of depolymerized tubulin aggregates were apparent. In these salivary glands, large patches without staining indicated that tubulin was not present in these areas (Figure 4.5D). Since overexpression of CG4091 protein appeared to enhance the disruption of the tubulin network, we investigated whether overexpression of CG409 1 had any effect on autophagy. We used salivary glands from the wild type strain crossed with the salivary gland driver strain as a control. 142 Figure 4.5. Overexpression of CG4091 is sufficient to disrupt the tubulin network in dying salivary glands. Scale bars in A, B, C and D equal 20 microns and in A’, B’, C’ and D’ equal 5 microns. Images A-D were taken with a Nikon confocal microscope and shown is a single Z slice. Panel A and B (A’ and B’ are enlarged views) show a surface view of the wild type salivary gland stained for tubulin (using an anti-beta tubulin antibody) at 23 hr and 25 hr APF, respectively. At 23 hr APF, tubulin staining showed an intact and continuous network when viewed from the surface. At 25 hr APF, the tubulin network appears thinner and less regular than 23 hr APF. Panel C and D (C’ and D’ are enlarged views) show a surface view of salivary glands overexpressing the CG409 I protein. Tubulin staining using shows an irregular, disrupted and depolymerized tubulin network with small holes (arrow head) at 23 hr APF (C and C’). The surface tubulin network shows extensive depolymerization at 25 hr APF (D and D’) and tubulin was not detected in patches in these salivary glands (arrows). 143 Figure 4.5 C — 23 his AIFz (G4091-GOF x.y:20 urn 144 We dissected salivary glands from the CG409]-GOF strain at 16-26 hr APF, stained with MDC and analyzed them using fluorescence microscopy. In control salivary glands, the MDC positive late autophagic vacuoles were concentrated in 1-2 jim individual punctate structures or 3-5 jim small aggregates distributed in the cytoplasm and the perinuclear region (Figure 4.6A). Similar to what was observed by Mufano et. al. [15] in vinbiastine treated starved CHO cells, salivary glands from the CG4091-GOF strains showed dramatically enlarged (3-25 jim) MDC positive aggregates, mostly in the perinuclear area (Figure 4.6B). Therefore, in salivary glands, overexpression of CG4091 is sufficient to increase disruption of the microtubule network and appears to affect the size and distribution of late autophagic vacuoles. The observations from both loss-of-function and gain-of-function studies indicated that CG4091 is perhaps involved in microtubule polymerization andlor depolymerization events and therefore, involved in microtubule remodeling. In addition, disruptions in the microtubule network caused by mutations in CG409] affect the size and distribution of late autophagic vacuoles in larval Drosophila salivary glands. 4.3.4 Protein-protein interaction studies identify beta-oxidation proteins in CG4091 protein complex. To gain further insights into the function of CG409 1, we performed protein interaction and localization studies. To identify the proteins interacting with CG409 1, we performed seven immuno-affinity purification (IP) experiments where we expressed N- terminally or C-terminally FLAG-tagged CG409 1 as bait protein in Drosophila S2 cells. Protein complexes immunoprecipitated with the bait protein were analyzed by tandem mass spectrometry (MS!MS). 145 Figure 4.6. Salivary glands overexpressing CG4091 display large, aggregated autolysosomes. Scale bars in A-B equal 50 microns. Images A-B were captured with a Zeiss fluorescence microscope (x63 objective). Monodansyl cadaverine (MDC) staining of WT salivary glands (salivary gland Ga14 driver D59 X w1118 strain) at 24 hrs APF shows punctated autolysosomes throughout the cells (A). Most cells of salivary glands from CG4091-GOF show large aggregated autolysosomes that are perinuclear (B; arrows). 146 Figure 4.6 147 We prioritized 27 proteins that co-immunoprecipitated with FLAG tagged CG4091 bait proteins in at least two experiments (Materials and Methods; Table 4.1). Hereafter these proteins are referred to as candidate interaction partners. The presence of these proteins in a CG409 1 protein complex could be due to indirect or direct protein interactions. Three proteins that regulate fatty acid metabolism were identified frequently (Table 4.1) as interaction partners indicating that these proteins likely interact with CG4091 under our test conditions. One of these proteins CG11198, the Drosophila acetyl-CoA carboxylase is a nutrient sensor and directs the regulation of fatty acid synthesis and catabolism [46]. The two most frequent proteins we identified (CG4389 and Thiolase (CG4581)) were predicted to be found in fatty acid beta-oxidation multienzyme complexes in Drosophila [45] as their homologues in mammals and plants form multifunctional enzyme complexes and are required for the last two steps of f3-oxidation in the mitochondria [47,48] or peroxisomes [48]. Both mammalian and plant homologues of CG4389 and Thiolase are known to interact and have a role in the same cellular function; we sought to further investigate their interaction with Drosophila CG4091. First, to validate the direct or indirect protein interaction between CG4389 and CG4091, and Thiolase and CG4091 in our FLAG-tagged CG4091 (bait) immunoprecipitation experiments, we conducted co-immunoprecipitation (Co-IP) Western blot experiments. In this case, we used N-terminally FLAG-tagged CG4389 or N-terminally FLAG-tagged Thiolase proteins as baits and captured Myc-CG409 1 protein from co-transfected Drosophila S2 cells (Figure 4.7A-B). Myc-CG4091 did not immunoprecipitate in the absence of either bait protein (Figure 4.7A-B). 148 Table 4.1. Candidate interaction partners of CG4091. SYMBOL IP with N- Molecular function or C- terminal FLAG construct CG4091 N(4), C(3) autophagic cell death CG43 89 N(4), C(2) long-chain-3 -hydroxyacyl-CoA dehydrogenase activity Thiolase N(3), C(2) acetyl-CoA C-acyltransferase activity; long-chain-3-hydroxyacyl-CoA dehydrogenase activity Nopp 140 N(3), C(2) involved in nucleologenesis CG1 1198 N(3), C(1) acetyl-CoA carboxylase activity; ATP binding CG3074 N(3), C(1) cathepsin B activity Aats-glupro N(2), C(2) glutamate-tRNA ligase activity; proline-tRNA ligase activity CG1677 N(3), C(1) nucleic acid binding; zinc ion binding alphaTub84B N(3), C(1) structural constituent of cytoskeleton; tubulin binding alt N(2), C(2) unknown function CG2691 N(2), C(2) unknown function CG9281 N(2), C(1) ATPase activity, coupled to transmembrane movement of substances pit N(2), C(1) ATP-dependent RNA helicase activity; Cg25C N(3) extracellular matrix structural constituent; structural molecule activity FK506-bpl N(2), C(1) FK506 binding; peptidyl-prolyl cis-trans isomerase activity Mi-2 N(2), C(1) helicase activity eIF-2alpha N(2), C(1) initiation factor activity; GTP binding; tRNA binding Map205 N(2), C(1) microtubule binding 149 SYMBOL IP with N- Molecular function orC terminal FLAG construct l(i)G0020 N(2), C(1) N-acetyltransferase activity Pep N(2), C(1) single-stranded DNA binding Act42A N(2), C( 1) structural constituent of cytoskeleton; ATP binding Aly N(2), C(l) transcription coactivator activity; mRNA binding eIF4G N(2), C(l) translation initiation factor activity CG13096 N(2), C(1) unknown function Chro N(l), C(l) chromatin binding cora N(2) cytoskeletal protein binding; structural constituent of cytoskeleton; actin binding Gapdh2 N(2) glyceraldehyde-3-phosphate dehydrogenase (phosphorylating) activity pen N(l), C(l) involved in apposition of dorsal and ventral imaginal disc-derived wing surfaces Dpi N(2) single-stranded DNA binding; satellite DNA binding CG5516 N(l), C(l) unknown function Gene symbols, CG numbers, and molecular functions are from Flybase [45]. In total, seven immunoprecipitation experiments were performed. N and C in column 2 indicate whether the specific protein was observed in N- or C terminal FLAG tagged CG4091 immunoprecipitation. Number of times specific proteins immunoprecipitated with CG4091 is shown in column 2 in brackets. 150 Figure 4.7. Co-IP Western confirms interactions between CG4091 and fatty acid beta-oxidation multi-enzyme complex proteins. A FLAG-tagged CG4389 or Thiolase was co-expressed with Myc-tagged CG409 1, or FLAG-tagged CG43 89 was co-expressed with Myc-tagged Thiolase in Drosophila S2 cells and protein complexes were captured by an anti-FLAG antibody (M2) bound to agarose beads. Proteins were visualized on Western blots using anti-FLAG antibody (ct-FLAG) or anti-Myc antibody (c-Myc). (A) Co-IP (IP) Western blot (WB) shows co-immunoprecipitation of CG4091 protein (prey protein) only in anti-FLAG immunoprecipitates from cells expressing the FLAG-tagged bait proteins CG4389 or Thiolase (lanes A2 and A3). Myc-tagged Thiolase (prey protein) co-immunoprecipitated with FLAG-tagged CG4389 (bait) (lane A4) as expected since they are known to exist in a multi-protein complex [47,48]. Myc-tagged CG4091 protein was not eluted in the absence of Flag-tagged bait proteins (lane Al, negative control) though it was expressed in the cells (C, WB: x-Myc). (B) Western blot shows the immunoprecipitated (IP) bait proteins, FLAG-tagged CG4389 (lanes B2 and B4) or FLAG-tagged Thiolase (lane B3). (C) Western blot shows the protein expression of bait and prey proteins in the Drosophila S2 cell lysate preparations before immunoprecipitation. 