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Genome-wide analysis of endocytic recycling in S. cerevisiae Burston, Helen Elizabeth Jul 29, 2011

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 i GENOME-WIDE ANALYSIS OF ENDOCYTIC RECYCLING IN S. CEREVISIAE  by  Helen Elizabeth Burston  B.Sc.  Simon Fraser University, 2005   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in  The Faculty of Graduate Studies  (Medical Genetics)    THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)  July 2011      © Helen Elizabeth Burston, 2011  ii ABSTRACT   The process of endocytic recycling, in which cell surface proteins are internalized and re-delivered to the plasma membrane, is essential in all eukaryotes for maintaining plasma membrane composition and regulating the surface levels of signaling receptors.  The applicability of Saccharomyces cerevisiae as a model to study endocytic recycling is a subject of debate, as there appears to be critical differences between yeast and mammalian cells.  For example, while clathrin and its adaptors are critical for uptake in mammals, they do not seem to be essential in yeast.  Endocytic recycling has not been comprehensively studied on a genetic level in yeast, and only limited cargo have been considered, making it difficult to accurately assess the similarity between the two systems.  Furthermore, the transport of SNARE proteins is poorly understood, but appears to involve specialized mechanisms.  This study uses a genome-wide screening approach to systematically and quantitatively identify genes required for the endocytic recycling of the yeast SNARE protein Snc1, homologous to the mammalian VAMP2/synaptobrevin. Endocytic defects for mutants of many yeast homologs of mammalian endocytosis genes were identified, for the first time.  Significantly, a cargo-selective and partially- redundant role for clathrin and its adaptors yAP1801 and yAP1802 was identified.  The lipid phosphatase Inp52 was found to mediate AP180 release from endocytic vesicles.  Additionally, the previously uncharacterized protein Ldb17, homologous to the mammalian endocytic protein SPIN90, was identified as a new component of the endocytic machinery, and regulates both coat and actin dynamics at endocytic sites. Factors regulating Snc1 recycling were also identified, including the variant clathrin adaptor AP-1R.  This is the first reported function for this complex.  The previously uncharacterized protein Ima1 was found to be a putative enzyme that specifically binds to AP-1R, and may have activity related to AP-1R function. Overall, this study demonstrates that endocytic recycling in yeast and mammals is more similar than previously appreciated, and identifies new factors in this process.  Furthermore, it raises awareness of the degree of cargo-selectivity underlying this pathway, and demonstrates quantitative methods that can be further applied to future studies in both systems.  iii PREFACE  List of publications generated from work presented in this dissertation:  1. CHAPTER 2:  Burston HE, Maldonado-Báez L, Davey M, Montpetit B, Schluter C, Wendland B, and Conibear E. (2009) Regulators of Yeast Endocytosis Identified by Systematic Quantitative Analysis. Journal of Cell Biology. 185(6):1097-110. A re-formatted version of this publication is included as chapter 2.  Contributions I was responsible for the writing of the manuscript, all experiments and data analysis, with the exception of the following:  The primary, E-Mapping, and cargo-specificity screens for Invertase activity were carried out by Michael Davey (Conibear lab).  Data resulting from these screens were analyzed by Elizabeth Conibear, in collaboration with Jochen Brumm and Jenny Bryan (University of British Columbia).  Figure 2.7 (A-F, H) and Figure A2 (A-D): Live cell microscopy and TIRF analysis were carried out by Lymarie Maldonado-Báez and Beverly Wendland (Johns Hopkins University)  Figure A2 (E, G, and H): Co-immunoprecipitations and Yeast-two-hybrid analyses were carried out by Benjamin Montpetit (University of Berkley)  2. CHAPTER 3: Burston HE, Tam C, Davey M, Raghuram N, Maldonado-Báez L, Wendland B, and Conibear E. (2010). The Alternate AP-1R Clathrin Adaptor Mediates Snc1 Endocytic Recycling. A re- formatted version of this manuscript (in preparation) is included as chapter 3.     iv Contributions  I was responsible for the writing of this manuscript, and for the design, implementation, and analyses of all experiments, with the following exceptions:  Figure 3.1 (B): live cell imaging and TIRF analysis was carried out by Lymarie Maldonado- Báez and Beverly Wendland (Johns Hopkins University)  Figure 3.3 (B, C): Co-immunoprecipitations were carried out by Chris Tam (University of British Columbia)  Figure 3.3 (D) and 3.5 (D): Yeast-two-hybrid experiments and Invertase assays were carried out by Nandini Raghuram (University of British Columbia)     v TABLE OF CONTENTS  ABSTRACT  ........................................................................................................................................................................... ii PREFACE .............................................................................................................................................................................. iii TABLE OF CONTENTS .................................................................................................................................................... v LIST OF TABLES ............................................................................................................................................................ viii LIST OF FIGURES ............................................................................................................................................................. ix LIST OF ILLUSTRATIONS ..............................................................................................................................................x LIST OF SYMBOLS AND ABBREVIATIONS .......................................................................................................... xi ACKNOWLEDGEMENTS ............................................................................................................................................ xiii DEDICATION ....................................................................................................................................................................xiv CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW ........................................................................ 1 1.1. Foreward: Membrane protein transport in the endosomal system ........................................ 2 1.1.1. Endocytic trafficking in cellular function and human disease ........................................... 2 1.1.2. Overview of intracellular transport and the regulation of vesicle formation ............ 3 1.1.2. Markers of organelle identity and the specificity of vesicular transport ..................... 4 1.1.4. Coat proteins mediate vesicle formation ...................................................................................... 6 1.2. Clathrin adaptors are key regulators of cellular transport........................................................... 8 1.2.1. Heterotetrameric clathrin adaptors: structure and function ............................................. 8 1.2.2. Physiological importance of clathrin adaptors .......................................................................... 9 1.2.3. Recruitment and un-coating of AP complexes: membrane phospholipids ................. 9 1.2.4. AP appendage domains interact with multiple regulators ............................................... 10 1.2.5. Mechanisms of AP cargo recognition ........................................................................................... 11 1.2.6. Non-canonical cargo sorting signals are recognized by CLASPS ................................... 12 1.3. Transport of SNARE proteins .................................................................................................................... 13 1.3.1. Alternative sorting mechanisms regulate SNARE transport ........................................... 13 1.3.2. What is the role of palmitoylation in SNARE transport? ................................................... 14 1.4. Endocytosis and endocytic recycling pathways .............................................................................. 15 1.4.1. Yeast as a model for endocytic recycling ................................................................................... 15 1.4.2. Do yeast and mammals share common mechanisms of endocytosis?........................ 16 1.4.3. A comparison of the endosomal system in yeast and mammalian cells .................... 17 1.5. Yeast functional genomics: a tool to dissect trafficking pathways ........................................ 19 1.5.1. Systems biology approaches to study membrane transport ........................................... 19 1.5.2. Phenotypic screening in yeast to identify transport components ................................ 21 1.6. Research objectives and hypotheses ..................................................................................................... 22 1.6.1. A new approach for identifying endocytic recycling components in yeast.............. 22 1.7. Illustrations ........................................................................................................................................................ 24  vi CHAPTER 2. REGULATORS OF YEAST ENDOCYTOSIS IDENTIFIED BY SYSTEMATIC QUANTITATIVE ANALYSIS.  ..................................................................................................................................... 27 2.2. Introduction ....................................................................................................................................................... 28 2.3. Results ................................................................................................................................................................... 30 2.3.1. A Snc1-based quantitative assay for endocytic recycling.................................................. 30 2.3.2. Genetic interaction mapping clusters functionally related genes................................. 31 2.3.3. Integration of genetic and physical interaction data identifies complexes required for Snc1 transport ............................................................................................................................................... 32 2.3.4. Clathrin and clathrin assembly proteins are required for Snc1 endocytosis.......... 33 2.3.5. Systematic analysis of cargo specificity ...................................................................................... 34 2.3.6. Ldb17 is a new regulator of yeast endocytosis that is transiently recruited to cortical patches .................................................................................................................................................... 35 2.3.8. Aberrant actin distribution in LDB17 mutants ....................................................................... 37 2.4. Discussion............................................................................................................................................................ 37 2.4.1. Role for clathrin adaptors in yeast endocytosis ..................................................................... 38 2.4.2. Identification of novel components of the yeast endocytic machinery...................... 39 2.5. Materials and methods ................................................................................................................................. 40 2.6. Figures and Tables .......................................................................................................................................... 44 CHAPTER 3: THE YEAST VARIANT AP-1R CLATHRIN ADAPTOR AND IMA1 ARE REQUIRED FOR SNC1 ENDOCYTIC RECYCLING1 ................................................................................................................... 53 3.1. Synopsis ................................................................................................................................................................ 54 3.2. Introduction ....................................................................................................................................................... 54 3.3. Results ................................................................................................................................................................... 56 3.3.1. A role for the variant AP-1R complex in endocytic recycling .......................................... 56 3.3.2. AP-1R mediates intracellular recycling ...................................................................................... 57 3.3.3. AP-1R and Ima1 localize to Golgi/endosomal compartments ........................................ 57 3.3.4. Ima1 and AP-1R are not required for the transport of AP-1-dependent cargo ..... 58 3.3.5. Ima1 specifically binds the AP-1R C-terminal domain ....................................................... 59 3.3.6. Ima1 is not required for AP-1R recruitment or interaction with cargo..................... 60 3.3.7. Ima1 is a conserved protein with a consensus α/β hydrolase catalytic motif ....... 61 3.3.8. The Ima1 GXSXG catalytic motif is required for normal Snc1 surface levels .......... 62 3.4. Discussion............................................................................................................................................................ 63 3.4.1. AP-1R mediates Snc1 intracellular recycling ........................................................................... 63 3.4.2. Apm2 binds to Snc1 as cargo............................................................................................................ 63 3.4.3. Distinct sorting functions for AP-1/AP-1R ............................................................................... 64 3.4.4. AP-1/AP-1R localize to similar intracellular compartments ........................................... 65 3.4.5. Role of Ima1 in AP-1R regulation................................................................................................... 65 3.4.6. Ima1 has putative enzymatic activity .......................................................................................... 67  vii 3.5. Materials and methods ................................................................................................................................. 68 3.6. Figures ................................................................................................................................................................... 73 CHAPTER 4: DISCUSSION AND FUTURE DIRECTIONS .............................................................................. 81 4.1. Overview .............................................................................................................................................................. 82 4.2.1. Role of clathrin and yeast AP180 homologs in Snc1 endocytosis ................................. 83 4.2.2. How is yAP180 recruited to endocytic sites? .......................................................................... 83 4.2.3. Role of synaptojanin in yAP180 vesicle un-coating.............................................................. 85 4.2.4. How does yAP180 recognize Snc1 for internalization? ..................................................... 87 4.2.5. Does AP-2 mediate endocytosis in yeast?.................................................................................. 88 4.2.6. Role of actin and its regulators in Snc1 internalization ..................................................... 89 4.3. Regulators of Snc1 recycling: AP-1R and Ima1 ................................................................................ 91 4.3.1. What is the role of AP-1R in Golgi/endosomal recycling? ................................................ 91 4.3.2. What is the Snc1 recycling signal recognized by AP-1R? .................................................. 94 4.3.3. How do AP-1 and AP-1R regulate distinct sorting pathways? ........................................ 95 4.3.4. Do AP-1 and AP-1R localize to different lipid domains? .................................................... 96 4.3.5. Ima1 is a putative enzyme and binds the Apm2 C-terminal domain .......................... 97 4.3.6. Is Ima1 important for the generation of lipids required for AP-1R function? ......100 4.3.7. Determination of Ima1 substrates...............................................................................................100 4.3.8. Investigating the role of TMC04 in higher cells ....................................................................101 4.4. Genetic interaction profiling to identify complexes and pathways required for Snc1 transport .....................................................................................................................................................................102 4.4.1. Phenotypic profiling and the construction of genetic interaction networks ........102 4.4.2. Endocytic processes are part of a broader cellular context ...........................................104 4.4.3. Assessing the role of essential genes in Snc1 transport ...................................................105 4.4.4. Relationships between endocytic recycling factors; implications in disease .......106 4.4.5. Future perspectives.............................................................................................................................107 4.4. Illustrations ......................................................................................................................................................109 BIBLIOGRAPHY.............................................................................................................................................................111 APPENDIX A: Supplemental material for chapter 2 ..................................................................................130 APPENDIX B: Supplemental material (chapter 3) ......................................................................................221   viii LIST OF TABLES   Table 2.1. Predicted yeast endocytic genes identified in the screen................................................. 45 Table A1. Plasmids and yeast strains used in this study .......................................................................130 Table A2. Full list of mutants with cell surface GSS levels greater to or equal to the median value for all strains. ....................................................................................................................................................162 Table B.1. Plasmids and yeast strains used in this study ......................................................................221                                          ix LIST OF FIGURES   Figure 2.1. Genome-wide screen for endocytic recycling mutants. ................................................... 44 Figure 2.2. Endocytosis mutants have related genetic interaction profiles. ................................. 46 Figure 2.3. Integration of genome-wide genetic and physical interaction data identifies pathways and complexes. ......................................................................................................................................... 47 Figure 2.4. Yeast AP180 homologs have a conserved role in Snc1 internalization. .................. 48 Figure 2.5. Cargo sorting defects of yap1801∆ yap1802∆ mutants. ................................................. 49 Figure 2.6. Cargo specificity of genes required for Snc1 endocytosis. ............................................. 50 Figure 2.7. Ldb17 is required for proper coat and actin dynamics ................................................... 51 Figure 3.1. AP-1R is required for correct sorting of Snc1 ....................................................................... 73 Figure 3.2. AP-1R and Ima1 localize to Golgi and endosomal compartments ............................. 74 Figure 3.3. Ima1 associates functionally and physically with AP-1R................................................ 75 Figure 3.4. Ima1 is not required for Apm2 membrane recruitment or cargo binding ............ 77 Figure 3.5. Ima1 contains putative catalytic residues, required for Snc1 sorting ..................... 