151 IP: a-FLAG WB: a-FLAG Figure 4.7 Flag-CG4389 Genes Flag-Thiolase Expressed Myc-CG4091 Myc-Thiolase Lysates C WB: a-Myc WB: a-Myc WB: a-FLAG WB: a-FLAG + Myc-Thiolase 4 Myc-CG4091 FLAG-CG4389 i 4 FLAG-Thiolase 152 Flag-CG4389 - Genes Flag-Thiolase - Expressed Myc-CG4091 + Myc-Thiolase — A + + + + A2r Al IP: a-FLAG WB: a-Myc B + + MW (KDa) 64 Myc-Thiolase 51 39 Myc-CG4091 B4 97 4 FLAG-CG4389 64 51 4 FLAG-Thiolase __ B3 b + + + + + + We also captured Myc-Thiolase protein using N-terminally FLAG-tagged CG4389 as bait (Figure 4.7A-B), confirming that these two proteins also interact with each other in Drosophila S2 cells. Western blot analysis of the cell lysates prior to immunoprecipitation confirmed protein expression in the cell lysates prior to immunoprecipitation (Figure 4.7 C). Next, we performed co-localization experiments of CG409 1, CG43 89 and Thiolase to determine if these proteins localize in the same sub- cellular compartments. We used N-terminally flagged constructs of CG4389 and Thiolase and co-transfected S2 cells with the N-Myc-CG409 1 construct. To determine the co-localization of CG4389 and Thiolase, we co-transfected S2 cells with the N-Myc Thiolase and N-FLAG CG4389 constructs. The Beta-oxidation protein CG4389 mostly localized to punctate structures (Figure 4.8D, 8G). However, in some cells, we also observed CG4389 in the cytoplasm at low levels (Figure 4.8B, and 80). This cytoplasmic CG4389 staining appeared to show general co-localization with the Thiolase protein (Figure 4.8C). Similar to Thiolase, CG4091 localization was mainly observed in the cytoplasm (Figure 4.8E-F). Cytoplasmic CG4389 appeared to show general co localization with the CG4091 protein (Figure 4.80-I). Since CG4389 is predicted to be a mitochondrial multifunctional enzyme in FlyBase (as of 12 Feb, 2008), we initially expected it to localize to the mitochondria. However, punctate staining of CG4389 did not co-localize with MitoTracker stained structures (Figure 4.8K-L), indicating that it was not localized to the mitochondria under our experimental conditions. 153 Figure 4.8. Immunofluorescence assay showing possible sub-cellular localization of CG4091, CG4389 and Thiolase. Scale bars in A-O are 5 microns and in L’ is 25 microns. The images were taken with a Nikon confocal microscope and shown are single Z slices. Interaction partners Thiolase (A, red), and CG4389 (B, green) showed cytoplasmic and punctate staining respectively in Drosophila S2 cells (A-C). CG4091 (E and H, green) localizes in the cytoplasmic and lamellar areas (L) in the lamellar form cells. CG4389 (D and G, red) localizes in punctate structures (D) in all cells and in the cytoplasmic and lamellar areas (G) in some cells. As shown in Panel G-I, the cytoplasm - localized CG4389 appears to co-localize generally with CG4091 (arrows). CG4389 (J, green) does not co-localize with mitochondria (K, red) (see arrowheads in L and enlarged L’). CG4389 punctates (M, green) are always present in close proximity to tubulin (N, red). 154 Figure 4.8 C merge • 4 F merge 0 merge 155 Close examination of the protein sequence of CG4389 revealed a peroxisomal targeting signal (PTS-1) in its C-terminal end (TGSSKL; underlined sequence indicates PTS-1 sequence). Beta-oxidation of fatty acids occurs either in mitochondria or in peroxisomes. Since CG4389 has a PTS-1 motif and localizes to punctated structures that do not co localize with mitochondria, we speculate that CG4389 is localizing to peroxisomes. In addition, the CG4389 localizing structures that we suspect as peroxisomes were found in close approximity to tubulin (Figure 8M-O) as observed by others [17,19,49,501. Since Thiolase is also a beta-oxidation multifunctional enzyme, we considered it likely this protein would be detected in the mitochondria or peroxisomes, however, we observed this protein in the cytoplasm under our experimental conditions. 4.3.5 CG4091 co-localizes with actin and microtubules in Drosophila S2 cells: CG4091 interacts with CG4389, a protein that is similar to a plant peroxisomal multifunctjonal protein (AAL35606; 33% identity for 725 amino acids) with a 3- hydroxyacyl-CoA dehydrogenase domain. The plant protein binds to microtubules [17], particularly tubulin. In addition, we observed the cytoskeletal structural component alphaTub84B and Act42A and actin binding protein cora and microtubule binding protein Map205 (Table 4.1) as candidate interaction partners of CG409 1 protein. Hence, we sought to determine whether CG409 1 binds to MTs or other components of cytoskeleton in Drosophila S2 cells. To assess whether CG4091 was bound to microtubules and/or actin in S2 cells, we transfected S2 cells with N- or C-terminally FLAG-tagged CG4091 constructs, incubated them in CC2 coated chamber slides and performed localization experiments on fixed cells using CG4091, actin and tubulin probes. Similar to S2 cells grown on a concanavalin-A coated surface [51], S2 cells grown on CC2 coated slides 156 exhibited dramatic changes in their morphology within 30 mm; they attached themselves to the slides, flattened, spread, appeared symmetrical and were described as “lamellar form” cells (Figure 4.9A);. After 2-3 hrs, initial protrusions along the extreme periphery of cells were evident (Figure 4.9B, arrows). After 4-5 hrs of incubation, most cells produced short and long extensions that stained well with phalloidin, indicating that the extensions contain actin filaments (Figure 4.9C, arrows). In lamellar form cells, we observed lower levels of expression of CG4091 in the central region of the cells, and increased expression in the vicinity of the lamellar region (Figure 4.1 OB). Interestingly, in cells incubated for 4-5 hrs, patches of CG409 1 protein were observed along the tapered extensions (Figure 4.IOC-D). Our co-localization experiments in which we used anti-flag antibody to detect CG409 1 protein and rhodamine-phalloidin to detect actin, revealed that CG4091 protein was co-localized with actin mostly in the lamellar area and in the extensions (Figure 4.1OA-D). We observed strong microtubule staining and CG4091 staining in the long protrusions, as detected by anti-13-tubulin and anti-flag antibody, respectively (Figure 4.1 OE-H). To investigate the dependence of CG4091 ‘s sub-cellular localization on actin and microtubules, we treated cells with latrunculin B, a drug that disrupts actin microfilaments, or vinblastine, a drug that causes depolymerization of microtubules. Latrunculin B treatment for 10-15 minutes dramatically disrupted the actin cytoskeleton (Figure 4.101). Although actin disruption reduced CG4091 staining, a considerable amount of CG409 1 staining was still observed in the latrunculin-treated cells (Figure 4.1OJ-L). 157 Figure 4.9. Drosophila S2 cells grown for more than 3 hrs on CC2 coated slides attach, flatten, spread and form short and long extensions. Scale bars in images A-C were 10 microns. Images were captured using a Nikon confocal microscope and shown is a single Z slice. S2 cells were transfected with vector plasmid, grown on CC2 coated slides for 30 mm, 3 hrs or 5 hrs, fixed with 4% paraformaldehyde and stained for Actin with rhodamine-phalloidin. After 30 mm (7A) cells attached themselves to the slides, flattened, spread and formed Iamellae. The cells appeared symmetrical and extensive actin staining was observed in the lamellae (L) area (arrows). This morphology remained for up to 1 hr (data not shown). After 3 hrs, at least 50% of the cells showed short protrusions or long extensions that contain actin filament (7B, arrows). After 4-5 hrs, most of the cells had long extensions around the periphery (7C; arrows). 