78 Figure 3.6. Overexpression of Ima1 does not affect Snc1 palmitoylation ...................................... 80 Figure A1. Full hierarchical clustering of the genetic interaction data. .........................................218 Figure A2. Characterization of LDB17 mutants and identification of Ldb17-interacting proteins.............................................................................................................................................................................219      x LIST OF ILLUSTRATIONS  Illustration 1.1. Intracellular compartments and transport pathways. ......................................... 24 Illustration 1.2. Steps in clathrin-coated vesicle formation and transport. ................................. 25 Illustration 1.3. Clathrin Adaptor (AP) structure....................................................................................... 26 Illustration 1.4. Comparison of endocytic recycling compartments and pathways in yeast and mammalian cells. .................................................................................................................................................. 26 Illustration 4.1. New factors required for Snc1 endocytic recycling. ............................................109 Illustration 4.2. AP-1R transport function: Model 1 ...............................................................................110 Illustration 4.3. AP-1R transport function: Model 2 ...............................................................................110      xi LIST OF SYMBOLS AND ABBREVIATIONS  AAK1   Adaptor-associated kinase 1 ABE   Acyl-biotin exchange  ABPP   Activity-based protein profiling  AD   Alzheimer’s disease  ALP   Alkaline phosphatase ANTH   AP180 Amino-terminal homology domain AP   Adaptor Protein  AP-1R   AP-1 related  APP   Amyloid precursor protein  ARF  ADP Ribosylation Factor ARH   Autosomal recessive hypercholesterolemia  BAR   Bin/Amphiphysin/Rvs domain BFA   Brefeldin A  CCV   Clathrin-coated vesicle CLASP   Clathrin-associated sorting protein CPY   Carboxypeptidase Y DAB2   Disabled2  DEP   Dishevelled, egl-10, and pleckstrin domain DUF   Domain of unknown function Dvl   Dishevelled  E-Map   Epistatic miniarray profiling  EGF   Epidermal growth factor EH   Eps15 homology domain ENTH   Epsin amino terminal homology domain ER   Endoplasmic reticulum  ERC   Endocytic recycling compartment  ESCRT   Endosomal sorting required for transport FP   Fluorophosphonate  GAE   Gamma-adaptin ear domain GAP   GTPase-activating protein GAT  GGA and tom1 domain GDP  Guanosine di-phosphate  GEF   Guanine nucleotide exchange factor GGA   Golgi-localized, gamma-ear containing, ARF-binding  GLUT4   Insulin-sensitive glucose transporter 4  GPCR  G Protein-coupled receptor GSS    GFP-Snc1-Suc2 GTP  Guanosine triphosphate HD   Huntington's disease  Hip1/Hip1R  Huntington interacting/Huntington interacting-related protein HPS   Hermansky Pudlak syndrome  Ima1   Interacts with µ adaptin 1  LacZ   β-galactosidase  LatA    Latrunculin A LBPA   Lysobisphosphatidic acid  MVB   Multivesicular body  NGSS   3x NPFxD-GFP-Sso1-Suc2  xii NPF   Nucleation promoting factor PA   Phosphatidic acid PC   Phosphatidylcholine  PE   Phosphatidylethanolamine PH   Pleckstrin homology domain PIPK   Phosphatidylinositol phosphate kinase PLD   phospholipase D  PRD   Proline-rich domain PS   Phosphatidylserine  Ptb   Phosphotyrosine-binding domain PX   Phox homology domain RNAi    RNA interference SH3   SRC homology domain SNARE  Soluble NSF attachment protein receptor SNC1  Suppressor of the Null allele of CAP 1 SORL1   Sortilin-related receptor 1 TfR   Transferrin receptor TGN   Trans-Golgi network TMCO4  Transmembrane and coiled-coil domain 4 TS   Temperature-sensitive VAMP   Vesicle-associated membrane protein VHS   Vps-27, Hrs and STAM domain VPS  Vacuolar protein sorting WASP   Wiskott-Aldrich syndrome protein Y2H   Yeast two-hybrid                           xiii ACKNOWLEDGEMENTS  First, and foremost, I extend my greatest gratitude to Dr. Elizabeth Conibear.  Throughout my degree, Liz has been a constant source of support, guidance, and friendship.  Her wisdom and unrelenting enthusiasm is truly inspirational, and she is, and will always be my ultimate mentor. I am grateful to my colleagues in the Conibear lab, past and present.  They have offered support, guidance, and expertise during the course of this work, and it would not have been possible without them.  I would like to thank Mike Davey and Cayetana Schluter for their assistance in the design and implementation of many experiments, and for countless helpful discussions.  I would also like to thank Benjamin Montpetit, Chris Tam, and Nicole Quenneville for their ongoing advice, encouragement, and career mentorship, and Karen Lam for her support, and for the critical reading of this dissertation.  I am also amazed by the talent of the two undergraduate students, whom I had the opportunity to supervise during my degree.  Thank you to Nandini Raghuram and Sarah Konefal for your incredible work ethic and enthusiasm. I would also like to thank our collaborators, Dr. Beverly Wendland and Dr. Lymarie Maldonado-Báez, who have been instrumental in the work presented here.  Dr. Nick Davis and Dr. Amy Roth have also contributed many insights and have aided in the development of experimental approaches. I extend my gratitude to my graduate committee: Dr. Michael Kobor, Dr. Phil Hieter, and Dr. Pamela Hoodless, for their ongoing support and advice, and for the critical reading of this dissertation. Finally, I would like to thank NSERC and the Michael Smith Foundation for providing generous financial contributions.                     xiv DEDICATION         To my family and the many people whom have helped me along the way.  Thank you for your support and encouragement.                                     1        CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW                                   2 1.1. Foreward: Membrane protein transport in the endosomal system 1.1.1. Endocytic trafficking in cellular function and human disease In every eukaryotic cell, proteins are directed to the appropriate location by membrane transport pathways.   These pathways facilitate communication within the cell, and between the cell and its environment, maintaining cell homeostasis and function (Schu, 2001; Van Vliet et al., 2003).  Endocytosis allows cells to internalize extracellular material, ligands, and plasma membrane proteins.  This removal of membrane from the cell surface by endocytosis is balanced by recycling pathways that return many of these proteins and lipids back to the plasma membrane.  These endocytic recycling pathways control the composition of the plasma membrane and contribute to diverse cellular processes, including nutrient uptake, cell adhesion and junction formation, cell migration, cytokinesis, cell polarity, and signal transduction (Jovic et al., 2010; Grant and Donaldson, 2009).  Many human diseases caused by changes in cellular homeostasis arise through compromised membrane trafficking within the endosomal system (Howell et al., 2006; Aridor and Hannan, 2000 and 2002). Endocytosis has a major role in neuronal function, as it is required for synaptic vesicle (SV) recycling within the pre-synaptic compartment (Jung and Haucke, 2007; Girard et al., 2005). It also regulates the activity-dependent exo- endocytic trafficking of postsynaptic receptors, allowing for the fine-tuning of signal strength during neurotransmission and plasticity-associated changes, uptake of growth factors in the pre-synapse, and sculpting of synaptic structure (Sheng and Kim, 2002; Dickman et al., 2006).  Disturbance of trafficking is implicated in severe neurodegenerative disorders like Alzheimer’s disease (AD), which is characterized by deposition of amyloid β (Aβ) plaques in the brain (reviewed in Mayeux and Hyslop, 2008; Selkoe, 2001).  Endosomes appear to be one of the major sites of Aβ generation and several reports indicate that altered endocytic trafficking may play role in development of AD. For instance, the neuronal sortilin-related receptor SORL1 directs trafficking of amyloid precursor protein into recycling pathways and prevents it from accumulating in the compartments generating Aβ (Andersen et al., 2005; Shah and Yu, 2006).  Mutations in SORL1 are associated with both inherited and sporadic cases of Alzheimer’s disease (Mayeux and Hyslop, 2008).  Impaired trafficking has also been shown to contribute to the pathogenesis of Huntington's disease (HD). HD is characterized by the mutant protein huntingtin, which  3 aggregates and affects membrane trafficking in neurons, leading to neurodegenerative changes (Berman and Greenamyre, 2006; Caviston and Holzbaur, 2009). Abnormal trafficking of the insulin-sensitive glucose transporter GLUT4 has been identified as a possible mechanism of disease in patients with type 2 diabetes.  In some of these patients, GLUT4 accumulates in dense membrane compartments, suggesting that defects in GLUT4 membrane trafficking may be involved in the pathogenesis of insulin resistance (Bouché et al., 2004; Karylowski et al., 2004).  Membrane traffic is also intimately connected to infection and immunity.  Viruses and bacteria often use the endocytic pathway of host cells for invasion (Mercer et al., 2010; Lin and Guttman, 2010).  In addition, large DNA viruses such as adenovirus, herpes simplex virus, Epstein-Barr virus, and cytomegalovirus have evolved sophisticated mechanisms to evade host immune surveillance by perturbing the membrane traffic of host cells, thereby preventing antigen presentation of their own products (Ohno, 2006; Ohmura-Hoshino et al., 2006).  Despite the importance of these pathways, the molecular mechanisms governing their function remain poorly understood. A better understanding membrane transport is therefore crucial for our understanding of human disease, and the development of targeted treatments. 1.1.2. Overview of intracellular transport and the regulation of vesicle formation The secretory and endocytic pathways of eukaryotic cells connect membrane-bound organelles, whose primary function is to modify newly-synthesized proteins and deliver them to the appropriate location, and to regulate the uptake and turnover of cell surface proteins (Munro, 2004; van Vliet et al., 2003). Each of these organelles is functionally specialized, and contains a unique composition of proteins and lipids pertinent to its function (Munro, 2004).  Vesicular transport pathways are essential for maintaining organelle composition and identity.  The transport of cellular material between organelles is highly organized and regulated. A large number of factors ensure that each protein is accurately delivered to its appropriate location, thus preventing the inappropriate mixing of cellular compartments.   The main compartments of the secretory and endocytic pathway are the endoplasmic reticulum (ER), Golgi apparatus, plasma membrane, and endosomal compartments (Illustration 1.1). Following delivery to the cell surface, proteins are internalized by endocytosis, and reach early endosomes, where they are then either recycled back to the  4 cell surface directly or by retrograde transport through the TGN, or targeted for degradation in the vacuole (Munro, 2004). Recycling of cell surface proteins is essential in all organisms to maintain the composition of the plasma membrane, by balancing the removal of proteins by endocytosis.  This process, called endocytic recycling is the focus of this dissertation.  Proteins are transported as ‘cargo’ within membrane-bound vesicles, which shuttle them between organelles. The selective incorporation of cargo into forming vesicles is mediated by protein coats, which are assemblies of proteins that are recruited from the cytosol. Vesicle coats recognize various components of the target membrane, including sorting signals present in the cytosolic domain of cargo proteins.  Transport between each compartment is mediated by distinct sets of coats and sorting signals, which confer specificity to these pathways (Bonifacino and Lippincott-Schwartz, 2003).  The steps of cargo recognition and vesicle formation will be described in more detail below. 1.1.2. Markers of organelle identity and the specificity of vesicular transport Vesicle transport is a precise process that requires the specific recognition of cellular membranes by components of the trafficking machinery.  How do these components ‘‘know’’ how to reach a particular cellular destination?  Most internal organelles have ‘signposts’ of identity to distinguish them from other organelles.  The main components specifying organelle identity include specific GTPases of the Rab/Arf family, SNARE proteins, and membrane lipids (Reviewed in Behnia and Munro, 2005).   GTPases The small GTPases of the Rab/Arf family are molecular switches that can alternate between a membrane-associated GTP-bound active form and a cytosolic GDP-bound inactive form.  The activity of these GTPases is controlled by proteins that regulate their GDP/GTP cycle.  These include guanine nucleotide exchange factors (GEFs), which replace GDP by GTP, and GTPase-activating proteins (GAPs), which stimulate GTP hydrolysis.  There are more than 60 different Rabs in mammalian cells, and fewer in lower eukaryotes.  Each organelle is enriched for a particular subset of these Rabs (Segev, 2010; Pereira-Leal and Seabra, 2001). Regulatory GEFs/GAPs also show a restricted distribution, which increases the functional specificity of their cognate GTPases by allowing specific and rapid control of their activity at these compartments (Kawasaki et al., 2005; Itzen and Goody, 2010).    5 Membrane phospholipids Phosphoinositide phospholipids (PIs) are also enriched on one or a small subset of organelles.  PI(4,5)P2 is enriched at the plasma membrane, PI3P at endosomal compartments, PI(3,5)P2 at the vacuole, and PI4P at the Golgi.  Much like GTPases, localized synthesis and turnover of these lipids is regulated by specific factors, namely PI kinases and phosphatases, which are also spatially restricted to a subset of organelles.  This ensures that the steady state concentration of each PI species varies between organelles.  Many components of the vesicle coat have domains that recognize these PI species. These domains include pleckstrin homology (PH), phox homology (PX), epsin amino terminal homology (ENTH) and AP180 amino-terminal holomology (ANTH) domains (Reviewed in De Matteis and Godi, 2004).  SNARE proteins The selectivity of membrane transport is also provided in part by SNARE proteins, which catalyze the fusion of the opposing membranes of the vesicle and target membrane.  Functionally, SNAREs are classified into v-SNAREs, which associate with the vesicle, and t- SNAREs, which are present on the target compartment.  Specific interaction between v- SNAREs on an incoming transport vesicle with t-SNAREs on the target membrane is the central event of the docking and fusion process (Pelham, 2001).  As each SNARE is restricted to a subset of specific compartments, SNAREs contribute to the specificity of the fusion process.  There are 25 members of this family in S. cerevisiae and 36 in Homo sapiens, most of which are small membrane proteins (Pelham, 2001; Hong, 2005)). The major, N-terminal portion of the SNARE protein is exposed in the cytoplasm, followed by a single membrane-spanning region and a few amino acids that face either the lumen of an intracellular compartment or the extracellular space.  The core feature of SNAREs is the evolutionarily conserved SNARE motif, which is present in all family members. During membrane fusion, SNAREs assemble into a four helical bundle via interactions between specific residues within their SNARE domains.  SNAREs can also be classified based on the residue contributed to this interaction.  While Q SNAREs contribute a glutamine residue to the core layer of the assembled complex, R SNAREs contribute an arginine residue.  The assembly of SNARE motifs of cognate v- and t-SNAREs generates a trans-SNARE complex bridging two membranes, which brings the lipid bilayers in close proximity and drives membrane fusion. Following fusion, the v- and t-SNAREs are present  6 on the same membrane, and the complex is thus called a cis-SNARE complex.  The cis- complex is dissembled by ATP-hydrolysis generated by the coordinated activity of two proteins: SNAP and NSF.  The SNAREs are then returned to the donor membranes (Ungar and Hughson, 2003; Brunger, 2005) In addition to SNAREs, tethering complexes have a major role in the specificity of vesicle fusion with the target membrane.  Tethering factors are the initial connection, or tether, between an intracellular trafficking vesicle and its target membrane (Barlowe 1997, Cao et al., 1998). Tethering complexes recognize the features of both the originating upstream compartment and the downstream target compartment, including SNARE proteins of both compartments, as well as activated Rab proteins and phospholipids.  Coincidence detection Individually, Rab/Arf GTPases, SNAREs and phosphoinositides are not sufficient to explain the degree of specificity achieved in vesicle transport. The precision of this process requires the simultaneous recognition of multiple determinants.  Coat recruitment at the donor membrane is achieved through combinatorial recognition of an activated Arf GTPase, specific phospholipids, and cargo.  Similarly, Rab, SNAREs and membrane lipids all contribute to tether recruitment and SNARE assembly at the target membrane. Hence, organelle identity is more precisely defined by the combination of these restricted components.  The process by which the vesicular transport machinery recognizes multiple determinants at a given membrane is often referred to in the literature as ‘coincidence detection’ (Carlton and Cullen, 2005). 1.1.4. Coat proteins mediate vesicle formation The biogenesis of transport vesicles is initiated through the recruitment of large multi-subunit protein complexes termed coats. These coats control both cargo selection and deformation of the lipid bilayer into a budding vesicle. There are three well-defined vesicle coats: COPI, COPII, and clathrin, each of which are involved in distinct transport pathways (Bonifacino and Lippincott-Schwartz, 2003; Kirchhausen, 2000).  COPI mediates both intra- Golgi transport and retrograde transport from the Golgi to the ER, while COPII functions in anterograde ER to Golgi traffic.  Clathrin was the first coat to be identified, and is the best characterized, both structurally and biochemically.  Clathrin coats are considerably more complex than the COPI/COPII coats, as they participate in multiple post-Golgi transport pathways, including receptor-mediated endocytosis, and several sorting pathways between  7 the TGN and endosomes (Kirchhausen, 2000).  To fulfill its role in each of these pathways, clathrin associates with an additional  subset of regulatory proteins.  The clathrin-coated vesicle itself is a three-layered structure, consisting of an outer clathrin layer, an inner membrane layer and an adaptor protein layer sandwiched between the two (Brodsky et al., 2001; Edeling et al., 2006). Clathrin is a large hetero-hexameric protein complex composed of three heavy chains and three light chains. Clathrin molecules self-assemble to make a spherical ‘‘clathrin lattice’’ structure, a polyhedron made of regular pentagons and hexagons. The clathrin lattice serves as a mechanical scaffold but is unable to bind directly to the membrane. Adaptor protein (AP) complexes are required for recruitment of clathrin.  These complexes interact directly with components of the lipid bilayer, cargo, and clathrin, and thus link clathrin to the membrane and to the specific cargo to be transported (Robinson, 2004).  Both clathrin and its adaptors interact with many additional regulatory components.   The formation and delivery of clathrin-coated vesicles is divided into 5 major steps: initiation, coated pit formation, vesicle budding, uncoating, and vesicle fusion (Illustration 1.2, Ritter and Wendland, 2009; Ungewickell and Hinrichsen, 2007).  Initiation is thought to begin by the recruitment of APs to specific membrane domains where they recruit cargo proteins.  Clathrin then binds to these docked AP/cargo complexes, and polymerizes to form the coat.  Further stabilization of the budding site is achieved through enhanced affinity of APs with membrane and cargo, and the recruitment of accessory proteins.   