158 Figure 4.9 A L 30 lUll) C 5hryIOon 159 Figure 4.10. CG4091 colocalizes with the cytoskeleton in S2 cells growing on CC2 coated slides. Panels A-H show untreated S2 cells, while panels I-P show S2 cells treated with lantrunculin B and panels Q-X show cells treated with vinbiastine. Scale bars in A-C , E-G, I-K, M-O, Q-S, and U-W equal 5 microns. Scale bars in D, H, L, P, T and X equal 25 microns. Images were taken with Nikon confocal microscopy and shown is a single Z slice. A cell stained for actin with rhodamine-phalloidin (A, red) and CG4091 (B, green) shows some co-localization of actin and CG4091 (yellow-orange) in the lamellar areas (L) and extended processes (arrow). A cell stained for tubulin, an abundant type of microtubule (MT) (E, red), and CG409 1 (F, green) also show co localization, especially in the long extended protrusions (G, arrow) and around the vacuoles (G, V-arrow head). CG4091 appears as patches along the protrusions and at the tips. Latrunculin B treatment (I-L) disrupts actin (I, red), however, CG409 I (J, green) still localizes in the lamellar areas (L) and along the protrusions (arrows). A latrunculin B treated cell (M-P) stained for tubulin (M, red) and CG409 1 (N, green) depicts intact tubulin network co-localizing to CG4091 protein similar to untreated cells. Disruption of tubulin with vinbiastine (Q-T) does not affect the actin filaments (Q, red) and CG4091 (R, green) is still present in the central area of the cells but only very little CG4091 protein was observed in the extensions (R, arrows). Vinbiastine treatment (U-X) disrupted the tubulin (U, red) filaments but some tubulin filaments were still not affected (U). CG4091 (V, green) localized with the undisrupted microtubules (panel W-X; arrow). In tubulin disrupted cells, localization of CG4091 protein (W, green) was reduced (arrow head). 160 Figure 4.10 A Actin U fltreate(l E Nil Untreated i Actin Lati tinculiii B Ni NV LatiLInCLIlili B Q Actin Viii blast i lie U NI iIIl)Iastilic B CG4091 V F CG4091 (C4091 N ((;4091 (‘(4O91 V ((4091 merge Enlarged -r 0 S 161 Even after disruption of actin filaments, CG409 1 was still evident along the extensions (Figure 4.1OJ-L), indicating a possible association between CG4091 and microtubules. Also, co-staining for CG4091 and tubulin in latrunculin-treated cells showed that CG4091 localized to the microtubules (Figure 4.IOM-P), and particularly was in the vicinity of vacuoles and in the long tapered extensions (Figure 4.1 OM-P). Vinbiastine treatment for 30-40 minutes did not affect the CG409 1 localization except in the tapered long extensions. Most of the long extensions were absent in the vinblastine treated cells (Figure 4.1OQ-T and U-X). Co-localization of CG4091 and phalloidin was clearly observed in the vinblastine treated cells (Figure 4.1OQ-T), except in the protrusions, where CG409 1 expression was reduced. Vinbiastine treatment disrupted most of the tubulin filaments, but some remnants of tubulin filaments remained (Figure 4.1 OU), and localization of CG409 1 along these remnants was observed (Figure 4.1 OU-X). These observations indicate that CG409 1 binds to both microtubules and actin, particularly in the newly extended protrusions of S2 cells. 4.3.6 CG4091 is sufficient to increase the number of lipid droplets in Drosophila salivary glands. Since CG4091 interacts with CG4389 and Thiolase (which are fatty acid beta- oxidation proteins) in S2 cells in culture, we explored whether CG409 1 affected lipid metabolism in vivo. Nile red, a stain that specifically accumulates in neutral lipids [52], has been successfully used by others in C. elegans [53] and Drosophila [54,55] to determine defects in lipid metabolism. First we established the profile of lipid droplet accumulation in the wild type salivary glands from pupae staged between 0-24 hrs APF using Nile red (Figure 4.1 lA-F). 162 Figure 4.11. Nile red staining of wild type salivary glands. Scale bars in A-F equal 50 microns. Images A-F were captured with a Zeiss fluorescence microscope (x63 objective). Wild type control (WT; SG Ga14 Driver crossed with wild type strain w”8) salivary glands from pupae staged at 0, 8, 14, 16, 20 and 24 hr APF were dissected out and stained with nile red, a stain specific to neutral lipids. A large number of lipid droplets were observed at 0 and 8 hr APF (A-B), which decreased between 14-16 hr APF (C, D) (p0.01). Lipid droplet accumulation appeared to slightly increase again at 20 hr APF and remained at approximately the same levels until salivary glands histolysed (E, F). Lipid droplets/cell were counted (see methods) at the same developmental stages in multiple animals (n 8) and are shown in panel I. 163 Figure 4.11 c l4hrs WT Fat droplets in wild type salivary glands during pupal development I 160 =140 120 -. — C 60 20 0 --I * * pO.O1 * 0 hrs APF 8 hrs APF 14 hrs APF 16 hrs APF 20 hrs APF 24 hrs APF Pupal stage 164 In wild type salivary glands, Nile red-stained lipid droplets were observed at elevated levels at 0 and 8 hrs APF [117 ± 30 and 80 ± 17 respectively] (Figure 4.1 lA-B; Figure 4.111). These droplets decreased in numbers between 14-16 hrs APF [37 ± 26 and 32 ± 21 respectively], (Figure 4.I1C-D, I), slightly increased again at 20 hrs APF [62 ± 36] and remained at the same levels [53 ± 22 at 24 hrs APF; Figure 4.111] until SOs histolysed (Figure 4.1 1E-F, I). Next, we examined the salivary glands from CG409]- LOF for lipid droplets, at 1, 5, 15-16, and 23-24 hrs APF. Lipid droplets were evident throughout the development in the salivary glands but the tissue was so grossly abnormal that we could not reliably quantitate the lipid droplets (Figure 4.12A-B). Thus, we next examined the salivary glands from our CG4091-GOF strain and determined the profile of lipid droplet accumulation in this tissue at the same timepoints as wild type. Salivary glands from the CG409] -GOF strain showed excessive levels of lipid droplets throughout the stages we examined (for an example, see Figure 4.12). Also, quantitation of lipid droplets in CG409] overexpressing salivary glands at 16 hrs APF, a stage that exhibited the lowest levels of lipid droplets in wild type salivary glands, demonstrated approximately 342 ± 47 droplets/cell, an approximately 10 fold increase in lipid droplet accumulation compared to wild type (Figure 4.120). This observation suggests that CG4091 expression is sufficient to result in an increased number of lipid droplets in Drosophila salivary glands. 165 Figure 4.12. Overexpression of CG4091 is sufficient to increase lipid droplets in larval salivary glands. Scale bars in A-F equals 50 microns. Images A-F were captured with a Zeiss fluorescence microscope (x63 objective). ‘Wild-type rescue’ (rescue strain of CG409]-LOF) (A-B), CG4091-LOF (C-D), wild type (WT) (E), and CG4091-GOF (F) salivary glands were dissected out at 0-24 hrs APF and stained with nile red. CG409 1 -LOF salivary glands showed lipid droplets throughout development. Panels C D show examples of CG4091-LOF salivary glands at 1 hr and 24 hrs APF respectively as examples. Salivary glands were grossly enlarged and abnormal and lipid droplets were not quantitated. In CG4091-GOF salivary glands, increased numbers of lipid droplets were observed throughout the timepoints examined (see methods). At 16 hrs APF, very few lipid droplets were observed in wild type salivary glands (E), but many were observed in CG4091-GOF glands (F). Lipid droplets/cell in salivary glands overexpressing CG4091 remained high throughout pupal development; quantitation of droplets at 16 hrs APF in CG4091 overexpressing salivary glands (G) demonstrating relatively high levels (pl .8x1 0) of lipid droplets/cell. 166 Figure 4.12 I hr 1’F; Vild hpc—rc%due C I hr APF; (G4091-LOF B 24 hrs APF Wild type-rescue D 24 hrs APF; CG4091-LOF G Fat droplets in wild type and CG4091-GOF — salivary glands 350 300 i8x1O7 250 200 150 100 CG4091-GOF 167 4.4 Discussion. To identify the genes that were transcriptionally regulated in Drosophila salivary glands during ecdysone-induced PCD, we previously constructed serial analysis of gene expression (SAGE) libraries [56] from SGs collected at 16 hrs APF at 18°C (approximately around the time ecdysone pulse occurs), just after the ecdysone pulse (20 hrs APF at 18 °C) and immediately prior to death (23 hrs APF at 18°C) [57]. We observed more than a 100-fold increase in expression of CG409] in this gene expression study and confirmed this finding by QRT-PCR (Figure 4.1A). Genes that are generally involved in ecdysone-induced cell death may be differentially expressed in more than one tissue undergoing ecdysone-induced PCD. Therefore, we determined the expression profile of CG4091 in larval midgut (at 3’ instar, 0, 2, 4 and 5 hrs APF at 25°C), as it undergoes cell death associated with autophagy [58], unpublished personal observation) after the ecdysone pulse at the third instar stage [26]. We observed increased expression of CG4091 in larval midgut only during the death stage (0-5 hrs APF at 25°C) and not at earlier stages (3d instar) (Figure 4.1C). Using S2 cells, we found that addition of ecdysone did not directly upregulate CG4091 expression in the system (data not shown). However, up-regulation of CG4091 in both larval midgut and salivary gland during death stages suggested that CG4091 plays a role in PCD in these larval tissues. Determining a gene’s pattern of expression is a key step towards understanding its function during development. Whole-mount embryo in situ hybridization is a well established approach for determining precise temporal and spatial gene-expression patterns [59-61]. Tomancak et a!, 2007 [61] performed extensive genome-wide analysis of patterns of gene expression during Drosophila embryogenesis, which showed the 168 functional relationship of expression patterns. CG4091 in situ hybridization of Drosophila embryos showed expression of this gene initially in the endodermal cells, corresponding to the invaginating posterior midgut primordium and in the anterior midgut primordium (Figure 4.1D-G; I). In late embryogenesis CG4091 expression was observed in the fat body and oenocytes (Figure 4.1G-H), These expression patterns suggest that CG4091 may play a role during organogenesis of these tissues. The larval fat body and midgut are important organs in lipid metabolism. Large amounts of fat droplets are stored in these tissues when the larvae feed, and are catabolized and used for energy when the animal stops feeding at late 3’ instar stage and during pupation ([43]; personal observation). During starvation, stored lipids from the fat body are released into the haemolymph [62,63]. Insect lipids released from the fat body are then processed in oenocytes, which are hepatocyte-like cells [64]. Expression of CG4091 in midgut, fat body and oenocyte during embryogenesis, interaction of CG409 1 protein with fatty-acid 13-oxidation proteins, and increased levels of fat droplets in salivary glands of CG4091- GOF animals suggest that CG409 1 has a direct or indirect role in fatty acid metabolism. Further study in this direction is necessary to understand the specific mechanism of CG4091 in fatty acid oxidation. To determine the function of CG4091 in PCD of Drosophila larval salivary glands, we created a loss-of-function mutant and gain-of-function mutants to express CG4091 in tissue specific manner. Both CG409]-LOF and CG4091-GOF animals developed normally, and salivary glands from both strains developed as wild type OreR or w1118 salivary glands, histolysing after 26 brs APF at 18°C. However, the salivary glands from CG4091-LOF looked grossly abnormal. Our observations (Figure 4.3, Figure 4.5) using 169 tubulin staining indicated that CG409] was possibly involved in tubulin polymerizationldepolymerization and therefore, in microtubule remodeling. We also explored whether CG409 1 could also alter the structures of intermediate or late autophagic vacuoles. We observed enlarged intermediate-late autophagic vacuoles that stained with MDC in CG4091-GOF salivary glands (Figure 4.6A-B) at a timepoint (23- 26 brs APF), which coincides with the increased disruption of the tubulin network observed in the same strain. The MDC-labeled large-autophagic vesicles showed an altered distribution where they aggregated around the nucleus (Figure 4.6B). This overexpression phenotype of CG4091 appears very similar to the phenotype that was observed by Mufano et a!. [15], in which vinblastine treatment was used to disrupt the tubulin network, which is then affected the fusion of autophagosomes to endosomes and lysosomes in starved CR0 cells. The authors suggested that these large intermediate-late stage autophagic vacuoles in starved CHO cells treated with vinblastine were late autophagosomes that acquired acidifying H+-ATPase, and therefore stained with MDC. Their observation suggests that CG409] is disrupting the tubulin network at late stages prior to death, and this is possibly affecting the size of intermediate-late stage autophagic vacuoles. However, we were not able to assess whether the autophagy process was completed in the salivary glands ectopically expressing CG4091. Experiments are now underway to determine whether autophagosomes are fusing with lysosomes in the CG4091-GOF mutant by recombining the GFP-LC3 marker into this strain. I will examine the salivary glands expressing both GFP-LC3 and CG4091, stain with lysotracker (a marker for lysosomes and autolysosomes) and determine whether fusion occurs in these glands in comparison to wild type. 170 We did not see disruption in the tubulin network in salivary glands before 23 hrs APF. Also, in S2 Drosophila cells, we did not see depolymerization of tubulin when CG4091 was ectopically expressed under the culturing conditions we employed. It is possible that CG4091 needs a co-factor for depolymerizing the tubulin network, which becomes available only after 23 hr APF in Drosophila salivary glands. For example, a candidate protein for co-factor activity of CG409 1 may be stathmin, a microtubule disrupting protein that showed increased expression in larval salivary glands undergoing PCD [57]. Another candidate protein that we identified in CG4091 Co-IP experiments is MAP2O5, a microtubule binding protein (Table 4.1). It would be intriguing to test these candidate proteins in the future to determine whether there are any synergistic effects of CG4091 and MAP2O5 or stathmin in depolymerizing tubulin. Our immunoprecipitation studies (IP and tandem MS) with FLAG-tagged CG4091 protein as bait revealed that CG4091 interacts with fatty acid oxidation proteins CG4389 and Thiolase directly or indirectly. These two proteins were identified as interacting proteins with both N terminus and C terminus FLAG-tagged CG4091 (Table 4.1). To validate the interaction of CG4091 with these two proteins, we employed Co-IP and Western blot analysis using FLAG-tagged CG4389 or Thiolase as baits and Myc-tagged CG4091 as potential prey. Myc-tagged CG4091 protein was co-immunoprecipitated only in the presence of FLAG-CG4389 or FLAG-Thiolase (Figure 4.7), confirming an interaction between these proteins. As expected, co-immunoprecipitation of Myc Thiolase was also observed with FLAG-CG4389; previous studies have demonstrated that these two proteins interact within a multi-enzyme complex [47,48]. Based on our Western blot analyses, a relatively smaller amount of co-immunoprecipitated prey protein 171 (Myc-CG4091) was observed compared to the amount of immunoprecipitated FLAG CG43 89 or FLAG-Thiolase detected. There are multiple possible explanations for the observed stoichiometry. For example, the proteins may have multiple interaction partners, the interactions may be weak, and/or the interactions may depend on particular cellular conditions, the different relative pool size of the ectopically expressed proteins, and/or localization to specific subcellular compartments. In addition, CG4389 and Thiolase may not be interacting directly with CG409 1 and/or may require additional protein(s) for a stable interaction. Thus, the endogenous levels of CG4389 and Thiolase or any additional interacting protein(s) may limit the amount of bound CG409 1 in the ectopic bait protein complexes. These potential explanations are consistent with the known role of CG4389 and Thiolase in a multi-enzyme complex [47,481 and the observed stoichiometry of co-immunoprecipitated FLAG-CG4389 and Myc-Thiolase (Figure 4.7). The co-immunoprecipitation of Myc-Thiolase was not stoichiometric with the amount of FLAG-CG4389 bait protein even though it is known to exist in a multi- enzyme complex. The relative amounts of Myc-Thiolase and Myc-CG4091 to the FLAG CG4389 bait in each Co-IP were similar, suggesting that under the conditions of this assay their stoichiometry relative to FLAG-CG4389 is similar. Together, the IP/tandem MS data and Co-IP Western analyses with two different fatty acid 13-oxidation proteins, along with the expression of CG409 1 in Drosophila lipid storage/processing organs and the in vivo CG409 1 overexpression phenotype of increased lipid droplets in salivary glands, support a role for CG4091 in lipid metabolism. Based on its cytoskeletal localization and in vivo phenotypes, we predict that CG4091 has a regulatory role in this process, but its specific function and mechanism of action remain to be elucidated. 