As clathrin polymerizes, accessory proteins that include BAR (Bin/amphiphysin/Rvs) domain- containing proteins, such as amphiphysin and endophilin, promote the membrane curvature required for vesicle budding.  The crescent-shaped BAR domain has a highly positively charged concave surface, contributing to electrostatic interactions that aid membrane deformation.  Further deformation of the membrane and polymerization of clathrin leads to a coated vesicle attached to the plasma membrane by a narrow neck, which pinches off to form a free coated vesicle.  Once the vesicle is formed, the clathrin coat is removed.  This allows the vesicle to fuse with its target membrane and deliver its cargo, and ensures that coat proteins are returned to the soluble pool to initiate new rounds of coat assembly (Ritter and Wendland, 2009).       8 1.2. Clathrin adaptors are key regulators of cellular transport 1.2.1. Heterotetrameric clathrin adaptors: structure and function There are three main AP complexes (AP-1, AP-2, and AP-3) in most organisms, including yeast, while higher organisms also have AP-4.  Each of these complexes regulates distinct vesicle transport pathways, localizes to different compartments, and binds distinct sets of cargo (Boehm and Bonifacino, 2002).  AP-2 mediates the formation of endocytic CCVs from the plasma membrane.  AP-1 regulates transport between the TGN and endosomes, although it is not clear in which direction it operates.  AP-3 traffics cargo from the TGN to the yeast vacuole, or the mammalian lysosome, and is involved in the biogenesis of lysosome-like organelles.  The function of AP-4 is not well understood, but it appears to be involved in TGN to endosome trafficking (Robinson, 2004).   All APs share a similar hetero-tetrameric structure, consisting of two large subunits of 100–130 kDa (β and one of either α, γ, δ, or ε), a medium-sized subunit of ~50 kDa (μ1–4 in AP1–4, respectively) and a small subunit of ~20 kDa (σ1–4 in AP1–4, respectively), (Illustration 1.3).  The large subunits are divided into an N-terminal core domain, which assembles with the medium and small subunits, and a C-terminal appendage domain, which is connected to the core by an unstructured hinge.  Each subunit and domain mediates distinct sets of regulated interactions pertinent to AP function.  The core domain of the large subunits (α, γ, δ, and ε) is required for binding to the target membrane.  The other large subunit (β) contains a clathrin box within its hinge, and is required for the recruitment of clathrin.  The medium (μ) subunits have a direct role in the recognition of cargo sorting signals, while the small (σ) subunit is mainly involved in complex stability.  Together with regions of the large subunits, the small subunits also bind to cargo sorting signals that are distinct from those recognized by the medium subunit.  Interactions between APs and their binding partners are dynamic, weak, and under strict spatiotemporal control, ensuring that vesicles form at the correct time and place, and can be rapidly disassembled once the vesicle has formed (Owen et al., 2004). Some AP complexes can exist as different isoforms that have different sorting functions.  Exchange of the large, medium, and small subunits are all observed in mammals (Owen et al., 2004; Nakatsu and Ohno, 2003). Mammals have two isoforms of both AP-1 and AP-3, which differ by the inclusion of an alternate medium subunit.  These are expressed in a cell-type specific manner. AP-3B is expressed exclusively in neurons, and is involved in synaptic vesicle biogenesis (Newell-Litwa et al., 2009).  AP-1B is expressed only in polarized  9 epithelial cells, and mediates sorting to the basolateral membrane (Traub and Apodaca, 2003). From these studies, it is clear that exchange of the medium subunit can dramatically affect the sorting function of each complex. Two isoforms of the AP-1 complex also exist in yeast, containing the alternate medium subunits Apm1 or Apm2.  While the Apm1- containing complex has a well-established role in the clathrin-mediated sorting of the Chitin synthase Chs3 and the -factor modification enzyme Ste13 between the endosomes and Golgi (Valdivia et al, 2002; Foote and Nothwehr, 2006), no role has been established for the alternate Apm2-containing complex (Stepp et al., 1995).  1.2.2. Physiological importance of clathrin adaptors The physiological importance of AP complexes is illustrated by studies in multiple organisms.  Knockout of AP-1A or AP-2 results in embryonic lethality in C. elegans and mice, indicating that they are essential for normal development (Ohno, 2006).  Mutations in AP- 3A underlie the autosomal recessive disorder Hermansky-Pudlak syndrome 2 (Dell'Angelica et al., 1999).  This disease is characterized by defective transport to lysosome-related organelles, including melanosomes and platelet dense granules, and results in clinical features including albinism, platelet storage pool deficiency, defective immune function, and bleeding defects (Huizing and Gahl, 2002 and Huizing et al., 2002).  In mice, knockout of the neuronal-specific AP-3B causes epileptic seizures and neurotransmission defects, as a result of mis-regulation of synaptic vesicle formation (Nakatsu et al., 2004; Seong et al., 2005).  In addition to demonstrating the critical role of APs, these studies illustrate that different phenotypic consequences can result from deficiency of closely related AP isoforms. The physiological importance of AP complexes has driven considerable research into their function.  The mechanisms regulating AP membrane recruitment, cargo recognition, and un- coating are described below. 1.2.3. Recruitment and un-coating of AP complexes: membrane phospholipids  Interaction with membrane phospholipids appears to be an early event in the recruitment and activation of APs at their target membranes.  Accordingly, the control of phosphoinositide levels by kinases and phosphatases is important in regulating AP recruitment and uncoating (Edeling et al., 2006).  For example, higher rates of endocytic internalization by AP2 are associated with increased levels of PI(4,5)P2, caused by overexpression of the type I phosphatidylinositol 4-phosphate 5-kinase h (PIP5KIh) (Krauss et al., 2006) .  There is a good correlation between PI(4,5)P2 levels, association of AP-2 with  10 the cell surface, and the number of clathrin coated structures (Gaidarov and Keen, 1999; Padrón et al., 2003; ) Conversely, synaptojanin 1, which hydrolyses PtdIns(4,5)P2 to PtdIns(4)P, promotes the dissociation of AP-2 from the membrane of CCVs following budding.  In mice knockout studies, the absence of synaptojanin 1 leads to 100% mortality within 2 weeks of birth, elevated steady-state levels of PI(4,5)P2, an increased number of clathrin-coated vesicles in presynaptic terminals, and increased synaptic depression in hippocampal slices (Cremona et al., 1999). The Golgi contains the main cellular pool of PI(4)P, generated by the phosphorylation of PtdIns by the type II alpha phosphatidylinsositol 4-kinase PI4KII (D'Angelo et al., 2008).  In both yeast and mammalian cells, PI4KII homologs are involved in sorting at the late Golgi (De Matteis and D'Angelo, 2007).  AP-1 has been shown to bind directly to PI(4)P in mammalian cells, and reduction of PI(4)P levels results in the redistribution of AP-1 from Golgi compartments to the cytosol  (Wang et al., 2003).  1.2.4. AP appendage domains interact with multiple regulators The appendage domains of the large AP subunits serve as a major interaction hub for various regulatory proteins that help drive rapid assembly of AP-containing vesicles and aid in cargo recognition.  These proteins, called “accessory” factors, fall into three categories: regulatory proteins, mechanical/assembly proteins, and alternate adaptors (Traub, 2005).  Examples of regulatory proteins include the kinases AAK1, and GAK, which phosphorylate the  subunit of AP-2 and AP-1, respectively.  These phosphorylation events are required for productive association of AP-1 and AP-2 with cargo.   Mechanical/assembly proteins act during and after cargo recognition to synchronize interactions between adaptors and other components of the vesicle formation machinery, and may also contribute directly to the vesicle budding event. Although there seem to be multiple mechanisms involved, interaction of clathrin with these proteins appears to increase the intrinsic curvature and rigidity of coated vesicles at the membrane.  Many of these proteins are lipid-binding proteins that contribute to membrane deformation (Lundmark and Carlsson, 2010).  A well-studied example is epsin, an ENTH domain protein, which inserts a hydrophobic helix into the membrane, leading to membrane curvature (Horvath et al., 2007).  Proteins containing BAR domains facilitate the membrane bending required at late stages of vesicle formation.  These include amphiphysin1 and Sorting nexin 9 (SNX9) (Itoh and De Camilli, 2006).   Alternate sorting adaptors or CLASPs link a subset of cargo to AP complexes.  Most  11 CLASPs identified to date interact with the AP appendage domain.  Mechanisms of AP cargo recognition and the role of CLASPs are discussed below.  1.2.5. Mechanisms of AP cargo recognition Most signals recognized by AP complexes consist of short, linear sequences of amino acid residues present in the cytosolic domain of cargo proteins.  Two of the most widely- used and best understood signals conform to YXXΦ ‘Tyrosine’ motif (in which X represents any amino acid and Φ represents a large hydrophobic residue) and [D/E]XXXL[L/I] ‘acidic dileucine’ motif.  All APs recognize YXXΦ motifs, and some additionally bind dileucine motifs (Heilker et al., 1999; Bonifacino and Traub, 2003). Examples of YXXΦ-containing cargo include mammalian LAMPs, the Transferrin receptor and CD63, and yeast Yck3 (Bonifacino and Traub, 2003; Sun et al., 2004). Dileucine-based cargo includes mammalian tyrosinase and GLUT4, and yeast ALP and Gap1 (Bonifacino and Traub, 2003).  The medium (μ) subunit of each AP interacts with a distinct but overlapping set of YXXΦ signals, as defined by deviation in the residues other than the critical tyrosine.  This partially explains how each is able to recognize a different subset of YXXΦ-based cargo. The μ subunit is organized into two main domains, separated by a flexible linker.  The N- terminal domain assembles with the core complex, while the C-terminal domain contains the YXXΦ binding site (Owen et al., 2004). The C-terminal domain is further divided into two β-sandwich subdomains (A and B).  Subdomain A is folded to create a cargo-binding pocket.  The critical Y and Φ residues fit into hydrophobic pockets on the surface of this domain, and binding is mediated through both hydrogen bonding and backbone interactions (Edeling et al., 2006, Brodsky et al., 2001). Structural studies have demonstrated that in order to efficiently bind cargo, the μ subunit undergoes a large-scale rearrangement relative to the rest of the complex.  In the inactive form, the YXXΦ binding site on the μ subunit is occluded by interaction with the large subunit (closed form), and is freed from this occlusion by the movement of the C-terminal cargo binding domain (open form).  This rearrangement occurs following binding of the complex to membrane lipids, and is stabilized by phosphorylation of a specific threonine residue within the unstructured linker of μ2 by the kinase AAK1, and by association with cargo.  This complex rearrangement is thought to couple cargo binding to membrane attachment, therefore preventing inappropriate interactions the complex and cytosolic proteins (Jackson et al., 2010).  12 The dileucine signal is structurally distinct from the tyrosine-based signal, and binds to the AP complex in a unique manner.  The interaction surface is primarily positioned on the small (σ) subunit.  Similarly to the recognition of tyrosine-based signals by the μ subunit, interaction of dileucine-based signals requires a structural rearrangement of the complex.  In this case, the binding site on the σ subunit is blocked by the large β subunit, which must shift to expose the binding site.  This shift may be mediated through phosphorylation of a tyrosine residue on the β subunit, and is less dramatic than the large- scale movement of the μ subunit relative to the core.  Dileucine-based peptides can engage in binding while the tyrosine binding site remains in a closed conformation (Huang et al., 2003). It seems that cargo recognition is not a mandatory step in AP recruitment, as APs with mutated cargo binding sites still assemble into CCVS.  Cargo binding has, however, been shown to enhance the membrane affinity of APs.  It is likely that cargo capture occurs concomitantly with coat polymerization.  The numerous simultaneous contacts that APs can establish with other factors and accessory proteins serve to explain how APs can associate with the membrane before binding to cargo.  It also appears that cargo load is dynamically monitored in the forming vesicle by APs and their regulators, in order to prevent unproductive budding (Traub, 2009). For example, overexpression of the transferrin receptor (TfR), a well-studied AP-2 cargo, decreases the number buds that abort prior to formation or scission (Loerke et al., 2009).  1.2.6. Non-canonical cargo sorting signals are recognized by CLASPS Not all cargo sorting motifs conform to the YXXΦ or [D/E]XXXL[L/I] based motif.  In fact, there a broad range of alternative sorting signals.  These include variants of the tyrosine and dileucine motifs, but can also involve various post-translational modifications, including phosphorylation or ubiquitination. These signals are not recognized directly by AP complexes, but by a family of AP-associated monomeric adaptors called clathrin- associated sorting proteins (CLASPs), which link APs to cargo containing these alternative signals.  Although they share little overall sequence homology with APs, all have a clathrin- binding box, and/or AP interaction sequences that mediate interaction with the clathrin heavy chain and the AP appendage domain, and contain binding sites for membrane phospholipids (reviewed in Traub, 2009 and Maldonado-Baez and Wendland, 2006).  The phosphotyrosine-binding (Ptb) CLASPs, including β-arrestins, recognize [FY]XNPX[YF] signals.  These mediate internalization of phosphorylated GPCR, by recruiting  13 activated receptors to pre-existing AP-2 containing endocytic pits.  ARH and disabled2 (DAB2) recognize the tyrosine-based FXNPXY signal within the LDL receptor, and mediate its internalization. The epsin superfamily is another subset of CLASPs, which includes AP180/CALM, epsin1, and Hip1/Hip1R.  Each of these has structurally related ENTH/ANTH domains, and primarily recognizes ubiquitylated cargo.  These include the yeast epsin homologs Ent1 and Ent2, which mediate internalization of monoubiquitinated cargo, which is the primary internalization signal in yeast (Maldonado-Baez and Wendland, 2006).  Another family of Golgi regulatory adaptors is the Golgi-localized, gamma-ear containing, ARF-binding (GGA) proteins. There are two forms of Gga in yeast (Gga1 and Gga2), which are thought to be largely redundant, and three forms of Gga in mammalian cells, which may have unique sorting roles. These monomeric ubiquitously-expressed proteins have 4 modular domains (VHS, GAT, a hinge and GAE) that essentially recapitulate all of the functional attributes of AP-1 and AP-2. The VHS domain binds to DXXLL-type acidic cluster sorting signals in mammalian cells, and recognizes the receptor Vps10 in yeast.  The GAT domain is required for membrane recruitment by activated Arf1 and PI4P at the Golgi, and interacts with ubiquitylated cargo.  Clathrin binding is mediated by a variant of the clathrin box motif that is present in the hinge region of Gga.  Finally, the GAE domain interacts with accessory proteins that are involved in cargo selection and membrane binding (reviewed in Ghosh and Kornfeld, 2004 and Bonifacino, 2004).  Gga proteins are required for sorting of proteins, including the SNARE Pep12, from the Golgi to the late endosome (Black and Pelham, 2000). The use of multiple adaptors provides plasticity to allow precise temporal control in the face of high traffic volumes, ensuring that cargo do not compete with each other for inclusion into coated vesicles (Sorkin, 2004; Traub, 2003).  Alternate adaptors can be regulated to alter the sorting of individual cargo, without affecting the sorting of other cargo by the main AP complexes. 1.3. Transport of SNARE proteins 1.3.1. Alternative sorting mechanisms regulate SNARE transport SNARE proteins are critical regulators of vesicle fusion.  An important concept is that SNAREs themselves must be accurately transported in the cell.  To ensure that a vesicle can fuse with its target membrane, sufficient amounts of the correct v-SNARE must be incorporated into a vesicle during formation, and its cognate t-SNARE must be correctly  14 sorted to its target membrane.  Following fusion, SNAREs must also be recycled back to the donor compartment in order for fusion processes to continue (Miller et al., 2007).  Some SNAREs interact with directly with AP complexes through canonical motifs, including the TGN-localized VAMP4, which binds to AP-1 through a dileucine-based signal (Peden et al., 2001).  Most SNAREs, however, lack the canonical motifs recognized by adaptor proteins.  Recent studies have demonstrated that SNARE sorting often involves recognition by unconventional adaptors, and novel methods of cargo interaction.  In both yeast and mammals, epsin family proteins interact with various SNAREs involved in the late endocytic pathway.  In mammals, enthoprotin, also called epsinR  (Wasiak et al., 2002) interacts with the Q- SNARES vti1b, syntaxin 7 and syntaxin 8, involved in late endosome/lysosome transport (Chidambaram et al., 2004 and 2008).  The yeast epsinR homolog Ent3 binds the related SNAREs Vti1, Pep12 and Syn8, which participate in fusion with the late endosome (Chidambaram et al., 2004). The localization of Vti1 and Pep12 is dependent on Ent3 together with the partially redundant Ent5, indicating that the cargo-sorting function of Ent3 is conserved in yeast and extends to more than one SNARE (Chidambaram et al., 2008). The clathrin-mediated endocytic retrieval of VAMP7 from the plasma membrane requires the protein Hrb1 (HIV Rev-binding protein), (Pryor et al., 2008).  Hrb1 is an ArfGAP, which binds both the AP-2 appendage domain and clathrin, demonstrating the properties of an alternate adaptor.    For SNAREs, the transport signal recognized by adaptors can consist of a folded epitope instead of a short cytosolic motif.  The ENTH domain of EpsinR interacts with the N- terminus of vti1b via a conformational motif, which includes at least two turns and one helix of epsinR and amino acid residues from three helices of vti1b (Miller et al., 2007).  VAMP7 binds Hrb1 through its N-terminal longin domain, a highly structured region of 120 amino acids (Pryor et al., 2008). These studies demonstrate that mechanistically novel interactions occur between given SNARE/adaptor pairs.  These specific mechanisms may ensure that there is no competition between SNAREs and standard motif-containing cargo for inclusion in a nascent vesicle.  This is important, as a vesicle must include both cargo and SNAREs to be productively delivered to the target membrane (Miller et al, 2007).  As the proper sorting of SNAREs is critical to the integrity of essential transport processes, there is considerable interest in uncovering how they are recognized and transported. 1.3.2. What is the role of palmitoylation in SNARE transport? Several SNARE proteins are post-translationally modified by palmitoylation, the  15 reversible addition of palmitate to a cysteine via thioesterification (Roth et al., 2006). SNAREs lacking transmembrane regions require palmitoylation for membrane anchoring (Dietrich et al., 2005; Veit et al., 1996). Many integral membrane SNAREs are also palmitoylated, but the functional consequences of these modifications are not clear (Roth et al., 2006). There is growing evidence that this could regulate the trafficking of these transmembrane SNAREs. For example, palmitoylation of the yeast SNARE Tlg1, which mediates endosome to Golgi transport, protects it from ubiquitination and subsequent degradation in the vacuole (Valdez-Taubas and Pelham, 2005). The mammalian endosomal SNARE syntaxin7 is also palmitoylated.  While it normally localizes to early and late endosomes, preventing syntaxin7 palmitoylation leads to its accumulation on the cell surface (He and Linder, 2009). Several studies have highlighted regulatory effects of palmitoylation on either retention or anterograde trafficking of proteins at the ER–Golgi or protein cycling within the endosomal/lysosomal system (Linder and Deschenes, 2007; Greaves et al., 2009). Palmitoylation can also aid in the partitioning of proteins into cholesterol-rich membrane subdomains, and in changing protein orientation and thus affecting protein-protein interactions that could regulate trafficking (Linder and Deschenes, 2007).   The mechanisms by which palmitoylation regulates the dynamics of SNARE transport are an important unresolved issue in the field.  It remains unclear if palmitoylation directly affects the recognition of SNAREs by components of the transport machinery, and whether the consequences of this modification are generally applicable to all SNARES. 1.4. Endocytosis and endocytic recycling pathways 1.4.1. Yeast as a model for endocytic recycling   The protein families that mediate vesicle trafficking are conserved from yeast to mammals, as is the compartmentalization throughout the cell from the endoplasmic reticulum to the plasma membrane.  Yeast has therefore been used as a model for both genetic and biochemical analyses to study transport processes for decades (Bock et al., 2001). These studies have revealed that identifying the transport machinery and their pathway relationships in yeast can inform relationships between gene products in mammalian cells.  Despite this, there do appear to be some important differences between transport in yeast and mammalian cells, especially in mechanisms regulating endocytosis  16 and recycling.  The similarities and differences in these pathways, and possible explanations for these discrepancies are discussed below.   1.4.2. Do yeast and mammals share common mechanisms of endocytosis?  Elegant studies in both yeast and mammalian systems have revealed an intricate network of endocytic regulatory proteins, and have used novel methods to investigate their dynamics at endocytic sites.   This has revealed that most components of the endocytic machinery are highly conserved from yeast to humans.  These studies also show that actin polymerization has an important role in the endocytic process (Engqvist-Goldstein and Drubin, 2003). Most progress in defining the order and timing of endocytic internalization events has resulted from real-time, live cell fluorescence microscopy.  A striking feature revealed by these studies is that proteins fall into discrete groups based on their dynamic relationship to clathrin-coated structures, which is also conserved in both mammalian cells and yeast (Kaksonen et al., 2005; Perrais and Merrifield, 2005).  In yeast, four protein modules cooperate to drive the distinct stages of endocytic vesicle formation, based on their dynamic localization.  The early coat complex is the first to arrive which recruit cargo and establish the endocytic site. The late coat module is then recruited, followed by components of the actin polymerization machinery including the Arp2/3 complex and its activators. An actin network is formed by the Arp2/3 complex, which then drives the rapid internalization of the vesicle.  Finally, the vesicle scission machinery pinches the vesicle off the membrane, and coat components are released (Kaksonen et al., 2005; Toret et al., 2008).  Despite the similar timeline of recruitment of endocytic homologs in yeast and mammals, there appear to be some critical differences in their relative importance. The endocytic adaptor AP-2 is required for endocytosis in mammals, but appears to be dispensable for uptake in yeast.  Targeted disruption of AP-2 is lethal in mammalian cells (Mitsunari et al., 2005), and has been shown to block the uptake of multiple cargo, including the transferrin receptor (Conner and Schmid, 2003), as well as a population of lysosome-associated membrane proteins that traffic via the plasma membrane (Janvier and Bonifacino, 2005).  Yeast AP-2 deletion mutants, however, are viable, and have no defects in the internalization of commonly studied endocytic cargo, including Ste6 (Burston et al., 2009; Conibear, 2010).    Actin is an essential component of the cytoskeleton, and localizes to endocytic sites in both yeast and mammalian cells (Engqvist-Goldstein and Drubin, 2003). The importance of dynamic actin regulation in endocytic vesicle formation seems to differ between yeast and  17 mammals.  In yeast, actin and actin-regulatory proteins are essential for this process.  Treatment with inhibitors of actin polymerization, such as latrunculin, or deletion of actin- regulatory proteins blocks endocytosis completely in yeast.  Actin is required to drive invagination and post-scission movement of the newly formed vesicle (Kaksonen et al., 2006). In mammalian cells, actin appears to be less important, as blocking polymerization results in only partial endocytic defects (Engqvist-Goldstein and Drubin, 2003).    Finally, the GTPase dynamin has a key role in the scission of endocytic vesicles in mammalian cells.  Upon GTP-binding, it self-assembles into a ring-like collar around the neck of deeply invaginated, mature coated pits.  Subsequent GTP hydrolysis causes constriction of this collar, which facilitates vesicle fission.  Dynamin was not previously thought to play a role in yeast endocytosis, although a recent study has suggested that it may be involved (Smaczynska-de Rooij et al., 2010). 1.4.3. A comparison of the endosomal system in yeast and mammalian cells   The basic organization of the endosomal system in mammalian cells is now fairly well defined.   It has functionally and physically distinct compartments, which includes early/sorting endosomes, recycling endosomes, lysosomes, and the TGN (Illustration 1.4.).  The sorting endosome is the first destination for endocytosed cargo.  Sorting events initiated at this compartment determine the subsequent fate of internalized proteins, directing them for either recycling to the plasma membrane, delivery to the trans-Golgi network, or for degradation. The sorting endosomes have a characteristic morphology, consisting of thin tubular extensions, and vesicular structures.  These endosomes contain distinct membrane subdomains, in which cargo are concentrated for different downstream transport steps.  Proteins targeted for recycling have been shown to cluster within tubules, while those destined for degradation are concentrated within the vesicular structures. There are multiple routes back to the cell surface from sorting endosomes.  Molecules are delivered directly back to the plasma membrane either through an intermediate compartment called the endocytic recycling compartment, or can alternatively pass through the Golgi from sorting endosomes prior to surface redelivery.  Each of these pathways has different kinetics of transport.  Proteins targeted for degradation are transported from sorting endosomes, which mature into compartments called the multivesicular body (MVB), and subsequently reach lysosomes.  The first step in targeting these proteins for lysosomal degradation is often the ubiquitination of their cytoplasmic domain.  These ubiquitinated receptors are recognized by the ESCRT (endosomal sorting required for transport) complex  18 at the MVB, which sorts them for delivery to later compartments.  The ESCRT complex invaginates the endosomal membrane to form the internal vesicles of the MVB. Fusion of the limiting membrane of the MVB with the lysosome ultimately delivers the internalized vesicles to the lumen for degradation.    Most mammalian endocytic compartments can be distinguished based on specific lipid composition.  Sorting and recycling endosomes contain high amounts of PI(3)P, while later compartments are enriched in PI(3,5)P2 and the lipid lysobisphosphatidic acid (LBPA).  As different endocytic compartments are quite distinct in mammalian cells, most approaches used to study them are based on morphology, and there are a variety of markers available for proteins and lipids at each of these compartments, also facilitating their study (Gruenberg, 2003)  Yeast cells share many conserved recycling components and mechanisms with mammalian cells (Illustration 1.4.; left).  In yeast, however, the morphological distinction between different endocytic compartments is more elusive than in mammals, and LBPA has not been detected in yeast.  It is not clear whether yeast has distinct populations of endosomes, or if subdomains with different lipid compositions exist on these organelles, like those in mammals (Russell et al., 2006).  Due to the difficulty in discerning endosomal components in yeast, most compartments have traditionally been defined by genetic analysis, through identifying mutants that lead to the mistargeting of cargo known to transit through the endosomal system.  Despite the apparent differences, some key aspects of these sorting pathways appear to be remarkably conserved.  In fact, the molecular machinery involved in sorting at the MVB was first identified in yeast. Loss of the ESCRT machinery results in a readily identifiable phenotype: the accumulation of endosomal membranes resulting from the failure in the formation of MVB luminal vesicles (Raymond et al., 1992).  Despite progress in identifying components of the late endocytic (MVB) pathway, the early endocytic pathway has not been as well characterized in yeast (Pelham, 2002).  Several proteins have been used as markers to study these recycling pathways.  For example, the pheromone-induced endocytosis of Ste3 results in its recycling back to the plasma membrane (Chen and Davis 2000, 2002), while the chitin synthase Chs3 translocates between sites of chitin deposition on the cell surface and endosomes (Ziman et al. 1998; Valdivia et al., 2002).    Another marker that has been used to study endocytic recycling in yeast is the exocytic v-SNARE Snc1, which is involved in fusion of Golgi-derived secretory vesicles with  19 the plasma membrane, and recycles through early endosomes to the Golgi before redelivery to the cell surface. The localization of GFP-Snc1 has typically been used to identify genes required for its early endosomal recycling.  In wild-type cells, Snc1 is localized at the plasma membrane with some punctate staining of internal structures, and has been found to either accumulate in intracellular structures or is enhanced at the plasma membrane in various recycling mutants (Lewis et al. 2000; Galan et al. 2001).  Multiple proteins have been implicated in Snc1 recycling, based on the effects of deleting these proteins on the localization of GFP-Snc1.  These include the sorting nexin, Snx4, which interacts specifically with the endosome-enriched PI3P (Hettema et al., 2003), and the Arf-GAP Gcs1, which binds directly to Snx4 (Robinson et al., 2006).  This process also requires Rcy1, the Ypt31/32 GTPases that facilitate Golgi export and act upstream of Rcy1 (Chen et al., 2005), and components of the coatomer coat complex (Robinson et al., 2006).  Importantly, the recycling of Snc1 is not blocked by loss of the MVB sorting machinery, including the ESCRT and retromer complexes, suggesting that Snc1 transits through a distinct endosomal population (Lewis et al., 2000; Schluter et al., 2008; Hettema et al., 2003). The Snc1 recycling pathway has not previously been genetically well characterized, and in most cases, the relationships between genes required for this pathway are not well understood.     To understand the similarities and differences between these sorting pathways in yeast and other organisms, it will be important to develop new methods to better define these early sorting steps.  It is likely that the development and application of novel technologies to study these pathways in yeast will help resolve these differences, and lead to a better understanding of endosomal sorting in eukaryotic cells.  1.5. Yeast functional genomics: a tool to dissect trafficking pathways  1.5.1. Systems biology approaches to study membrane transport   The work described in this dissertation uses yeast functional genomics to study mechanisms regulating endocytic recycling. This approach identifies protein complexes and pathways that are coordinately required in a broad cellular context.  By considering the requirements for endocytic recycling on a genome-wide level, we aim to elucidate basic principles that may not be apparent at the level of individual components, and to understand how individual genes and pathways are connected to carry out a common process on the level of a whole organism.   20  S. cerevisiae is an important model system for the development of large-scale genomic and proteomic technologies, due to its compact genome and relatively simple genetics.  The yeast genome was the first eukaryotic genome to be successfully sequenced, and over the last decade, numerous genomic methodologies have been developed to identify functions for the roughly 5800 genes in yeast.  A collection of ~4800 yeast mutant strains, comprised of systematic knock-out disruptions of all non-essential genes, is available in haploid (MATa and MATα), homozygous and heterozygous diploid strains (Giaever et al., 2002). The deletion collection has allowed for a variety of “reverse genetics” investigations, leading to the discovery of novel components in genetic pathways and protein complexes (Scherens and Goffeau, 2004). In recent years, additional genome wide collections have been developed, allowing for studies of over-expression, localization, protein-protein interactions, and essential genes (Boone et al., 2007). Finally, yeast is easy to manipulate for cell biological and biochemical studies, providing a robust system for functional genomics.   Genetic interactions, which represent the modulation of the phenotype of one mutation by the presence of a second mutation, have long been used as a tool to dissect the functional relationships among sets of genes (Guarente, 1993; Kaiser and Schekman, 1990). Classically, researchers have looked for strong qualitative differences between observed phenotypes of double mutants and the phenotypes of the two related single mutants. For example, a relationship referred to as synthetic lethality is observed when two mutations are not lethal when present individually but, when combined, result in an inviable organism. Synthetic sick/ lethal, or negative, interactions have been used as evidence that two genes act in independent but complementary pathways. Strong negative genetic interactions, in which the double mutant phenotype is stronger than the phenotype of either single mutant, often suggests that these genes work in parallel/redundant pathways.  On the other hand, a positive interaction, in which a normally deleterious mutation has no additive effect in the context of a second mutation, often identifies genes that act in the same pathway or complex.  Investigating these interactions has provided a wealth of data about functional relationships between genes in yeast (Collins et al., 2010).  In recent years, technology has developed allowing genetic interactions to be evaluated on a large scale.  Genes that are closely related in function often share highly similar patterns of genetic interactions.  Thus, the pattern of genetic interactions of each mutant can be considered as a phenotypic signature. Genes that share similar signatures can be identified and grouped, a useful method for identifying functionally related genes (Schuldiner et al., 2005; Tong et al.,  21 2004).  One problem with this approach is that with 6000 genes in the yeast genome, a complete genetic interaction map requires accurately evaluating 18 million double mutant phenotypes, which is beyond the capacity of most studies.  The E-MAP (Epistatic miniarray profiling) approach provides a shortcut, in which pairwise interactions are measured among a rationally chosen subset of genes, predicted to to have a shared function in a given process (Schuldiner et al., 2005; Collins et al., 2010).  The subset of genes can be selected based on multiple criteria, including shared protein localization (Schuldiner et al., 2005), or protein-protein interaction data (Collins et al., 2007).  1.5.2. Phenotypic screening in yeast to identify transport components Genetic approaches are a well-established, commonly used approach to evaluate gene function for a wide variety of cellular pathways. In yeast, genetic screens have been immensely successful for discovering genes involved in the secretory, Golgi, endosomal and vacuolar transport pathways (Raymond et al., 1996; Novick et al., 1980; Bankaitis et al., 1996). Characterization of mutants discovered in these screens has revealed roles in cargo sorting, vesicle budding, and tethering/fusion, emphasizing the power of this approach to discover genes with direct roles in trafficking.   In recent years, genetic screens have been developed which focus on phenotypes directly related to trafficking.  This involves detection of missorting of specific cargo proteins within different transport pathways in the genome-wide deletion collection, allowing for systematic identification of the pathway requirements.  Many genes, for example, have been identified that are required for the sorting of the CPY receptor Vps10, between the Golgi and late endosome through these phenotypic screening methods.  While in the Golgi, Vps10 binds newly synthesized pro-CPY, and together, Vps10 and pro-CPY are transported to the late endosome.  At the late endosome, CPY dissociates from Vps10, and is delivered to the vacuole, where it matures and functions.  In the absence of Vps10, or other factors required for transport of pro-CPY, this pathway is blocked, resulting in the missorting of pro-CPY to the extra-cellular space.  CPY secretion can be detected based on a colony overlay assay, in which yeast colonies are grown on a nitrocellulose membrane, and secreted pro-CPY is detected by western blotting.  Identifying mutants in the genome-wide collection has that lead to pro-CPY secretion have been a well-used screening approach to identify genes involved in Golgi/vacuolar transport (Bonangelino et al., 2002; Schluter et al., 2008). Despite the progress in yeast functional genomics, over 20% of all yeast genes remain functionally uncharacterized (Peña-Castillo and Hughes, 2007).  Furthermore, many  22 yeast homologs of mammalian genes known to be involved in characterized transport steps have not yet been shown to be functionally important.  A prime example is the discrepancy between the requirement for many yeast and mammalian endocytosis genes, as previously described (Conibear, 2010).  One explanation for this discrepancy is that deletion of many of these genes may lead to a weak phenotype in yeast that is undetectable by standard assays of transport defects. This issue necessitates the development of novel quantitative strategies, which are sensitive enough to detect these mild defects. 1.6. Research objectives and hypotheses 1.6.1. A new approach for identifying endocytic recycling components in yeast   The endocytic recycling pathway of Snc1 appears to involve many genes not required for the transport of other recycling cargo (Kama et al., 2007; Robinson et al., 2006).  It is therefore expected that developing a functional genomics approach to dissect the Snc1 recycling pathway in yeast could identify previously unrecognized endocytic recycling factors, and generate insight into their functional relationships. Snc1 was selected as a reporter for endocytic recycling due to the similarity of its sorting pathway to that of mammalian VAMP2/synaptobrevin.  In mammalian neuronal cells, VAMP2 mediates the fusion of synaptic vesicles with the presynaptic membrane, and is required for neurotransmitter release.  Its recycling allows continued rounds of synaptic vesicle fusion, and sustained neurotransmission (Grote et al., 1995).  As defects in pathways of synaptic vesicle formation and recycling are prominent in a variety of neurological disorders, systematically characterizing the genes required for its sorting pathway will aid in the identification of causal variants in human disease, and ultimately will contribute to the development of drugs that are targeted to correct the resulting defects.  