172 In beta-oxidation of fatty acids, the potential molecular functions of CG4389 and Thiolase are predicted to be long-chain-3-hydroxyacyl-CoA dehydrogenase activity and acetyl-CoA C-acyltransferase activity, respectively [45]. A lipid-droplet proteome study by Cermelli et al., 2006 [65] revealed that both proteins were found on lipid droplets purified from Drosophila embryos, indicating a potential role in lipid metabolism. An extensive literature search on Thiolase and CG4389 homologues both in mammals and plants provided evidence that the plant homologue of CG4389 is an RNA and microtubule binding protein that localizes to the peroxisomes [17,18]. Our results (Figure 4.8) showed localization of CG4389 protein in “vesicle-like” structures, and no observable co-localization with mitochondria (Figure 4.8J-L). These “vesicle-like” structures were always found in close proximity to microtubules (Figure 4.8M-O.). Long chain fatty acid beta oxidation occurs either in mitochondria or peroxisomes and CG4389 has functional domains corresponding to long-chain-3-hydroxyacyl-CoA dehydrogenase and long-chain-enoyl-CoA hydratase, indicating a possible role in fatty acid beta- oxidation. The Drosophila CG43 89 has a peroxisomal targeting signal “SKL” (PTS- 1) at its C-terminus, compatible with the notion that it is a peroxisomal protein. These observations, when taken together, lead us to believe that CG4389 may be a peroxisomal localizing protein involved in fatty acid beta oxidation. We tested the human catalase antibody (Abeam), a peroxisomal marker, to detect peroxisomes in S2 cells. However, the human antibody failed to cross react with Drosophila catalase (data not shown). Since Thiolase (CG458 1) is predicted to also be involved in fatty acid beta-oxidation and we showed that CG4389 and Thiolase interact (Figure 4.7), we predict that Thiolase is also involved in peroxisomal fatty acid beta-oxidation. We did not however identify a 173 peroxisomal targeting signal in the Thiolase sequence. Perhaps Thiolase binds to CG4389 or depends on other carrier proteins for shuttling into peroxisomes during fatty acid beta-oxidation. Our immunostaining of both N-terminal FLAG tagged or N-terminal Myc flagged Thiolase fusion protein showed a cytoplasmic localization pattern (Figure 4.8A). It is possible that as a convergence of the Myc and FLAG tags, both Myc- and FLAG-Thiolase fusion proteins were localizing to the wrong sub cellular compartment, the cytoplasm. In the future, native antibodies against Thiolase and CG4389 would be useful to confirm our findings. Since CG4091 appears to be a cytoskeleton binding protein (Table 4.1; Figure 4.10), it is possible for it to interact with functionally not related proteins that are localized to cytoskeleton. In fact, we did identify several other cytoskeletal binding proteins such as myosin heavy chain II, glyceraldehyde-3-phosphate dehydrogenase II, several RNA binding proteins and eukaryotic translation initiation factor 2 and 4A (Table 4.1; data not shown) in our immunoprecipitation experiments. These proteins have been implicated in binding to the cytoskeleton to facilitate mRNA localization to the destined subcellular compartment and their translation in plant and mammalian cells [50,66] and in vivo [67- 69]. These proteins were identified as interaction partners of CG4091 in one or two Co IP experiments only. It is possible, that some of these proteins are part of a protein complex that has some functional relationship to binding partners of CG409 1. For example, the plant peroxisomal protein that is similar to CG4389 is known to have RNA binding activity [18] and some of the RNA binding proteins we identified in our immunoprecipitations may be due to the interaction with CG4389. 174 We used nile red to determine whether salivary glands store neutral lipid during development. As indicated in Figure 4.11, in wild type strains neutral lipid droplets can be observed in the larval salivary glands at 0-8 hr APF and 20-24 hr APF. Unlike the major fat storage organs, the fat body and midgut, which showed very large (5-25 and 1-4 p.m diameter respectively) lipid droplets (data not shown), the fat droplets in salivary glands were relatively small and distributed throughout the cell (approximately 0.6-1 p.m in diameter). In contrast to wild type strains, salivary glands overexpressing CG4091 showed an increased number of fat droplets throughout development (0-24 hr APF). As shown in our model in Figure. 4.13, it is possible that highly expressed CG4091 is binding to CG4389 and Thiolase proteins and inhibiting their transport to the peroxisome, which could reduce fatty acid oxidation and result in increased fat droplet accumulation. In addition, or alternatively, overexpression of CG409 1, which affects the tubulin network, might disrupt the trafficking of fatty acids and fatty acid oxidizing proteins to peroxisomes and increase the quantities of cytoplasmic neutral lipid. Defects in autophagy may also affect the lipid degradation process and result in increased lipids in the salivary glands. Although we do not know the exact mechanism, the dramatically increased lipid droplets in the larval salivary glands of flies overexpressing CG4091, and the interactions of CG409 I with fatty acid beta-oxidation proteins in S2 cells, suggest that CG4091 has a direct or indirect role in lipid metabolism in larval salivary glands. When salivary glands undergo PCD, large amounts of lipid molecules are produced from degrading organelles, etc. 175 Figure 4.13. A model for the role of CG4091 in the Drosophila salivary gland PCD process. In wild type salivary glands, the expression of CG4091 increases just prior to death at 23-24 hrs APF. Increased expression of CG4091 occurs later in this process, possibly to allow maintenance of an intact microtubule network so that cellular processes such as autophagy can take place to efficiently degrade obsolete cytoplasmic components until total collapse of the salivary glands. The late expression of CG4091 may promote then cytoskeletal collapse in salivary glands, which in turn may trigger the production of MMPs (either directly or by suppressing timp) to degrade extracellular matrix components such as collagens. Increased expression of CG4091 can enhance disruption of microtubules and affect the size and distribution of autolysosomes. At this point, it is not clear whether autophagosome-lysosome fusion is affected in salivary glands when CG4091 is overexpressed. However, loss of CG4091 expression appears to affect the microtubule network, which appears to reduce autophagy in at least some cells, indicating the importance of timely expression of CG4091 in salivary glands. The autophagy process and lipases that break down storage fats release large quantities of energy-rich fatty acid during salivary gland cell death. CG4091 interacts with 13-oxidation proteins to possibly limit fatty acid oxidation to the levels required to accomplish PCD, retaining the remaining energy-rich fatty acids for adult tissue development. 176 Figure 4.13 Yin lastine Q PeroxisomeCG4091 p-oxia ion S°fdepoI1n.iLiii torage at Acetyl-CoA\\ Iipas /,3__auA2clondria Cell 1 •.•I’.’ 4y FattY.[c) \\Amino acid ATPAutophagasome lysosome (L) \ MMP-1 fusion autolysosome Extracellular matrix disruDtion 177 These lipids are broken down into fatty acids possibly by lipases in the cytoplasm and in the autolysosomes (Figure 4.13). Since Drosophila pupae at this stage do not feed, these energy-rich fatty acids from degrading tissues might be conserved and used for new adult tissue development. Hence, it is possible that the elevated expression of CG409 1 prior to death achieves rations of p-oxidation proteins into peroxisomes to catabolize fatty acids at the minimum required levels for PCD. A model of the proposed role of CG4091 in salivary gland cells is provided in Figure 4.13. TNFAIP8, the human homologue of CG409 1, was first identified in a differential display screen that identified tumor necrosis factor-ct (TNF-ct) responsive genes in endothelial cells [70] and was described further by Kumar et. a!., 2000 [71], when identified in a screen of a human heart cDNA library. TNFAIP8 and CG4091 show 42% amino acid identity and 65% amino acid similarity (based on BLAST analysis [72]) over the entire 188 amino acid sequence. No other similar genes exist in the Drosophila genome. Overexpression of Drosphila Eiger, a TNF-ligand like protein, both in vivo and in vitro, did not result in enhanced expression of CG4091 as detected by QRT-PCR (data not shown). However, an alternate TNF related protein (eg. traf-2, toll-i) may be involved in the upstream regulation of CG4091 in Drosophila. TNFAIP8 has been implicated in several cellular processes relevant to disease. In MDA-MB 435 breast cancer cells, exogenous expression of TNFAIP8 caused enhanced DNA synthesis, cell proliferation, and tumour growth rate [73] and promoted invasion [74]. siRNA treatment of TNFAIP8 in rheumatoid arthritis synovial fibroblasts (RASFs) inhibited MMP-1 production to a great extent [75], Zhang et al. [74] also observed 178 increased expression of VEGFR-2 and MMP- 1 and MMP-9 in breast cancer cells overexpressing TNFAIP8 and suggested that induction of VEGFR-2 via TNFAIP8 may lead