The work described in this dissertation uses a genome-wide phenotypic screen to identify components involved in Snc1 endocytic recycling based on quantitative genome- wide techniques to measure the localization of the Snc1 in the genome-wide deletion collection. In this study, a reporter for Snc1 recycling was created by fusing the sucrose converting enzyme invertase, encoded by the gene SUC2, to the C-terminus of GFP-Snc1. The invertase portion is exposed to the extracellular space, allowing detection of plasma membrane localization by whole colony assays of invertase activity. The identification of transport defects in the genome-wide collection relies on densitometry measurements of cell surface invertase activity in each mutant.  This provides a sensitive and quantitative  23 assay, which is compatible with high-throughput approach. The following chapters are based on our genome-wide phenotypic assay for increased Snc1 surface levels.  The goal of this screen was to identify genes regulating Snc1 endocytosis and recycling in a systematic and non-biased manner.  Due to its sensitive and quantitative nature, we anticipated that it would reveal functions for genes that were previously uncharacterized due to weak mutant phenotypes or cargo-specific functions.  By evaluating the transport pathway of Snc1, we also aimed to address the mechanisms regulating the sorting of SNARE proteins, one of the least understood issues in the field.  We anticipated that we would identify novel factors required for Snc1 sorting, including cargo-specific adaptor proteins and regulators that are not required for the uptake or recycling of other proteins.  Chapter 2 is focused on genes required for the endocytosis of Snc1 from the plasma membrane, and the downstream analysis of novel components regulating this process.  Chapter 3 is an extension of the results of the primary screen, and investigates the function of the previously uncharacterized clathrin adaptor AP- 1R and its interacting protein Ima1 in Snc1 endosomal recycling.       24 1.7. Illustrations                 Illustration 1.1.  Intracellular compartments and transport pathways.  Following synthesis in the endoplasmic reticulum (ER), proteins are transported to the Golgi (1). The last compartment of the Golgi (the trans-Golgi network) sorts cargo for delivery to multiple possible destinations.  From the TGN, proteins move by anterograde transport to the plasma membrane (2), or are diverted to endosomes (3), or to the vacuole for targeted degradation (4). Following cell surface delivery, some proteins are retrieved through endocytosis (5), and are recycled back to the surface via the endosomes and Golgi (Endocytic recycling, (6)).   25        Illustration 1.2. Steps in clathrin-coated vesicle formation and transport. Vesicle formation is initiated when adaptor proteins are recruited to the donor membrane and bind transmembrane cargo (1).  Adaptor/cargo complexes then recruit components of the clathrin coat, leading to its polymerization.  These include BAR domain proteins, which promote the membrane curvature required for budding (2).  The vesicle is internalized, and pinches off of the target membrane (3).  Adaptors and other components are subsequently removed from the vesicle (4).  Finally, the uncoated vesicle fuses with the target membrane, delivering its cargo (5).   26  Illustration 1.3. Clathrin Adaptor (AP) structure Structure of the heterotetrameric AP-1 complex.  The complex consists of two large subunits (γ and β1), one medium subunit (μ1), and one small subunit (σ1).  The large subunits are divided into a core domain, which assembles with the medium and small subunits, and appendage domains, connected to the core by flexible hinges.  Each subunit interacts with a different subset of transport components, as indicated.                 Illustration 1.4. Comparison of endocytic recycling compartments and pathways in yeast and mammalian cells.  Following endocytosis, yeast cell surface proteins are transported the the early endosome (EE), from which they can recycle back to the plasma membrane directly, or by passing throught the TGN.  Alternatively, they can be targeted to the vacuole for degradation through transport to the late endosome (LE).  In mammalian cells, internalized proteins first reach the sorting endosome (SE), from which they can take a variety of routes back to the surface.  They are either recycled directly back from early endosomes (rapid recycling), or can pass through the intermediate endocytic recycling compartment (ERC, slow recycling).  They can also recycle by passing through the TGN from the endocytic recycling compartment.  Proteins targeted for degradation are transported through late endosomes (LE), to the lysosome, the mammalian equivalent of the yeast vacuole. Core  b    b Appendage AppendageAccessory proteins Clathrin Membrane phospholipids Cargo (Yxx) Membrane phospholipids Cargo D/ExxLL Accessory proteins 27 CHAPTER 2. REGULATORS OF YEAST ENDOCYTOSIS IDENTIFIED BY SYSTEMATIC QUANTITATIVE ANALYSIS. 1  I  II                                                                                        1 A version of this chapter has been published as: Burston HE, Maldonado-Baez L, Davey M, Montpetit B, Schluter C, Wendland B, and Conibear E. (2008) Regulators of yeast endocytosis identified by systematic quantitative analysis. Journal of Cell Biology. 185 (6): 1097-1111.       28 2.1. Synopsis  This chapter describes the screening approach used to identify genes involved in the Snc1 endocytic recycling pathway, and focuses on genes that were identified to play a role in yeast endocytosis, and the relationships between them.  The main goal of this study was to explain why internalization defects have not been shown for many yeast homologs of mammalian endocytosis genes.  This is a question that has puzzled many in the field, leading to the hypothesis that internalization in yeast and mammals utilizes fundamentally different mechanisms.  Multiple explanations have been advanced to account for these differences. First, deletion of yeast endocytic homologs may have internalization defects that have not yet been detected, due to weak defects that cannot be measured by standard assays, which may be a result of functional redundancy.  Second, many of these genes may be important only for a subset of endocytic cargo.  To  overcome these limitations, a quantitative approach was developed to systematically assess endocytic defects across the genome, using a novel enzymatic reporter based on Snc1. This revealed roles for many of these yeast endocytic homologs, as well as other previously uncharacterized genes.  Genetic interaction mapping was used to place these genes into functional modules containing known and novel endocytic regulators.  Hypothesis-driven downstream analysis was then used to functionally characterize novel regulators.  In addition, an array-based comparison of two different reporters containing distinct internalization signals was carried out in order to evaluate cargo specificity on a large scale.   This study demonstrates that clathrin and the yeast AP180 clathrin adaptor proteins have a cargo-specific role in Snc1 internalization. Additionally, low dye binding 17 (LDB17) is shown to be a novel conserved component of the endocytic machinery. Ldb17 is recruited to cortical actin patches before actin polymerization and regulates normal coat dynamics and actin assembly. Collectively, these findings highlight the conserved machinery and reveal novel mechanisms that underlie endocytic internalization.  They also illustrate that parallel mechanisms regulate the internalization of Snc1 in yeast and mammalian cells. 2.2. Introduction Clathrin-mediated endocytosis selects proteins at the plasma membrane for internalization in membrane-bound vesicles. In mammalian cells, cargo is initially concentrated at endocytic sites by adaptor proteins that promote clathrin recruitment and assembly. A variety of adaptors, such AP2, AP180/CALM, epsins, arrestins and Dab2, recognize different endocytic motifs and select distinct classes of cargo (Maldonado-Baez  29 and Wendland, 2006). The subsequent recruitment of accessory factors including WASP, dynamin, and amphiphysin stimulates actin polymerization, resulting in membrane deformation and vesicle scission (Smythe and Ayscough, 2006). Studies in yeast have demonstrated conserved endocytic modules are recruited to sites of internalization in a similar temporal sequence (Kaksonen et al., 2005; Newpher et al., 2005; Perrais and Merrifield, 2005). Clathrin and adaptors are part of the early coat module that establishes the initial site of uptake, while the late coat module (Sla1/Sla2/End3/Pan1) couples coat formation to actin polymerization through recruitment and stimulation of yeast WASP (Las17) and Myo5. This activates the Arp2/3 complex to form an actin network that, stabilized by the actin regulatory module (Cap1/2, Sac6, Abp1), promotes rapid inward movement of the internalizing vesicle. Finally, the amphiphysins Rvs161/167 are thought to drive scission of endocytic vesicles from the plasma membrane. Recycling of the endocytic machinery by vesicle uncoating requires additional proteins, including the synaptojanin homolog Inp52.  This sequence of events, defined by live cell imaging studies, suggests endocytic processes are largely conserved. However, striking differences in the functional requirement for certain regulatory proteins argue that internalization may be differentially regulated in yeast and mammalian cells. For example, the dynamic regulation of actin polymerization is essential for uptake in yeast but not in most mammalian cell types (Engqvist-Goldstein and Drubin, 2003; Smythe and Ayscough, 2006). Conversely, clathrin has an important role in higher cells yet loss of yeast clathrin causes only partial reduction in receptor internalization, and yeast homologs of major clathrin adaptor proteins such as AP2 and AP180 are not required for the uptake of known cargo (Huang et al., 1999; Wendland and Emr, 1998). A number of other yeast genes are homologous to components of the mammalian endocytic machinery, yet do not lead to observable endocytosis defects when mutated (Engqvist-Goldstein and Drubin, 2003; Kaksonen et al., 2005). Some of these factors may have functionally redundant homologs, or have cargo-specific roles. Additional, unrecognized factors may also regulate cargo uptake in yeast. To better understand the endocytic process in both yeast and mammalian cells, it will be important to identify the complete set of structural and regulatory proteins, and systematically define their specific roles.  The yeast VAMP2/synaptobrevin homolog Snc1, which regulates the fusion of exocytic vesicles at the cell surface, is a widely studied endocytic cargo protein. After  30 delivery to the plasma membrane of the growing bud, it is rapidly internalized and transported to endosomal and Golgi compartments, where it is incorporated into new secretory vesicles (Lewis et al., 2000). Here, we perform a genome-wide analysis of Snc1 localization in yeast to uncover genes with functional roles in endocytosis, and quantify their relative contribution to this process. We identify functions for known and novel proteins not previously shown to be required for uptake, and demonstrate that the yeast AP180 homologs and clathrin have a cargo-specific role in Snc1 internalization. In addition, we describe an endocytic function for the previously uncharacterized protein Ldb17.  2.3. Results 2.3.1. A Snc1-based quantitative assay for endocytic recycling  To quantify defects in endocytosis on a genome-wide scale, we developed an enzymatic assay based on the cell surface localization of a Snc1 reporter. The enzyme invertase (encoded by SUC2) was fused to the extracellular C-terminus of Snc1, and GFP was appended to its intracellular N-terminus, creating the chimeric protein GSS (GFP-Snc1-Suc2; Fig. 2.1 A). Cell surface GSS levels can be determined by a colorimetric invertase activity assay, using cell-impermeant reagents (Darsow et al., 2000). By fluorescence microscopy, GSS displayed a polarized distribution at the plasma membrane of small buds similar to Snc1 (Fig. 2.1 B; Lewis et al., 2000), which has been attributed to a cycle of localized exocytosis followed by rapid endocytosis that prevents diffusion away from the site of new growth (Valdez-Taubas and Pelham, 2003). In support of this model, when the Snc1 endocytosis signal was mutated, the polarization of GSS was lost and the level of invertase activity at the plasma membrane increased (Fig. 2.1 B and data not shown). Both Snc1 and GSS were mislocalized to the vacuole in vps51∆ mutants (data not shown), demonstrating that they follow a similar recycling pathway back to the cell surface (Conibear et al., 2003).  We introduced the GSS reporter into two independent genome-wide collections of viable deletion mutants, and measured its cell surface level for each mutant in parallel, using a large-scale plate-based invertase assay (Fig. 2.1 C). Mutants were ranked according to their median invertase activity score, determined by automated image densitometry (Fig. 2.1 D and Table A2). Mutants with increased cell-surface GSS included well-characterized endocytosis-defective strains such as rvs161∆ and vrp1∆.  Other predicted endocytosis genes were enriched in the top 400 hits (Table 2.1), including many not previously shown to cause defects in cargo uptake when deleted such as yeast homologs of AP180 (yap1801  31 and yap1802), epsin (ent1), tropomyosin (tpm1), type I myosin (myo5), synaptojanin (inp52), coronin (crn1), and syndapin (bzz1). We generated a “gold standard” list of 33 proteins that have been localized to sites of endocytosis by time-lapse live cell microscopy that were also represented in the haploid deletion collections we evaluated (Newpher et al, 2005; Maldonado-Baez et al., 2008; Toret et al., 2008; D. Drubin, personal communication). Of these, 23 were found in the top 400 hits, representing a significant degree of enrichment (p < 2.2 x 10-16, Fisher exact test). This set of ~400 top-scoring mutants was chosen for further analysis. Mutants with cell-surface GSS levels significantly lower than wildtype (e.g., snx4∆, vps51∆) were also identified in the screen. This class of mutants, which may have impaired endosomal recycling, will be described in more detail elsewhere.  2.3.2. Genetic interaction mapping clusters functionally related genes The large number of mutants with elevated surface invertase activity suggested many distinct processes influence GSS reporter distribution. To functionally dissect these processes, we analyzed GSS surface levels in 374 top-scoring deletion mutants in pairwise combination with a panel of 81 deletion mutants that affect a variety of protein trafficking pathways. Genes that co-function within individual complexes and pathways can be identified in large scale genetic interaction analyses based on two characteristic properties (Schuldiner et al., 2006). When loss of one gene disrupts a pathway or complex, loss of a second gene in the same pathway has no further effect, and the double mutant phenotype is less than would be expected under an additive model of genetic interaction. In addition, genes with related functions share similar patterns of genetic interactions and can be identified by cluster analysis.  In typical applications, such as synthetic lethal analysis, the double mutant array is analyzed using cell viability as the phenotypic readout. Here, we quantified the GSS surface distribution to analyze the ~33,000 double mutants of our 374 x 81 array. Hierarchical clustering grouped genes according to their pattern of genetic interactions (Fig. 2.2 A and Fig. A1, see Materials and Methods for details). Strikingly, many clusters were enriched for genes that act together (Fig. 2.2 B). Endocytosis genes were found in two distinct clusters, whereas other gene groupings corresponded to distinct processes (see below). We observed that mutants deleted for two different endocytic genes (eg. vrp1 and inp52) often had lower cell surface levels of GSS than would be expected under an additive model of genetic interaction, consistent with a function in the same pathway or complex.  In contrast, mutants disrupted for both endocytosis (vrp1, rvs167) and recycling (snx4, cvt20/snx42)  32 genes had cell surface GSS levels greater than expected under the additive null model. This is consistent with previous observations that endocytic defects are epistatic to defects in the Snx4-dependent recycling of Snc1 (Lewis et al., 2000). 2.3.3. Integration of genetic and physical interaction data identifies complexes required for Snc1 transport To comprehensively identify pathways that regulate Snc1 distribution, we integrated our genetic interaction results with genome-wide physical interaction datasets (see Materials and Methods for details). In a network analysis, genes are represented as “nodes” (circles) linked by “edges” (lines) that indicate an experimental observation such as a physical interaction. To generate a network from the genetic interaction data, pairwise correlation scores were calculated for all genes in the array, and genes were linked by an edge if their correlation score was greater than a threshold value. The resulting network connects genes that share similar patterns of genetic interaction, and thus may represent components of pathways and complexes. Physical interaction networks were then created for the same set of genes, where edges represent interactions observed in high throughput yeast two-hybrid or mass spectrometry experiments. Highly connected sets of genes in each network were identified and integrated, and significant gene clusters were assigned to subcellular compartments based on the localization of their constituent proteins (Huh et al., 2003).  The resulting map (Fig. 2.3) provides a visual representation of the processes contributing to GSS localization and an indication of their relative importance. The size of each node is proportional to the phenotype of the corresponding deletion mutant, whereas edges represent either a physical interaction or a genetic correlation extracted from genome-wide data.  Four major clusters, containing a total of 20 genes, mapped to the plasma membrane. The largest of these groupings was enriched for genes with known or predicted roles in endocytosis (SLA1, ABP1, INP52, EDE1, YAP1802, RVS161, RVS167, CRN1, and the INP52-overlapping ORF YNL105W). Additional genes implicated in endocytosis or actin regulation were found in three other clusters at the plasma membrane. These findings highlight the importance of known endocytic regulators in Snc1 trafficking, and predict an endocytic role for uncharacterized genes in these clusters, such as LDB17 (see below). A number of well-characterized protein complexes that function at intracellular organelles or regulate transcription or translation were also identified by our integrative network analysis (Fig. 2.3). Some have established roles in actin assembly or protein  33 transport, such as the cytosolic Prefoldin/GimC complex, which acts as a co-chaperone in actin folding (Siegers et al., 1999). ESCRT mutants are known to exhibit increased cell surface levels of receptors, which has been attributed to enhanced recycling from endosomal compartments (Davis et al., 1993). Chromatin remodeling complexes have also been implicated in regulating vesicle transport at endosomes (Schluter et al., 2008), although the mechanism remains unclear. Mutant strains lacking components of the Sin3/Rpd3 histone deacetylation complex, including Dep1 and Ume6, had particularly strong phenotypes. These proteins regulate the expression of phospholipid biosynthesis genes such as OPI3, INO1, and CHO2 (Elkhaimi et al., 2000; Lamping et al., 1994), which were among the top hits in our screen (Table S1). The regulation of plasma membrane lipid composition may also explain the identification of RIM pathway components, which mediate the cellular response to lipid asymmetry and other stimuli (Ikeda et al., 2008).  2.3.4. Clathrin and clathrin assembly proteins are required for Snc1 endocytosis Our network analysis suggested 20 genes, in four major clusters, are involved in Snc1 uptake at the plasma membrane. To confirm the results of the large-scale plate-based assay, cell-surface GSS levels in these 20 mutants were quantified by a liquid-based invertase activity assay (Fig. 2.4 A). Most had elevated GSS levels that correlated well with values derived from the large-scale densitometry data. The significant internalization defect of yap1802 mutants was surprising, as previous studies have not identified a clear role for AP180 homologs in yeast (Huang et al., 1999; Wendland et al., 1999). Yap1802 shares 43% sequence identity with Yap1801, which was also recovered by the genome-wide screen (Table A2). By microscopy, the polarized distribution of Snc1 at the bud was largely maintained in yap1801 or yap1802 single mutants, but Snc1 was evenly distributed at the cell surface of yap1801 yap1802 double mutants (Fig. 2.4 B). This strong defect in internalization is consistent with a functionally redundant role for the yeast AP180 proteins in Snc1 uptake.   In mammalian cells, the ubiquitous AP180 homolog CALM participates in clathrin- mediated endocytosis, and interacts with the AP-2 adaptor complex (Meyerholz et al., 2005). Deletion of clathrin heavy or light chain (CHC1 or CLC1), but not AP-2 (APL1), also caused a strong Snc1 localization defect (Fig. 2.4 B and data not shown). Surprisingly, no defect was seen when the major clathrin-binding site in Yap1802 (Wendland and Emr, 1998) was deleted in a strain lacking Yap1801 (Fig. 2.5 A), suggesting that Yap1802  34 contains additional clathrin binding sites, or that additional proteins can bridge the interaction.   In contrast to Snc1 endocytosis, loss of Yap1801 and Yap1802 singly or in combination does not alter ligand-induced down-regulation of the a-factor/Ste2 complex (Huang et al., 1999). We found loss of Yap1801/2 had little effect on the internalization of a distinct endocytic cargo, Ste6-GFP (Fig. 2.5 B). Defects may be more apparent for Snc1, which depends on continuous rounds of internalization and recycling to maintain its polarized distribution, compared to Ste6, which is delivered to the vacuole following internalization (Kelm et al., 2004). To determine if Yap1801/2 are generally required for the uptake of proteins subject to endocytic recycling, we appended the well-characterized Sla1-dependent NPFxD endocytosis signal to the t-SNARE GFP-Sso1 to create a different recycling reporter, NPF-Sso1 (Valdez-Taubas and Pelham, 2003). Like Snc1, NPF-Sso1 has a polarized distribution that depends on endocytosis. Consistent with previous results, we found the localization of NPF-Sso1 to be similar to that of Snc1 in wild type cells, but completely depolarized in sla1 mutants (Fig. 2.4 B). Its polarized distribution was maintained in yap1801 yap1802 double mutants, suggesting Yap1801/2 are specifically required for Snc1 internalization. We created a chimeric version of the NPF-Sso1 reporter by fusing invertase to the NPF-GFP-Sso1 C-terminus and adding two additional NPFxD motifs to further enhance internalization (Fig. 2.4 C), and measured cell surface levels of the resulting NGSS (3xNPF- GFP-Sso1-Suc2) and GSS reporters (Fig. 2.4 D). Internalization of GSS was blocked by mutation of the Snc1 endocytic signal, whereas NPF-dependent internalization of NGSS was abolished in a sla1 mutant, as expected. Combined deletion of YAP1801 and YAP1802 dramatically increased levels of GSS at the cell surface, whereas NGSS surface levels were unaffected. Taken together, these results indicate Yap1801 and Yap1802 act as cargo- specific adaptors for the clathrin-mediated endocytosis of Snc1.  2.3.5. Systematic analysis of cargo specificity  To determine if other genes identified in our genome-wide screen have cargo- specific functions, we re-introduced the GSS and NGSS reporters in parallel into our array of top-scoring deletion mutants. Invertase activity values for each mutant, normalized to the array median, were determined from 6 independent mutant arrays per reporter and converted into relative sorting scores.  The ranked differences between NGSS and GSS sorting scores for each mutant indicated that deletion of YAP1802 and INP52 had the  35 greatest specific effect on GSS (Fig. 2.6 A). By measuring cell surface reporter levels in liquid culture (Fig. 2.6 B), we confirmed inp52 mutants (rank=2) exhibited a highly significant degree of cargo specificity whereas a lower-ranking mutant (ldb17) that fell below the 2SD cutoff did not.  A cargo-specific role for the synaptojanin homolog Inp52, a PI(4,5)P2 phosphatase required for recycling of coat proteins after vesicle budding is complete (Toret et al., 2008), was unexpected. Because the membrane association of Yap1801/2 is mediated by PI(4,5)P2-binding ANTH domains, we considered the possibility that elevated PI(4,5)P2 levels in inp52 mutants lead to retention of Yap1801/2 on budded vesicles. Consistent with this hypothesis, Yap1801/2-GFP were observed on cytosolic patches inp52 mutants, but not in wild type cells (Fig. 2.6 C). Likewise, loss of Inp52 resulted in cytoplasmic aggregates of the ANTH domain protein Sla2-GFP, but had no effect on Sla1-GFP localization, as previously reported (Fig. 2.6 C, (Toret et al., 2008)). Prolonged association of Yap1801/2 with budded vesicles would be expected to reduce levels available for GSS internalization, which may explain the apparent cargo specificity of the inp52 deletion.  2.3.6. Ldb17 is a new regulator of yeast endocytosis that is transiently recruited to cortical patches  Mutation of the uncharacterized gene LDB17 (Low Dye Binding 17; Corbacho et al., 2005) caused a strong GSS localization defect (Fig 2.3 and Fig 2.4 A) that, in contrast to yap1801 yap1802 and inp52 mutants, was not strongly cargo-specific (Fig. 2.6 B). We confirmed both Snc1 and NPF-Sso1 lost their polarized distributions in ldb17 mutants (Fig. 2.6 D), and a weak internalization defect was also observed for Ste6-GFP (Fig. 2.5 B), suggesting Ldb17 is a general component of the endocytic machinery. Although an endocytic role for Ldb17 has not previously been described, it has a PTHR13357 domain also found in the mammalian protein SPIN90 (Fig. 2.6 E), which has been implicated in clathrin-mediated endocytosis in fibroblasts (Kim et al., 2007; Kim et al., 2006). Most organisms, including yeast and human, contain a single PTHR13357 family member, indicating Ldb17 and SPIN90 may have orthologous functions.  To help define the role of Ldb17 in endocytosis, we analyzed its recruitment to sites of internalization using two-color time-lapse fluorescence microscopy. Although difficult to visualize due to its low abundance (Ghaemmaghami et al., 2003), GFP-tagged Ldb17 was observed in faint puncta at the cell surface where it showed partial overlap with mRFP- tagged forms of the late coat component Sla1, the Type I myosin Myo5 and the F-actin- 36 binding protein Abp1 (Fig. 2.7 A-C), consistent with transient co-localization. Kymograph analysis showed Ldb17 joined pre-existing Sla1 patches just prior to the onset of Sla1 inward movement and Myo5 recruitment (Fig. A2 A-C). Myo5 patches appeared ~1-3 s after Ldb17 patches, whereas Ldb17 dissociated from the membrane ~4-6 s prior to Abp1 disassembly. These results allow us to place Ldb17 on the temporal map of the endocytic process (Fig. 2.7 D): Ldb17 is maximally recruited after assembly of the late coat components, immediately prior to the recruitment of the Myosin module, which precedes the actin-driven inward movement of the invaginating membrane.   The coat module assembles at endocytic sites prior to the onset of actin polymerization, and its components are recruited before the appearance of F-actin. Treatment with the actin monomer-sequestering drug Latrunculin A (LatA) resulted in the expected complete delocalization of Abp1, whereas the membrane localization of Ldb17 was dramatically enhanced (Fig. 2.7 E). The endocytic coat components Sla1 and Sla2 show similar LatA-resistant cortical localization (Ayscough et al., 1997).  This indicates actin is not required for the membrane recruitment of Ldb17, and is consistent with a role for Ldb17 at late stages of coat assembly. 2.3.7. Sla1 contributes to membrane recruitment of Ldb17  The F-actin-independent localization of Ldb17 suggests other factors regulate its recruitment to sites of endocytosis. We found the C-terminal Proline-Rich Domain (PRD) of Ldb17 was important for its localization at the cell periphery (Figs. A2 D, left panels, and 2.6 F). Many endocytic proteins contain SH3 domains that recognize specific PRD sequences and contribute to the assembly of the endocytic network. We confirmed by co- immunoprecipitation that the yeast syndapin homolog Bzz1 binds Ldb17 in a PRD- dependent manner (Fig. A2 E), as predicted in a large-scale study (Tong et al., 2002). Surprisingly, membrane localization of Ldb17-GFP was enhanced in bzz1 mutants (Figs. A2 D and 6 F) and simultaneous loss of Bzz1 and the Ldb17 PRD had additive effects on cell surface GSS levels (Fig. A2 F), indicating Bzz1-PRD interactions are not involved in Ldb17 recruitment.   To identify additional PRD binding partners, we used yeast two-hybrid analysis to screen a panel of 16 SH3 domains from proteins implicated in endocytosis or actin regulation (Tong et al., 2002). SH3 domains from Sla1, Lsb3, and Lsb4 all exhibited PRD- dependent interactions with Ldb17 (Fig. A2 G and H). Because Lsb3 and Lsb4 are known binding partners of Sla1 (Dewar et al., 2002; Gavin et al., 2006), their interactions with  37 Ldb17 may be indirect. Interestingly, loss of Sla1 had an effect similar to loss of the PRD; by live-cell microscopy, the lifetime of Ldb17 at the cell surface was reduced from 9 sec to 5 sec (Fig. 2.7 F). Taken together, these results suggest Sla1 binds the Ldb17 PRD to enhance its membrane association at endocytic sites, whereas Bzz1 is important for its release. 2.3.8. Aberrant actin distribution in LDB17 mutants  Based on the timing of its recruitment, we hypothesized Ldb17 may link coat formation to actin polymerization, as has been suggested for other components of the late coat module. Consistent with this, the actin module protein Abp1 was found in a smaller number of larger, brighter clusters in ldb17 cells compared to wildtype cells (Fig. 2.7 G), similar to the large actin clumps found in sla1 mutants (Kaksonen et al., 2005). Actin polymerization is required for internalization of the Sla1-containing late coat module; in cells treated with LatA or lacking the Arp2/3 activator Las17, Sla1 patches remain immobile at the cell surface (Ayscough et al., 1997; Sun et al., 2006). Sla1 was similarly stabilized at the membrane in the absence of Ldb17 (Fig. 2.7 H), suggesting Ldb17 plays a role in the dynamic regulation of actin polymerization required for the internalization of Sla1- containing endocytic vesicles.  2.4. Discussion We have developed a genome-wide screening method that provides a systematic and quantitative analysis of genes required for the endocytic recycling of Snc1, the yeast VAMP2 homolog. In addition to well-established endocytic regulators, this screen uncovered phenotypes for deletion mutants of predicted endocytosis genes for which no cargo uptake defects had previously been observed. The mammalian homologs of many of these genes also have endocytic roles, underscoring the conserved nature of endocytic processes in eukaryotic cells (Engqvist-Goldstein and Drubin, 2003; Kaksonen et al., 2005; Smythe and Ayscough, 2006).   Collectively, our results highlight the sensitive nature of our reporter assay and reinforce the importance of dynamic actin regulation for the endocytic process. Multiple regulators of the actin cytoskeleton were identified in our screen, including the actin binding proteins Abp1 and Crn1 (coronin homolog), the Actin Capping complex (Cap1/2), and the Cap1/2 binding protein twinfilin (Twf1). Lack of sufficiently sensitive assays and study of limited cargo may have prevented detection of endocytic phenotypes for these mutants in previous studies (Kubler and Riezman, 1993). In addition, redundancy of the  38 endocytic machinery may account for the weak but significant phenotypes resulting from loss of individual myosin-I (Myo5) and epsin (Ent1) isoforms (Lechler et al., 2000; Maldonado-Baez and Wendland, 2006; Wendland et al., 1999).  2.4.1. Role for clathrin adaptors in yeast endocytosis The severe defect in Snc1 uptake caused by loss of Yap1801 and Yap1802, homologs of the mammalian clathrin assembly factor AP180/CALM, represents the first demonstration of a unique role for these proteins in yeast endocytosis. Studies in mammalian cells, worms, and flies all support a requirement for AP180 and its homologs in the internalization of VAMP/Synaptobrevin. It mediates the selective uptake of this SNARE in worms, and appears to regulate the internalization of additional proteins in flies (Bao et al., 2005; Nonet et al., 1999).  AP180-like proteins may cooperate with other adaptors for the uptake of certain cargo. For example, a redundant role with the epsins in the internalization of the yeast pheromone receptor Ste3 was recently reported (Maldonado-Baez et al., 2008). AP180/CALM contains multiple binding sites for AP2, Eps15, and clathrin (Maldonado-Baez and Wendland, 2006; Wendland and Emr, 1998). A quantitative analysis of synaptobrevin localization in selected C. elegans mutants using the pH-sensitive synaptobrevin-GFP fusion protein synaptopHluorin demonstrated its surface levels were enhanced in both AP180 and AP2 mutants (Dittman and Kaplan, 2006), suggesting the interaction between AP180 and AP2 is functionally important in worms. In contrast, our results show Yap1801/2 does not require AP2 to mediate Snc1 internalization in yeast, consistent with a recent study that saw little effect of mutating the AP2 binding site of CALM on synaptobrevin uptake in mammalian cells (Harel et al., 2008). The specific requirement for Yap1801/2 in Snc1 endocytosis suggests they may act as adaptors to recruit Snc1 into a clathrin-coated pit. Internalization signals recognized by AP180-like monomeric adaptors have yet to be described (Maldonado-Baez and Wendland, 2006) and, like most SNAREs, Snc1 lacks canonical adaptor sorting motifs such as YxxF or D/ExxxL/E. Instead, SNARE proteins appear to use specialized sorting signals that differ from those of other cellular cargo (Chidambaram et al., 2004; Miller et al., 2007). The V40A M43A mutations that reduce Snc1 endocytosis could impair a Yap1801/2 recognition site; however, this remains to be determined, as we have not been able to demonstrate a direct physical interaction between Yap1801/2 and Snc1.   39 2.4.2. Identification of novel components of the yeast endocytic machinery Our systematic analysis of cargo specificity did not identify additional adaptor proteins that were clearly specific for Snc1. Instead, we discovered loss of the syntaptojanin homolog Inp52 affected uptake of the Snc1 reporter more strongly than a reporter that uses a Sla1-dependent NPFxD signal. This can be explained by the differential recognition of PI(4,5)P2 by Yap1801/2 and Sla1. High levels of PI(4,5)P2 resulting from loss of Inp52 prevented efficient recycling of Yap1801/2, which is predicted to reduce its availability for further rounds of internalization. However, no such effect was seen for Sla1, consistent with previous reports (Toret et al., 2008).   In contrast to the cargo-specific role of Yap1801/2, we found the previously uncharacterized gene LDB17 plays a broad role in regulating endocytosis. Ldb17 is transiently recruited to Sla1-containing cortical patches shortly before the onset of actin polymerization, and its membrane association is stabilized by interactions between its PRD and the Sla1 SH3 domain. The aberrant actin assembly and increased lifetime of Sla1 patches in ldb17 mutants suggest Ldb17 helps trigger the dynamic actin rearrangements that precede coat disassembly. Ldb17 may link coat assembly to the activation of the Arp2/3 complex through interactions with Sla1 and Arp2/3 activators, or act more directly. The C-terminal region of SPIN90 most similar to Ldb17 is sufficient to promote the WASP-independent activation of Arp2/3-mediated actin polymerization in vitro (Kim et al., 2007). The Arp2/3 and actin binding motifs present in SPIN90 are only partially conserved in Ldb17, and we did not observe binding of Ldb17 to the Arp2/3 complex and the yeast WASP homolog Las17 in vivo (unpublished results). However, we identified an interaction between the Ldb17 PRD and the Bzz1 SH3 domain that mirrors the PRD-dependent binding of the Ldb17-related protein SPIN90 to the mammalian Bzz1 homolog syndapin (Kim et al., 2006). The conserved interaction of syndapin-like proteins with proline-rich regions in Ldb17 and SPIN90, despite the different placement of the interacting domains, suggests these proteins may fulfill related roles. Further work will be needed to clarify the function of these conserved proteins in regulating actin polymerization and endocytosis.   Overall, our results suggest that endocytic processes are generally more similar in yeast and higher cells than previously believed, and underscores Snc1 transport in yeast as a model for synaptobrevin recycling at the synapse. Characterization of other genes identified in our screen may yield additional endocytosis factors. Due to the functional  40 redundancy of the endocytic machinery in all eukaryotes, many regulatory proteins are likely to have weak mutant phenotypes that can only be discovered by more sensitive and quantitative approaches. Future application of our genome-wide analysis to different reporter proteins may identify alternative cargo-specific machinery and further define the complexity of endocytic systems. 2.5. Materials and methods   Construction of plasmids and yeast strains Plasmids and yeast strains used in this study, and details of their construction, are listed in Table S2. Unless otherwise indicated, plasmids were constructed by homologous recombination after co-transforming yeast with linearized vector and DNA fragments bearing 50-55bp homology, and recovering recombinant plasmids in Escherichia coli. Oligonucleotide sequences are available upon request. The MATa yeast strain BY4741 and its gene deletion derivatives were obtained through Open Biosystems (Huntsville, AL). Unless otherwise stated, gene disruptions and tagging of genomic ORFs were carried out by transformation of a PCR product containing a drug selection marker, flanked by 50-55bp of homology to the region of interest.  Genome wide screening The GFP-Snc1-Suc2 (GSS) reporter was introduced into MATa and MATalpha knockout collections using the SGA procedure (Tong and Boone, 2006). Query strains containing the GSS reporter and a gene deletion marked with NATR were mated to a 384- colony knockout array that contained 374 mutants identified in the genome-wide analysis (top 402 hits minus 28 mitochondrial mutants) and controls (wild type, blank, ent3, and rvs161). Double mutant haploid strains containing the GSS reporter were selected on –LEU – URA +G418 +clonNAT plates.  Manipulation and screening of the resulting colony arrays was performed essentially as described (Burston et al., 2008). Colony arrays on 384-array stock plates were pinned four times to YPF plates creating 1536-arrays using a Virtek automated colony arrayer (BioRad, Hercules, CA). Digital images of colony arrays subjected to the invertase overlay assay (Darsow et al., 2000) were acquired using an Epson 2400 flat-bed scanner. Local normalization was carried out using National Institute of Health ImageJ software (http://rsb.info.nih.gov/ij/) with the local normalization plugin  41 (bigwww.epfl.ch/sage/soft/localnormalization) to correct for differences in intensity resulting from uneven distribution of reagents. Densitometry on corrected images used the spot-finding program GridGrinder (gridgrinder.sourceforge.net) and values were subjected to background subtraction and filtered to eliminate absent or very slow-growing strains. As densitometry values are inverted during analysis, reported values are inversely correlated with cell surface levels of the reporter. Therefore, these values were subtracted from the median value for all strains to give a score where a high value represents a high level of the reporter. The invertase overlay assay was carried out twice on each knockout collection; average values were used to generate the final ranking.  Genetic Interaction and Network Analysis In an additive model of genetic interaction, the phenotype of the double mutant strain (PXY) can be expressed as: PXY =  PWT + EX + EY + EGI, where PWT is the wild type phenotype, EX is the effect of the first mutation, EY is the effect of the second mutation and EGI is the genetic interaction effect. In a genetic interaction matrix, all double mutants in a given row or column have a mutation in the same “array” gene (row) or “query” gene (column).  