to MMP- 1 production. Matrix metalloproteinase (MMP- 1), commonly known as collagenase- 1, can cleave interstitial collagens. It is produced by various types of cells in vitro and in vivo and its expression has been associated with inflammation, wound healing, and tumour invasion, growth, and metastasis [76-78]. It has been shown that microtubule disrupting agents such as coichicine and vinbiastine augment MMP-1 secretion in rheumatoid and normal synovial cells [79,80]. Though loss-of function [75] and gain-of-firnction [74] studies of TNFAIP8 showed that this gene regulates MMP-1 expression, the mechanism by which TNFAIP8 produces these effects is unknown. It is intriguing that the Drosophila mmp-1 matrix metalloproteinase gene is highly induced in dying salivary glands, while the expression of the metalloprotease inhibitor gene timp is repressed ([57,81]; independent confirmation by QRT-PC, unpublished). As predicted by our model, increased expression of CG4091 in dying salivary glands enhances microtubule disruption and therefore, increases the expression of MMP- 1 which can degrade components of the extracellular matrix, such as collagens. Therefore, our study may provide new insights as to how TNFAIP8 may be regulating the expression of MMP-l. TNFAIP8 has been implicated to play a role in metastatic breast cancer [74], and rheumatoid arthritis [75]. An increased expression of cytokines such as TNF-c as well as TNFAIP8 have been observed in blood cells that initiate plaques in atherosclerotic lesions and artheroscierosis [82]. Therefore, further studies in the role of CG4091 and TNFAIP8 in relation to cytoskeletal organization, autophagy and lipid metabolism in cancer and atherosclerotic disease models will be valuable. 179 In conclusion, we have analyzed CG409 1, a gene that is up-regulated during steroid- induced PCD. To our knowledge, we are the first to show that CG4091, a Drosophila ortholog of TNFAIP8, localizes to microtubules in Drosophila cells and plays a role in microtubule remodelling. The importance of an intact microtubule network to autophagy has been shown in in vitro systems previously, however, ours is the first study to confirm this finding in vivo. We also showed that CG409 1 forms a complex with probable beta- oxidation proteins CG4389 and Thiolase in Drosophila S2 cells. Overexpression of CG4091 increased fat droplets in larval salivary glands, increased degradation of tubulin and altered the size and distribution of intermediate-late stage autophagic vacuoles during death stages. The observation by others [74,75] is that the human homologue TNFAIP8 regulates matrix metalloproteinase MMPs. 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Cuff Biol 13: 350-357. 82. Patino WD, Kang JG, Matoba S, Mian OY, Gochuico BR, et al. (2006) Atherosclerotic plaque macrophage transcriptional regulators are expressed in blood and modulated by tristetraprolin. Circ Res 98: 1282-1289. 190 Chapter 5. CONCLUSIONS 5.1 Overall Summary and Significance of the Studies This thesis describes my efforts (1) to identify genes that are transcriptionally regulated during steroid-induced PCD in Drosophila salivary glands, (2) to identify the genes with pro-death and pro-survival function in ecdysone-induced PCD and (3) to discover the role of a novel gene in PCD in Drosophila salivary glands. I anticipated that the outcome of the study would both identify new genes that are involved in apoptosis and autophagy, and provide new insights into steroid-hormone induced PCD. The transcriptional profiling of Drosophila salivary glands describes one of the first large-scale comprehensive descriptions of in vivo gene expression associated with PCD with features of apoptosis and autophagy during normal metazoan development. A similar experiment, involving, transcriptional profiling of Drosophila salivary glands using microarrays was co-published with our study [1]. In addition to core apoptosis and autophagy genes, our study revealed genes involved in other cellular process such as protein synthesis, transcription, innate immunity, and multiple signal transduction pathways that were also transcriptionally regulated. These observations suggest the possible involvement of these other cellular processes in salivary gland PCD. In total, 1,244 different transcripts were differentially expressed during salivary gland PCD and of these, 377 did not correspond to predicted genes (GadFly release 2; [2]). Therefore, this study generates further hypotheses regarding the involvement of known genes, predicted genes, novel transcripts and cellular processes in salivary gland PCD. A medium-scale follow up functional analysis of differentially expressed genes in vitro led me to identify many novel genes in the steroid hormone ecdysone signaling 191 network that governs cell death and cell survival. In this study, I verified functionally the pro-death effects of six genes and the pro-survival effects of 21 genes, and further characterized their functions on the basis of ecdysone dependency and cell death regulation. Identifying known genes and biochemical complexes such as Ras85D - hid, and Sin3A — Smr, which are involved in cell survival or cell death processes in Drosophila, validates my approach. The association of the corresponding human homologs with cancer [3-5], indicates the relevance of my study to cancer. For example, this study identified six previously uncharacterized genes (CGJ3 748, CGJ3 784, CG15239, CG32016, CG33087, and CO 7466) as ecdysone dependent pro-survival genes. Of these six genes, at least two of them (CG33087 and CG7466) have human homolougues and may be interesting to investigate further with respect to biological role, human orthology and possible cancer relationship. Also, my study identified, for the first time, a possible pro-death role for the transcription factor Soxl4. In contrast to this pro- death role elucidated for Drosophila Soxl4, Drosophila SoxN had an anti-death pro- survival role. These findings generate an interesting hypothesis, which could be tested in future studies, that Sox]4 and SoxN may function antagonistically to determine cell death or cell survival in response to ecdysone. Finally, my study provides more insights into the role of a novel gene, CG409], in PCD of larval salivary gland, a model system it was identified from. This demonstrates how expression profiling experiments can be used to identify and characterize novel genes involved in PCD. This study showed that CG4091 is a microtubule binding protein that is probably involved in MT remodeling in the Drosophila salivary gland. Deregulation of CG409 1 affects the microtubule network in the salivary glands and 192 affects MT-dependent processes such as autophagy and lipid metabolism. Hence, correct amounts of CG409 1 must be expressed in a timely manner in the Drosophila larval salivary glands during the PCD process. Failure to disrupt MTs in salivary glands at earlier timepoints (i.e., before 20 hrs APF at 18°C), and in S2 cells when ectopically expressed may suggest that other microtubule depolymerizing proteins are required in combination or for the complete activity of CG4091. For example, proteins such as stathmin or MAP2O5 may act synergistically with CG4091 during PCD to execute depolymerization of microtubules. Therefore, it would be appealing to determine the potential synergistic effects of CG4091 and MAP2O5 or stathmin in depolymerizing tubulin. TNFAIP8 is the human homologue of CG409 1. Interestingly, siRNA treatment of TNFAIP8 inhibited production of MMP-l [6], a protein that cleaves the extracellular matrix. In contrast, increased expression of TNFAIP8 resulted in increased expression of MMPs via VEGFR-2. Microtubule disruption with chemicals augments MMP-l secretion [7,8] in rheumatoid and normal synovial cells. Though loss-of function [6] and gain-of-function [9] studies of TNFAIP8 showed that this protein is regulating MMP-1 expression, the mechanism by which TNFAIP8 produces these effects is unknown. For the first time, the study of CG409] provides clues as to how TNFAIP8 is regulating MMPs. Exogenous increased expression of TNFAIP8 has been associated with cell proliferation and tumour invasion [9,10]. Cytoskeletal rearrangements and expression of MMPs has been observed during various diseases, including cancer metastasis and atherosclerosis. When these observations are combined, it appears that the human homologue of CG4091 may have functional relevance in diseases involving cytoskeletal 193 rearrangements and extracellular matrix degradation. Therefore, further characterization of CG4091 in vivo using the tools that we generated, as well as the study of human TNFAIP8 in relation to microtubule disruption and extracellular matrix disruption, could provide more insight into processes such as metastasis, tumour invasion, and initiation of atherosclerotic plaques. In addition, the association of CG4091 with 3-oxidation proteins and lipid accumulation may have further important implications for cellular metabolism and energy utilization, as well as atherosclerosis progression. In summary, since deregulation of autophagy and apoptosis have been associated with many diseases, and several apoptotic genes have been used as therapeutic targets [11], it is essential to develop a detailed understanding of the molecules required for both processes. The studies described in this thesis have enabled us to identify and prioritize several hundred genes potentially involved in these processes and have provided a powerful starting point for extensive functional studies that will determine the mechanisms that are essential to execute PCD associated with apoptosis and autophagy. 