Assuming genetic interactions are rare, and positive and negative interactions are equally common, dividing double mutant phenotype values (PXY) in each column by the mean of that column removes the effect of the query mutation   (Pwt + EY). Subsequently dividing values in each row by the row-wise mean removes the effect of the array mutation (EX), leaving only the genetic interaction effect, EGI.   We applied a modified version of this data pre-processing strategy to the matrix of raw double mutant invertase activity values. Rows with more than 20% missing observations were removed. Remaining values were divided by row- and column-wise medians, and values in each row and column were scaled so the sum of the squares of the values in each row or column was 1.0. Although these manipulations do not preserve the numerical value of EGI they optimize clustering of functionally related groups by emphasizing patterns of genetic interactions. Cluster 3.0 software (http://bonsai.ims.u- tokyo.ac.jp/~mdehoon/software/cluster/software.htm) was used to perform average linkage hierarchical clustering using an uncentered correlation similarity metric on both horizontal and vertical axes, and results were presented using Java Treeview (http://jtreeview.sourceforge.net/), where ordering of genes on both axes reflects the similarity of their genetic interaction profiles, and cluster relationships are indicated by  42 trees. The resulting heat map (Fig. A1) does not provide a true quantitative measure of genetic interaction, but instead approximates the direction of the genetic interaction effect for each double mutant where yellow is negative (less than expected under the additive null model), and blue positive (greater than expected).  A network of correlated genetic interaction profiles was generated using the ARACNE algorithm (Margolin et al., 2006) with a threshold of 0.015. The MCODE plugin for Cytoscape (Bader and Hogue, 2003; Shannon et al., 2003) was used to identify densely- connected gene clusters in synthetic genetic data and physical interaction networks from SGD (www.yeastgenome.org) and WI-PHI (Kiemer et al., 2007), which were then integrated. The size of each node (gene) was mapped to the strength of the endocytic defect in Cytoscape based on the results from the genome-wide analysis in Table A2.  Liquid invertase assay The liquid invertase assay was modified from (Darsow et al., 2000). Strains expressing GSS or NGSS reporters were grown for 20 h in 2ml YP fructose (OD600 ≈10). After dilution to 3 OD600/mL, 5μl of each culture was mixed with 55μl 0.1M NaOAc buffer pH4.9 in a 96 well microtiter plate. Subsequent steps were carried out with a VICTOR3 1420 multilabel plate reader system (PerkinElmer, Waltham, Massachusetts). 13μl of freshly prepared 0.5M ultra pure sucrose was added to each well, and the plate was incubated for 5min at 30°C. Next, 100μl of glucostat reagent (0.1M K2HPO4 pH7.0, 347.1 U Glucose Oxidase, 2.6 ng/ml Horseradish Peroxidase, 102.6 nM N-ethyl-maleimide, 0.15 mg/ml O- Dianisidine) was added to each well, and the plate incubated for 5 min at 30°C. Finally, 100μl of 6N HCl was added to each well to stop the reaction. The absorbance at 540nm was used to determine glucose concentration by comparison to a glucose standard curve (range from 5-50nM glucose). Results are reported as nM glucose produced per 1 OD600 of culture.   Live cell imaging Yeast cells expressing GFP-tagged proteins were grown to mid-log phase and were viewed directly in minimal selective media at room temperature using a Plan-Apochromat 100x 1.40 NA oil-immersion objective on a Zeiss Axioplan 2 fluorescence microscope (Carl Zeiss, Thornwood, NY). Images were captured with a CoolSNAP camera (Roper Scientific, Tuscan, AZ) using MetaMorph 6.1 software (Molecular Devices, Downingtown, PA) and adjusted using Adobe Photoshop CS. Alternatively, cells were grown to early log phase on  43 rich medium plates at 30°C and placed in 200 ml minimal media on Concavalin A-coated 8 well Lab-Tek coverglass bottom dishes (Nalge Nunc, Rochester, NY).  Images were collected at room temperature with a 3i Marianas microscope (Intelligent Imaging Innovations, Denver, CO) equipped with an alpha Plan-Fluar 100x 1.46 NA objective and a Zeiss TIRF slider. Single color widefield GFP images were acquired using 488 nm laser excitation and a GFP dichroic and emission filter (Semrock, Rochester, NY). Two-color and RFP images were acquired with 488nm and/or 561nm laser excitation, with GFP and RFP emission split between two Cascade II 512 cameras with an Optical Insights Dual Cam (Photometrics, Germany) equipped with the D520/30m D630/50m splitting optics (Mag Biosciences).   Exposure times varied from 600-750ms as follows: Ldb17-GFP single experiments, 750ms; two-color Ldb17/Myo5, 750ms; Ldb17/Sla1, 750ms; Lbd17/Abp1, 750ms for Ldb17 and 650 for Abp1. TetraSpeck 100nm beads (Invitrogen) were used to align the two channels and for subsequent registration in software. Slide-Book 4.2® software (Intelligent Imaging Innovations, Denver, CO) was used for image acquisition and dual channel image registration. Kymographs and montages were created using ImageJ software with Kymograph plugins (http://www.embl.de/eamnet/html/kymograph.html). Live-cell imaging experiments with LAT-A treatment were performed by incubating cells from early-log phase cultures in a final concentration of 200 mM LAT-A dissolved in DMSO for 30 min at 30°C.   Co-immunoprecipitation 30 OD600 cell pellets made from flash-frozen log phase cells were lysed by vortexing with glass beads in 200ul lysis buffer (100mM NaCl pH 8.0, 2mM EDTA, 0.5% Tween-20 + PMSF) and incubated with mouse αHA (1:1000 ABM) and 30ul Protein G-Sepharose (75% slurry in PBS). Co-precipitating proteins were identified by western blotting with mouse αGFP (1:1000, Roche) and HRP-labelled secondary antibodies (BioRad). Blots were developed with ECL (Pierce, Rockford, IL) and and luminescent images were captured with a Fluor S Max Multi-imager.     44 2.6. Figures and Tables   Figure 2.1. Genome-wide screen for endocytic recycling mutants.  (A) Schematic of the GFP-Snc1-Suc2 (GSS) reporter. At the plasma membrane (PM), the Suc2 (invertase) portion is accessible to the extracellular space. (B) Localization of GFP- Snc1, GSS, and an endocytosis-defective form of GSS containing snc1V40A,M43A mutations (Scale bar, 2μm). (C) Representative portion of the yeast knockout array tested using the invertase activity overlay assay. Mutants defective in Snc1 endocytosis exhibit increased surface invertase activity relative to wildtype cells, and appear dark. Mutants with high (tpm1 and rvs161) or low (snx4 and irs4) levels of cell surface invertase activity are indicated. (D) Relative cell surface invertase activities of top 1000 mutants. Red line indicates threshold used to designate top hits.   45 Table 2.1. Predicted yeast endocytic genes identified in the screen       ND, not determined aSee Table A1. bKaksonen et al., 2005 cInternalization of FM4-64 or cargo proteins.  See Engqvist-Goldstein and Drubin (2003), Kaksonen et al. (2005), and Moseley and Goode (2006).  46 Figure 2.2. Endocytosis mutants have related genetic interaction profiles.  (A) Hierarchical clustering was used to analyze the invertase activity values of double mutant strains generated by crossing top-scoring mutants from the primary screen (y-axis) to 81 diverse trafficking mutants (x-axis). Yellow indicates lower than expected levels of GSS at the cell surface, while blue indicates higher than expected levels (see Methods and Materials for details). (B) Detailed view of clusters showing names of genes and highly represented pathways/complexes. Clusters are numbered to indicate their relative position on the heatmap in (A). Red bar indicates gene clusters on the Y-axis enriched in endocytosis or recyling genes. See Fig. A1 for a detailed view of gene names and cluster relationships.   47    Figure 2.3. Integration of genome-wide genetic and physical interaction data identifies pathways and complexes.  Significant genes clusters contributing to GSS localization were mapped based on integrated physical and genetic interaction networks. Array genes are represented as nodes (where relative size is proportional to GSS surface levels in the corresponding deletion mutant), and are connected by edges that represent either a physical interaction or a genetic correlation extracted from genome-wide data.  Clusters were assigned to subcellular compartments based on the localization of their constituent proteins.  48  Figure 2.4. Yeast AP180 homologs have a conserved role in Snc1 internalization.  (A) Quantification of cell surface GSS levels in WT and candidate endocytic mutants by the liquid invertase assay.  Invertase activity represents relative surface levels of the GSS reporter, quantified as nmol glucose released/OD600  (mean of at least 3 experiments ± SD). (B) Localization of GFP-tagged Snc1 and NPF-Sso1 in WT and mutant strains (Scale bar, 2μm). (C) Schematic of the GFP-Snc1-Suc2 (GSS) and 3xNPF-GFP-Sso1-Suc2 (NGSS) reporters. (D) Relative cell surface levels of GSS and NGSS reporters measured by liquid invertase assay in mutant strains (mean of 3 experiments +/- SD). Results for each reporter are expressed as % invertase activity relative to WT. Different endocytosis defective controls (*EN-) were used for each reporter. GSS: endocytosis defective GSS (snc1V40A M43A) reporter in WT cells. NGSS: NGSS in sla1 mutant strain.   49         Figure 2.5. Cargo sorting defects of yap1801∆ yap1802∆ mutants.  (A) The Yap1802 C-terminal clathrin-binding motif (CBM) is not required for Snc1 internalization. Localization of GFP-tagged Snc1 and NPF-Sso1 in WT and yap1801/ yap1802∆CBM mutants. (B) Deletion of YAP1801 and YAP1802 does not prevent internalization of Ste6-GFP, whereas loss of LDB17 results in a slight increase in cell surface Ste6-GFP. Localization of Ste6-GFP is shown in wild type (WT) and indicated mutants.             50      Figure 2.6. Cargo specificity of genes required for Snc1 endocytosis.  (A) Array-based analysis of cargo specificity. The difference (DIFF) in cell surface levels of GSS and NGSS reporters was determined for each mutant by subtracting normalized invertase activity scores measured in parallel analyses of mutant arrays. Mutants with differences greater than 2SD (p<0.05) from the mean are shown. * indicates loss of gene function by deletion of an overlapping open reading frame (B) Relative cell surface levels of GSS and NGSS reporters measured by liquid assay in inp52 and ldb17 mutants. Results for each reporter are expressed as % invertase activity relative to appropriate WT control (*p < 0.05).  (C) Yap180 and Sla2 are present on internal puncta in inp52 strains. Wild type and inp52 mutants expressing Sla1-GFP, Sla2-GFP or both Yap1801-GFP and Yap1802-GFP were examined by live cell microscopy. Arrows indicate internal patches. (D) Localization of GFP-tagged Snc1 and NPF-Sso1 in WT, ldb17, and end3 strains. Scale bar, 2μm.  (E) Ldb17 shares homology with the mammalian SPIN90 and contains a PRD. The conserved PTHR13357 domain is indicated (blue region).   51     Figure 2.7. Ldb17 is required for proper coat and actin dynamics  (A-C) Colocalization of Ldb17-GFP with Sla1-RFP, Myo5-RFP, and Abp1-RFP. Representative single frames from GFP and RFP channels are shown together with merged images. Arrows indicate cortical patches containing both Ldb17 and RFP-tagged proteins. (D) Schematic diagram, adapted from (Kaksonen et al., 2005), illustrating the timing of Ldb17 recruitment to cortical patches relative to markers of the late coat (Sla1), WASP/myo  52 (Myo5) and actin (Abp1) modules, based on kymograph analysis of 10 patches for each GFP/RFP pair (see Fig. S3 A-C). The average difference in the timing of Ldb17 arrival or disappearance (+/- SD, in seconds) relative to other markers is indicated, together with the total average lifetime of Ldb17, Myo5, and Abp1 patches. (E) Localization of Ldb17-GFP and Abp1-RFP in cells treated with DMSO (left panels), or 200 μM LAT-A (right panels), for 30 min at 30°C. (F) Lifetime of GFP-tagged Ldb17 and/or Ldb17∆PRD at cortical patches in WT, bzz1 and sla1. Lifetimes were measured for at least 10 patches/strain. (G) Reduced number and increased brightness of actin patches in ldb17 cells, as assessed by microscopy of Abp1-GFP. (H) Kymograph representation of time-lapse wide-field fluorescence microscopy showing extended lifetime of Sla1-RFP at endocytic patches in ldb17∆ mutants, as compared to wild type cells over 120s. Scale bar, 2μm.                                         53          CHAPTER 3: THE YEAST VARIANT AP-1R CLATHRIN ADAPTOR AND IMA1 ARE REQUIRED FOR SNC1 ENDOCYTIC RECYCLING1                               1Burston HE, Tam C, Davey M, Raghuram N, Maldonado-Báez L, Wendland B, and Conibear E. (2010). Chapter 2 is a version of a manuscript in preparation.     54 3.1. Synopsis  In this chapter, the results of the primary genome-wide screen described in Chapter 2 were extended to identify factors required for Snc1 intracellular recycling.  This identified a requirement for a previously uncharacterized variant of the AP-1 complex in this process, which we have named AP-1R (AP-1 related).  AP-1R differs from the well-characterized AP- 1 complex only by the alternate inclusion of the medium subunit. The work presented in this chapter demonstrates that AP-1R and AP-1 have distinct functions in endosomal recycling, and the mechanisms regulating the specificity of AP-1R in Snc1 transport are investigated. Inclusion of alternate medium subunits has been shown to alter the sorting function of AP complexes (Gonzalez and Rodriguez-Boulan, 2009; Gan et al., 2002). However, it is not well understood how subunit exchange can confer novel functions to these complexes.  Recent findings suggest that differential interactions between the medium subunit with cargo, regulatory proteins, and membrane lipids may underlie these differences (Fields et al., 2007 and 2010; Ang et al., 2003). Consistent with findings from these previous studies, this work demonstrates that AP-1 and AP-1R participate in different regulatory interactions. The previously uncharacterized gene YFL034w was identified as an AP-1R- specific regulator, and has putative enzymatic activity required for AP-1R function. Yfl034w has been predicted to physically interact with AP-1R components in genome-wide studies (Krogan et al., 2006; Gavin et al., 2006), and here, it is shown to interact preferentially with AP-1R versus AP-1.  Yfl034w is therefore referred to as Ima1 in this work (Interacts with  adaptin 1). Collectively, this study provides insight into the differential interactions that occur between alternate AP medium chains and regulatory proteins.  It also reinforces the idea that SNARE transport is mediated by specialized components of the vesicle formation machinery. 3.2. Introduction The process of endocytic recycling is essential for maintaining the composition of the plasma membrane, and also in the regulation of nutrient uptake, cell polarity, and signal transduction (Jovic et al., 2010; Grant and Donaldson, 2009). The AP-1 adaptor complex plays a key role in endocytic recycling, and mediates sorting between the trans-Golgi network and endosomes (Reusch et al., 2002).  AP-1 is a member of the heterotetrameric clathrin adaptor complexes, and consists of four adaptin subunits: γ1 and β1, which interact  55 with accessory proteins, and μ1 and σ1.  The μ1 adaptin mediates cargo and membrane binding, while σ is involved both in complex stability, and cargo recognition (Mattera et al., 2011). AP-1 exists as variant isoforms, which differ through the alternate inclusion of one subunit.  In many cases, these variants mediate distinct sorting functions.  Mammalian cells express 3 isoforms of the small σ1 subunit (σ1A-C).  Although deletion of the large subunits are embryonic lethal, specific deletion of σ1B in mice results in defects in the recycling of synaptic vesicles (Glyvuk et al., 2010).  These mice exhibit a severe reduction in the number of synaptic vesicles at hippocampal boutons, and the endosomal accumulation of vesicle components. Most organisms also express AP-1 variants that differ by inclusion of alternate medium subunits. Mammalian polarized epithelial cells express the ubiquitous AP-1A (containing 1A), as well as the epithelial-specific AP-1B (containing 1B).  While AP-1A mediates Golgi/endosomal sorting, AP-1B functions at recycling endosomes, and directs the transport of a distinct set of cargo to the basolateral domain (Gan et al., 2002). Although the mechanisms underlying this alternate specificity have not been well characterized, this subunit exchange may confer the ability of each complex to interact with a distinct set of cargo, lipids, and regulators (Fields et al., 2007 and 2010; Ang et al., 2003).  Two alternate forms of the AP-1 complex have also been identified in yeast, which share the large γ and β (Apl2, Apl4) and small σ (Aps1) chains, differing only by the alternate inclusion of either Apm1 or Apm2 as the medium μ subunit (Stepp et al., 1995).  The characterized AP-1 complex, which incorporates Apm1, has a well-established role in transport of cargo, including Chs3 (Chitin Synthase 3) and Ste13 between Golgi and endosomes (Valdivia et al., 2002; Foote and Nothwehr, 2006). No sorting role has previously been identified for the Apm2-containing complex.  Early studies suggested that the Apm1 and Apm2-containing complexes are biochemically and functionally distinct; they co-fractionate with separate clathrin-coated vesicle populations, and while deletion of APM1 enhances the defects in growth and -factor processing in combination with a temperature-sensitive allele of clathrin light chain, deletion of APM2 does not (Stepp et al., 1995).  A screening approach to identify regulators of the yeast Snc1/synaptobrevin endocytic recycling pathway was previously reported (Chapter II/Burston et al., 2009).  Through this approach, a role for the alternate AP-1 clathrin adaptor complex containing Apm2 (AP-1R; AP-1-related) in the regulation of Snc1 cell surface levels was revealed.    56 The work reported in this chapter demonstrates that AP-1R is involved in Snc1 intracellular transport, and that AP-1 and AP-1R mediate different sorting pathways. Additionally, a requirement for the previously uncharacterized gene, YFL034w in AP-1R- mediated Snc1 recycling was identified.  Yfl034w binds specifically to AP-1R vs. AP-1, and we have therefore named it IMA1 (interacts with mu Adaptin 1).  Furthermore, this work demonstrates that Ima1 is a putative enzyme of the serine hydrolase family, conserved among eukaryotes, and its catalytic activity may be required for Snc1 transport. This finding is significant, as a growing body of research has identified interactions between AP medium subunits with various enzymatic regulators, although this is the first study to investigate this in yeast.   3.3. Results 3.3.1. A role for the variant AP-1R complex in endocytic recycling  In the genome-wide screen to identify genes required for the intracellular recycling pathway of the yeast synaptobrevin homolog Snc1 (described in Chapter 2), deletion mutants of 3 subunits of the AP-1 complex resulted in increased Snc1 surface levels.  These results were surprising, as the subunits that were identified (Apl4, Aps1, and Apm2, table A2) are components of the functionally uncharacterized AP-1 isoform, AP-1R. Interestingly, loss of the uncharacterized gene YFL034w/IMA1 also led to increased Snc1 surface levels.  Ima1 has been predicted to bind AP-1R components in multiple high-throughput interaction studies (Krogan et al., 2006; Gavin et al., 2006).  Furthermore, AP-1R components and IMA1 shared similar genetic interaction profiles with a panel of trafficking mutants representing various sorting pathways, and were highly-connected based on our network analysis (Burston et al., 2009).  Collectively, these results suggest that Ima1 and AP-1R may share a related role in Snc1 transport. To verify that loss of AP-1R components leads to increased surface levels of GSS, these results were quantified in liquid culture (Fig. 3.1, A).  Loss of APM2 and APL4 led to GSS surface levels significantly greater than WT.  Although this phenotype was reproducible, it was weak. The increased GSS surface levels in apm2∆ mutants were lower than in yap1801∆ mutants.  