5.2 Strengths and limitations of the studies To identify the genes with pro-death and pro-survival function in ecdysone-induced PCD, this thesis employed SAGE and EST based analysis. Microarrays are also used for transcriptional profiling, but historically have not been as useful in studies aimed at new gene identification. Although EST analysis is an excellent gene discovery approach, it is usually not quantitative and, due to extensive sequencing, it has been relatively expensive. However, next-generation sequencing techniques can make this a cheaper and more viable method. The combined use of SAGE and EST allowed us to identify and quantitate annotated and new genes that are involved in salivary gland PCD. One major 194 criticism of expression profiling studies is that mRNA and protein levels may not always correlate. Although this may be true under certain circumstances, transcription profiling is a good starting point from which to study various cellular processes, particularly those that are transcriptionally regulated, as demonstrated in this study. Enrichment and prioritization for transcriptionally regulated genes in Drosophila larval salivary glands in the first phase of the study led us to choose 460 genes for a medium-scale RNAi experiment. In the absence of this knowledge, identification of pro- death or pro-survival genes in ecdysone-induced cell death would have required a several-fold more expensive and more time consuming whole genome RNAi approach or a less informed candidate gene approach. Employing an in vitro system using l(2)mbn cells, which employ an ecdysone-induced transcriptional cascade and subsequent PCD, allowed us to successfully identify 27 genes that are potentially involved in PCD and further allowed us to characterize their functions on the basis of ecdysone dependency and cell death regulation. Further, independent RNAi confirmation of these genes with non-overlapping dsRNA was used to confirm their phenotypes (i.e., pro-survival or pro- death) more reliably. Taken together, these 27 genes are excellent candidates for extensive functional characterization in relation to steroid-induced PCD. However, this system was limited to identifying death-related genes and not autophagy genes. In the salivary glands, autophagy genes were differentially expressed. However, these genes were not differentially expressed in the ecdysone treated l(2)mbn cells, indicating that not all cellular components are regulated in a similar manner in our in vitro system. Recently [121, a role for autophagy genes 1, 2, 3, 6, 7, 8, and 12 in salivary gland degradation has been demonstrated, however, our study did not find a death related role for autophagy 195 genes in our l(2)mbn system. This may suggest, which may suggest that the autophagy process is not involved in ecdysone-induced death in l(2)mbn cells. In our laboratory, an RNAi approach to identify genes regulating starvation-induced autophagy has been developed (Hou et al, submitted) using l(2)mbn cells. This method can be used to identify autophagy regulating genes by screening the 460 genes that we identified in our SAGE study. Since genes known to be involved in ecdysone induced salivary gland cell death are transcriptionally regulated during this process [13-15] we hypothesized that additional genes required for cell death would be up-regulated and genes required for cell survival would be transcriptionally down-regulated during larval salivary gland cell death. We screened (by RNAi) a total of 460 genes identified by SAGE and of these, 28 (i.e. 6%) were shown to play an essential role in ecdysone induced cell death or cell survival. As shown in chapter 3, our SAGE-based functional prediction (i.e. death or survival) and actual RNAi screen results agreed only 48% of the time (10/21 genes; Table 3.2). For 52% of the genes with both SAGE and RNAi data, our SAGE-based predictions did not match the RNAi-derived function (Table 3.2). There are several possible explanations for these observations. First, known pro-death genes reaper and Nc (drone) showed increased expression in the SAGE libraries; these gene products are essential to execute salivary gland death. However, the anti-apoptosis gene th (diap-]) did not show a transcriptional down-regulation. This suggests that perhaps th (and other genes) is not regulated at the transcriptional level but may instead be regulated at the protein level. In fact, it has been shown that diap- 1 protein mediates ubiquitination (and thus degradation) of the caspase Nc [16] under normal conditions, but during developmental death of 196 Drosophila ommatidium, binding of pro-death proteins rpr, hid and grim, releases diap-1 from the caspase which initiates the caspase cell death cascade. These findings suggest that the inhibitory effect of diap- 1 in cell death is regulated at the protein level. This type of regulation may explain why, at least in some cases, our transcription-based predictions did not agree with the actual function of genes as determined by RNAi. Second, careful examination of our data (Table 3.1 and 3.2) revealed that mechanism of gene function is another important determinant. Potential death related pro-survival genes that were transcriptionally down-regulated (predicted to be a pro-survival gene) have transcription factor activity or nucleic acid binding activity (SoxN, Smr, HmgD, and cpo). Down regulation of transcription factor activities of these genes is similar to that observed for early transcription factors E75, Br-C, etc. which are downregulated just prior to death (e.g. 23 hrs) but are actually transcriptionally upregulated at early stages of salivary gland cell death to induce expression of death related genes. However, pro-survival genes that were transcriptionally up-regulated based on SAGE were generally involved in protein carrier activity or protein degradation (Rpn2, Tbp-], Pros26. 4, Kap-a3, and Cpl). This may suggest that protein degradation and also ATP release is important to complete the cell death process. Thus, when predictions are made from transcriptionally-based data, incorporation of known functional roles andlor mechanisms of action may help to understand and establish hypotheses more accurately. Extensive characterization of the CG409] gene included both in vitro and in vivo studies. Our study employed genetic approaches in vivo, and molecular and biochemical studies such as Co-IP combined with mass spectrometry, and immunofluorescence. One limitation in our study was that we employed only in situ hybridization experiments in 197 embryos and tissues because we did not have a CG4091 antibody for this purpose. We did develop an antibody in collaboration with Dr. D. Xiabo (BC Cancer Agency, Victoria), but the antibody was not optimized for use in tissues at the time this thesis was written. In the future, we will optimize conditions to determine whether the antibody will be useful in tissues, and if so, perform analyses to determine the expression of CG4091 during development. To efficiently identify the interaction partners of CG409 1, we utilized the in vitro system, Drosophila S2 cells. This method allowed us to express CG4091 protein and IP interaction partners at a quantity required by mass spectrometry analysis. The findings from the in vitro studies were confirmed by both rcciprocal co expressed Co-IP western analysis as well as IF in whole cells. The abnormality in the tubulin network in the CG4091 mutant studies in vivo were in agreement with the protein-interaction studies in vitro in S2 cells, where we demonstrated the interaction of CG4091 with microtubule and related proteins. The interaction of CG4091 with fatty acid metabolism proteins CG4389 and Thiolase in vitro led to the finding of increased lipid droplets in vivo in the Drosophila salivary glands in the gain-of-function mutants. Therefore, this study efficiently used both in vivo and in vitro systems to characterize the function of the annotated gene, CG409]. In addition, the protein interaction study identified new targets to test and gain new insights into the function of CG4091 in relation to cytoskeletal remodeling and fatty acid oxidation regulation, and therefore in relation to diseases associated with these processes. Since CG4091 and the neighbouring gene l(2)dtl were positioned in close proximity in the Drosophila genome, we were only able to produce strains deficient for both of these genes (Df-C23). To create a loss-of-function strain for CG409], we rescued the 198 function of l(2)dtl by crossing the Df-C23 strain to pUAST-l(2)dtl 42-3 and established a strain that expresses l(2)dtl but not CG4091. To confirm that the phenotype we observed in the salivary glands in this strain was due to loss-of-function of CG4091, we crossed these animals with pUAST-CG4091 15-1 and rescued the function of CG4091. This procedure was time consuming and very labour intensive. Different approaches such as in vivo RNAi may have expedited the creation of a loss-of-function mutant for CG4091. We initiated this approach much later in our study and therefore, an in vivo RNAi mutant strain was not available at the time this thesis was written. However, we will examine our RNAi strains in-house to further test our finding in the future. 5.2 Future research The study described in this thesis identified 1,244 transcripts that were differentially expressed during salivary gland PCD and of these, 377 transcripts (i.e., SAGE tags) did not correspond to predicted genes (GadFly release 2; [2]). These 377 SAGE tags are probably generated from unannotated genes or even pseudogenes or artifacts that were produced during the SAGE procedure. Subsequent mapping of these 377 transcripts to the updated GadFly release 3, indicated that most of these transcripts did now map to annotated genes but some transcripts were still novel. To determine whether SAGE tags that did not map to annotated genes are novel transcripts, expression analysis experiments were carried out in our laboratory using QRT-PCR. The results suggest that at least some of these tags belong to true transcripts and are not artifacts. In addition, pilot experiments were initiated to clone the unannotated genes to which these novel SAGE tags mapped (B. Hambleton, unpublished). In our RNAi screen, we examined only the function of 460 genes that showed at least 5 fold differential expression in our SAGE data. Functional 199 characterization of the remaining genes identified, including the novel transcripts, in relation to PCD may be valuable in the future. Likewise, the role of these genes in autophagy can be determined by the RNAi approach that was established by Hou et. al., 2008 (submitted, unpublished data). These future studies may identify additional novel targets that are associated with either apoptosis or autophagy. The RNAi study identified the pro-death effects of six genes and the pro-survival effects of 21 genes. This study identified genes that are already being characterized by others in relation to diseases (e.g., Sin3A, smr, Tor, S6K, etc.). In addition, our screen identified six pro-survival genes that were not characterized previously in relation to any cellular processes, and at least two of these genes have human homologues. Several other genes identified were known previously to be involved in other cellular processes and were identified for the first time as cell death or cell survival genes in our study (e.g., Sox 14, cpo, Indy, HmgD, Vps 32, etc.). Therefore, future extensive characterization of these prioritized genes in relation to PCD will be valuable in understanding their biological roles and may provide insights into disease mechanisms. In our laboratory, we have initiated experiments to characterize the S’oxl4 gene further using an in vivo system. Preliminary studies using Soxl4 in vivo RNAi loss-of-function Drosophila mutants show persistent salivary glands, which is in agreement with our in vitro RNAi study. We are interested in elucidating a potential antagonistic functional role of Drosophila Soxl4, and Drosophila SoxN in relation to PCD as well as identifying their transcriptional targets. The role of CG4091 in MT remodeling in salivary glands and therefore possible activation of MMPs in salivary glands is intriguing, especially since this phenomenon has been observed in cancer and atherosclerosis, In the immediate future, expression of 200 MMPs will be determined in the CG409] mutant salivary glands and other tissue such as mid gut. We will also determine whether TNFAIP8 localizes with microtubules in human cell lines and/or affects the microtubule network and whether it binds or complexes to 13-oxidation proteins. In addition, we are interested in characterizing TNFAIP8 in human systems in association with PCD andlor cytoskeletal remodeling and/or fatty acid metabolism to gain further insights in relation to its role in diseases such as cancer and atherosclerosis. It would also be interesting to conduct further explorations to elucidate possible regulatory links between fatty acid metabolism, autophagy, and microtubule remodeling. In summary, our study identified genes involved in cell death and cell survival and has provided new insights into salivary gland PCD in Drosophila. Future characterization of these genes in relation to Drosophila development and specific disease models will provide more knowledge regarding gene function and possible relevance to human diseases. 201 5.3 References 1. Lee CY, Clough EA, Yellon P, Teslovich TM, Stephan DA, et al. (2003) Genome wide analyses of steroid- and radiation-triggered programmed cell death in Drosophila. Cuff Biol 13: 350-357. 2. Adams MD, Celniker SE, Holt RA, Evans CA, Gocayne JD, et al. (2000) The genome sequence of Drosophila melanogaster. Science 287: 2185-2195. 3. Prober DA, Edgar BA (2002) Interactions between Rasi, dMyc, and dPI3K signaling in the developing Drosophila wing. 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Copy of Animal Care Certificate Page 1 of 1 THE UNIVERSITY OF BRITISH COLUMBIA ANIMAL CARE CERTIFICATE Application Number: A05-0060 Investigator or Course Director: Sharon Gorski Department: Medical Genetics Animals: Drosophila melanogaster 10000 Start Date: October 1,2005 Approval June 20, 2007Date: Funding Sources: Funding Canadian Institutes of Health Research (CIHR)Agency: Funding Title: Molecular Characterization of Autophagic Cell Death Unfunded title: Molecular Characterization of Autophagic Cell Death The Animal Care Committee has examined and approved the use of animals for the above experimental project. This certificate is valid for one year from the above start or approval date (whichever is later) provided there is no change in the experimental procedures. Annual review is required by the CCAC and some granting agencies. A copy of this certificate must be displayed in your animal facility. Office of Research Services and Administration 102, 6190 Agronomy Road, Vancouver, BC V6T lZ3 Phone: 604-827-5111 Fax: 604-822-5093 https://rise.ubc.ealrisefDoc/0/26JDE32IOMHK73FO7EO4OAUO8A/fromString.html 6/20/2007 204 Appendix B. Copy of Biohazard Approval Certificate The University of British Columbia Biohazard Approval Certificate PROTOCOL NUMBER: H08-0038 INVESTIGATOR OR COURSE DIRECTOR: Gorski, Sharon DEPARTMENT Medical Genetics L PROJECT OR COURSE TITLE: Molecular Characterisation of autophagic cell death APPROVAL DATE: 08-01-25 APPROVED CONTAINMENT LEVEL. 2 FUNDING AGENCY: Canadian Institutes of Health Research (CIHR) The Principal Investigator/Course Director is responsible for ensuring that all research or course work involving biological hazards Is conducted in accordance with the Health Canada, Laboratory Biosafety Guidelines, (2nd Edition 1996). Copies of the Guidelines (1996) are available through the Biosafety Office, Department of Health, Safety and Environment, Room 50- 2075 Wesbrook Mall, UBC, Vancouver. BC, V6T 1Z1, 822-7596, Fax: 822-6650. Approval of the UBC Biohazards Committee by one of: Chair, Biosafety Committee Manager, Biosafety Ethics Director, Office of Research Services This certificate is valid for one year from the above start or approval date (whichever is later) provided there is no change in the experimental procedures. Annual review is required. A copy of this certificate must be displayed In your facility. Office of Research Services 102, 6190 Agronomy Road, Vancouver. V6T 1Z3 Phone: 604-827-5111 FAX: 604-822-0093 205

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