As described in chapter 2, yAP1801 is an endocytic adaptor required for Snc1 internalization, which is partially redundant with its homolog, yAP1802. This defect was specifically due to loss of AP-1R, as deletion of the AP-1 specific subunit, APM1, did not result in increased Snc1 surface levels.   57 3.3.2. AP-1R mediates intracellular recycling As Snc1 maintains a steady state surface localization through continuous rounds of endocytosis and redelivery through endosomal recycling, the increased surface levels of Snc1 in the absence of AP-1R could reflect either a defect in the rate of endocytosis or an increase in the rate of surface recycling.  An endocytic role for AP-1R would be surprising, as AP-1 has a well-established role in intracellular sorting, and localizes to Golgi and endosomal compartments (Valdivia et al., 2002; Fernández and Payne, 2006).  However, as no requirement for the endocytic adaptor AP-2 in Snc1 internalization was identified in the primary screen, it was considered possible that AP-1R may have a role in endocytosis.  Whether AP-1R could be detected at endocytic sites was determined by comparing the localization of Apm2 with that of the endocytic AP-2 medium chain, Apm4 in cells treated with LAT-A, which permits the visualization of cortical actin patches. While Apm4 co- localized with Clc1 in coated pits at the plasma membrane, Apm2 did not.  Instead, it localized to intracellular compartments (Fig. 3.1 B, upper). In very few cases, however, Apm2 was observed in close proximity to cortical patches.  The kinetics of these surface patches was further investigated.  While Apm4 retained co-localization with clathrin at the plasma membrane over the course of the TIRF experiment, Apm2 showed dynamic activity in relation to these cortical clathrin-containing patches (Fig. 3.1 B lower).  These results suggest that Apm2 is mostly present in intracellular compartments, consistent with a role for AP-1R in the intracellular recycling of Snc1, and not in endocytosis.   3.3.3. AP-1R and Ima1 localize to Golgi/endosomal compartments As Apm2 localized to motile intracellular structures, the identity of these structures, and whether they contain clathrin was investigated.  AP-1 has previously been shown to localize to Golgi/endosomal compartments (Valdivia et al., 2002).  To determine if this is also the case for AP-1R, fluorescence microscopy was used to compare the localization of Apm2-GFP relative to Sec7-RFP, a marker of late Golgi and endosomal compartments (Franzusoff et al., 1991). Consistent with a role in Golgi/endosomal sorting, substantial overlap was observed between Apm2-GFP and Sec7-RFP (Fig. 3.2 A).  Apm2-containing structures also showed overlap with intracellular clathrin patches (Fig. 3.2 B). The distinct sorting roles of AP-1 and AP-1R could reflect a different localization of the two complexes.  To investigate whether AP-1 and AP-1R have non-overlapping distributions, the localization of Apm1 and Apm2 were compared.  Consistent with previous findings, Apm1 localized to Golgi/endosomal membranes.  Direct co-localization of Apm1- 58 RFP and Apm2-GFP revealed substantial overlap of Apm2-GFP and Apm1-RFP at these compartments (Fig. 3.2 C).  Together with the functional invertase assays, AP-1 and AP-1R likely have non-overlapping sorting roles, and that this cannot likely be explained based purely on differential localization of the two complexes, as assessed by this study.  As Ima1 was also identified by our screening approach, and is a predicted binding partner of AP-1R, this suggested that it may be involved in AP-1R function. If this were the case, Ima1 would likely localize to compartments consistent with AP-1 function.  Although Apm2 and Ima1 could not be co-localized directly due to the low expression of both proteins, Ima1-GFP shared a similar extent of co-localization with both Apm1 and intracellular clathrin as did Apm2 (Fig. 3.2 D and E), suggesting that Ima1 and AP-1R localize to similar compartments, and that Ima1 may have a role in AP-1R-mediated transport. 3.3.4. Ima1 and AP-1R are not required for the transport of AP-1-dependent cargo Since Ima1 localized to compartments consistent with AP-1 function, the next question to be addressed is whether Ima1 functions specifically with AP-1R, or with both forms of AP-1.  If Ima1 functions specifically with AP-1R, it could suggest a regulatory role, and may contribute to the specific sorting function of the complex. The relative importance of Ima1 in AP-1R versus AP-1-mediated trafficking was investigated by determining if Ima1 is required for sorting of AP-1-dependent cargo. AP-1 is required for the endosomal transport of the chitin synthase Chs3 (Valdivia, 2002), and when deleted, can restore the cell surface translocation of Chs3 from late Golgi/endosomes in chs6Δ cells, in which this pathway is blocked.  It has previously been shown that Apm2 does not contribute to this sorting role (Valdivia et al., 2002).  We therefore compared the requirement for AP-1R and Ima1 in Chs3 transport using a previously established assay to measure Chs3 surface levels, based on the fluorescence levels observed for cells grown on media containing Calcofluor white (CW).  While deletion of AP-1 (APM1, APL2), restored WT cell surface levels of Chs3 in chs6Δ cells, deletion of either AP-1R (APM2) or IMA1 did not lead to an obvious restoration (Fig. 3.3, A).  Furthermore deletion of APM2 did not affect Chs3 surface levels in combination with deletion of either APM1 or IMA1. These results suggest that Ima1 functions preferentially with AP-1R, and has a minor, if any role in AP-1 transport.  59 3.3.5. Ima1 specifically binds the AP-1R C-terminal domain If Ima1 localization overlaps with both AP-1 and AP-1R, how does Ima1 specifically contribute to AP-1R function?  One explanation is that Ima1 may bind preferentially to AP- 1R vs. AP-1, as demonstrated in multiple genome-wide studies.  To investigate this, the ability for Ima1-GFP to co-immunoprecipitate Apm2-HA versus Apm1-HA was assessed.  Ima1-GFP co-precipitated exclusively with Apm2-HA, while no interaction was observed with Apm1-HA (Fig. 3.3, B).  This confirmed that Ima1 interacts preferentially with the AP- 1R vs. the AP-1 complex, and may therefore play a role in AP-1R regulation. Most AP-1 regulators interact with the appendage domain formed by the Gamma subunit (GAE domain, Page et al., 1999; Hirst et al., 2003), although a few have been found to bind to the Beta appendage (Edeling et al., 2006). It was therefore evaluated whether Ima1 interacts with the AP-1 Gamma appendage.  Interestingly, Ima1-GFP co-purified with Apl4-HA from yeast cell lysates, and this interaction was maintained in the absence of the Apl4 GAE appendage domain, suggesting that Ima1 binds to the AP-1R core complex (Fig. 3.3 C).  Although the role of the Beta appendage in mediating this interaction was not tested, it is likely that Ima1 interacts with the AP-1R core complex, since Ima1 interacted preferentially with AP-1R vs. AP-1, and these complexes differ only by the alternate inclusion of Apm1 and Apm2. To better define the interaction between Ima1 and AP-1R, a Yeast Two-Hybrid assay was carried out between Ima1 and Apm2, which confirmed the interaction between the full- length proteins.  Based on structural homology to other  adaptin chains, Apm2 is divided into an N-terminal domain, required for incorporation into the AP complex, and a C- terminal domain, which contains regions for both membrane recruitment and tyrosine- based cargo binding (Collins et al., 2002). To potentially narrow down the role of Ima1 in AP-1R regulation, further yeast-two hybrid assays were used to identify the regions involved in this interaction. This demonstrated that the Ima1 N-terminal domain (residues 1-262) interacted with the Apm2 C-terminal domain (Fig. 3.3 D).  As Ima1 binding does not require the presence of the Apm2 N-terminal domain, which mediates its assembly into the AP-1 complex, Ima1 likely interacts directly with Apm2, and not through another complex subunit. Based on structural analysis, the C-termini of adaptor  chains can be further divided into distinct subdomains (A and B).  Subdomain A forms the tyrosine-binding pocket, while subdomain B contains regions shown to interact with specific membrane lipids and regulatory factors (Owen and Evans, 1998, Heldwein et al., 2004).   Further Apm2  60 truncations revealed a minimal binding region of residues 389-562, which constitutes the B domain, and lacks subdomain A.  This indicates that Ima1 does not interact with Apm2 as a typical cargo through the tyrosine-binding pocket, but may associate with it through a region which, by analogy to other  subunits, contains sites for multiple regulatory and lipid interactions (Fields et al., 2010; Owen and Evans, 1998; Heldwein et al., 2004). 3.3.6. Ima1 is not required for AP-1R recruitment or interaction with cargo The work described above demonstrates that Ima1 is both functionally and physically associated with AP-1R, and may regulate the sorting function of this AP complex.  There are multiple mechanisms by which Ima1 may regulate AP-1R.  Ima1 may be important for the recruitment of AP-1R to Golgi/endosomal membranes, or may be an alternate cargo adaptor, linking Apm2 to Snc1. To determine if Ima1 is required for AP-1R membrane recruitment, fluorescence microscopy was used to compare Apm2-GFP localization in WT and ima1Δ cells.  No significant differences in the number of Apm2 membrane puncta in the absence of Ima1 were observed (Fig 3.4 A).  To rule out any subtle defects in Apm2 membrane association in the absence of IMA1, subcellular fractionation was used to compare the distribution of Apm2-HA in WT and ima1Δ cells.  Apm2 was enriched in the high-speed (P100) membrane fraction, containing vesicles and small organelles, in both WT and ima1Δ cells, consistent with the microscopy results (Fig. 3.4 B). These studies demonstrate that Ima1 is not important for the membrane recruitment or stabilization of AP-1R. An alternate possibility is that Ima1 may be important for AP-1R cargo recognition.  AP medium subunits bind directly to signals within the cytosolic domain of their respective cargo (Robinson et al., 2004, Owen et al., 2004). Since Snc1 does not contain canonical AP- binding tyrosine or dileucine motifs, Ima1 may be a non-conventional adaptor, bridging the interaction between Snc1 and Apm2. We sought to determine whether Apm2 physically interacts with Snc1 and subsequently, whether Ima1 is required for this interaction.   A GST- tagged Snc1 cytosolic domain was expressed in bacterial cells, and it was determined whether Apm2 could be co-precipitated from yeast cell lysates on a GST-binding column.  Apm2-TAP was pulled down by Snc1-GST, and this interaction was stronger than that between Apm2-TAP and GST alone (Fig. 3.4 C).  This indicates that Apm2 binds to Snc1 through its cytosolic domain, typical of adaptor-cargo binding mechanisms.  This interaction was maintained in the absence of IMA1.  However, a very weak interaction was identified  61 between Ima1-TAP and GST-Snc1 (Fig. 3.4 C), suggesting that Ima1 may be physically associated with the Apm2-Snc1 adaptor-cargo complex. 3.3.7. Ima1 is a conserved protein with a consensus α/β hydrolase catalytic motif   The results described above suggest that Ima1 is not critical for either AP-1R recruitment or cargo binding.  In order to form alternate hypotheses regarding Ima1 function, its molecular properties were further investigated. Ima1 contains a C-terminal DUF726 domain, which is also present in a large number of uncharacterized eukaryotic proteins, from yeast to humans (Fig. 3.5 A).  The DUF726 domain is predicted to conform to an / hydrolase fold, a catalytic domain found in a wide range of eukaryotic enzymes, including thioesterases, lipases, acetyltransferases, and peptidases (reviewed in Holmquist, 2000; Nardini and Dijkstra, 1999).  A BLAST search and sequence alignment revealed that that this domain within Ima1 is highly conserved among eukaryotes.  A characteristic feature of all / hydrolases is the presence of a conserved catalytic triad consisting of a nucleophile (generally a serine within the context of a G-X-S-X-G motif), an acidic residue (D or E), and a histidine.  The residues surrounding the active site are also well conserved, to preserve its structural features.  Based on these homology studies, a potential catalytic triad was identified within the Ima1 C-terminal domain, which was 100% conserved.  The conserved residues consist of S759 (within the motif GFSIG), D817, and H858. Ima1is predicted to be a trans-membrane protein, according to its hydrophobicity profile (TMHMM Server v. 2.0 http://www.cbs.dtu.dk/services/TMHMM, accessed on January 17, 2011).  If this were the case, however, the putative enzymatic domain would be contained within the predicted membrane-spanning region, which would not permit the association of this activity to potential substrates. To examine whether Ima1 is likely to be integral to the membrane, as predicted, subcellular fractionation was used.  This showed that Ima1 is present mostly in the soluble S100 fraction (Fig. 3.5 B).  The punctate membrane localization of Ima1 observed by microscopy suggests that it is likely peripherally membrane associated through weak or transient interactions with other membrane components.   These studies were followed up by determining whether the membrane association of Ima1 is influenced by treatment with Brefeldin A (BFA).  BFA is a fungal metabolite which blocks the GTP exchange and membrane recruitment of Arf1, therefore causing protein transport defects at the ER and Golgi, and the mislocalization of proteins whose recruitment to these membranes depend on Arf1 (Donaldson et al., 1992). Upon brief treatment of cells  62 with 100ug/mL BFA, Ima1 membrane localization was lost (Fig. 3.5 C).  This suggests that Ima1, like many other clathrin coat-associated proteins, is localized either directly by Arf1 or indirectly through interaction with Arf1-dependent components, and that Ima1 is likely dynamically recruited from the cytosol to sites of AP-1R function.  Together, the findings that the putative catalytic domain of Ima1 is not likely membrane spanning, and that Ima1 interacts with Apm2 through its N-terminal domain, supports that the putative catalytic residues may be accessible for binding to substrates and carrying out catalysis at these sites. 3.3.8. The Ima1 GXSXG catalytic motif is required for normal Snc1 surface levels To investigate whether the conserved predicted catalytic site identified in Ima1 is required for Snc1 sorting, the motif GFSIG containing the catalytic serine nucleophile was mutated to AFAIA by site-directed mutagenesis.  The ability of this mutant construct (Ima1CM catalytic mutant) to restore normal Snc1 surface levels ima1Δ cells was assessed by a plate-based invertase assay (Fig. 3.5 D).  Loss of IMA1 led to a significantly increased level of Snc1, as compared to WT cells in this assay.  This increase was partially complemented by introduction of a plasmid expressing WT IMA1 (pIMA1), as Snc1 surface levels were lowered relative to ima1Δ.  This complementation was not complete, likely because the final screening media (YPF) does not allow for plasmid selection.  Introduction of a plasmid expressing the catalytic mutant (pIMA1CM) however, did not complement the Snc1 sorting defect to any degree.  This suggests that Ima1 may have catalytic activity required for its role in Snc1 sorting by AP-1R.  The serine hydrolases include thioesterases, which catalyze the depalmitoylation of proteins (Zeidman et al., 2009). Snc1 is palmitoylated at a single cysteine residue, adjacent to its transmembrane domain, although the effects of this modification are unknown (Couve et al., 1995; Valdez-Taubas and Pelham, 2005). Since cycles of protein palmitoylation and depalmitoylation have been shown to regulate the transport of SNARE proteins (Valdez- Taubas and Pelham, 2005; He and Linder, 2009), one possibility is that Ima1 might have a role in Snc1 depalmitoylation, which may, in turn be required for its transport by AP-1R.  No increase in Snc1 palmitoylation was observed when IMA1 was overexpressed, as assessed using the Acyl-biotin exchange assay (Fig. 3.6 A and B).  This suggests that Ima1 does not likely have a direct role in its depalmitoylation.  63 As serine hydrolases catalyze a diverse array of reactions, future work should focus on identifying the biologically relevant substrates of Ima1, which will further our understanding of the role of Ima1 in AP-1R-mediated transport.   3.4. Discussion 3.4.1. AP-1R mediates Snc1 intracellular recycling In this study we identified a specific requirement for AP-1R in the endocytic recycling of the yeast synaptobrevin homolog Snc1, the first identified role for this complex.  The co-localization of AP-1R with intracellular clathrin at Golgi/endosomal compartments supports a role for AP-1R in Snc1 recycling, and not internalization. Although the precise role of AP-1R in this pathway remains to be determined, the increase in cell-surface Snc1 in the absence of AP-1R may reflect re-routing of Snc1 along an alternate bypass pathway with faster recycling kinetics than that of the AP-1R-mediated pathway. AP-1 has also been shown to play a role in the transport of the S. pombe synaptobrevin homolog, Syb1 (Kita et al. 2004; Ma et al., 2009).  Deletion of both the medium chain Apm1, homologous to yeast Apm1, and the small chain of the AP-1 complex resulted in the accumulation of Syb1 in Golgi⁄endosomes.  In addition, loss of fission yeast Apm1 function causes defects in cellular processes such as secretion, cytokinesis, vacuole fusion, and cell wall integrity. Deletion of AP-1 in S. cerevisiae, however, results in no discernible phenotypes and does not cause the intracellular accumulation of Snc1.  Despite these differences, both of these studies support the role of AP-1 in the endosomal sorting of synaptobrevin.  While Ima1 is present in S. pombe, Apm2 does not have considerable homology to either of the two AP-1 medium subunits.  In the future, it would be interesting to determine if the fission yeast Ima1 homolog plays a role in AP-1-mediated sorting of Syb1. 3.4.2. Apm2 binds to Snc1 as cargo A significant finding of this study is that Apm2 interacts with the Snc1 cytosolic domain, which is consistent with the well-established role of AP medium subunits in cargo recognition.  Like most SNAREs, Snc1 does not contain tyrosine or di-leucine motifs.  In mammalian cells, only VAMP4 and VAMP7 contain recognizable di-leucine-based motifs (Peden et al. 2001).  Multiple adaptor complexes have now been shown to interact with SNAREs of the VAMP family, and a growing body of research suggests that most of these interactions are mediated by nonconventional mechanisms. The use of folded regulatory  64 domains, rather than the commonly used short, linear motifs, and specialized components of the transport machinery appears to be the paradigm for sorting SNAREs into post-Golgi transport vesicles (Miller et al., 2007; Chidambaram et al., 2004). As the fidelity of vesicle fusion processes in the cell requires appropriate amounts of SNAREs at their correct locations, these specialized mechanisms are likely in place to ensure that the transport of SNAREs are not vulnerable to competition from standard motif-containing cargo, and that sufficient amounts of the correct SNAREs are incorporated into CCVs for transport. The in vitro binding assays used in this study could not resolve whether Apm2 interacts directly with Snc1, or if additional factors are required to bridge this interaction.  If this interaction is direct, it must be mediated by non-conventional sorting signals.  Apm2 may recognize Snc1 through a folded epitope.  Structural studies would therefore be insightful in the understanding of how this interaction is mediated. The primary screen identified a weak requirement for the epsins Ent1 and Ent4, suggesting the possibility that they bridge the interaction between Apm2 and Snc1.  As discussed, epsins are known to function as alternate sorting adaptors, and have been shown to bridge the interactions between SNAREs and AP complexes.  In yeast, Ent1 is partially redundant with Ent2 for internalization (Wendland et al., 1999). Ent3/5 are required for endosome to Golgi recycling of both Chs3 and Snc1, and bind to multiple SNAREs, including Vti1 and Pep12 (Chidambaram et al., 2004), while Ent4 mediates transport from the Golgi to the vacuole (Deng et al., 2009).  Whether one or more epsins bridges the interaction between Apm2 and Snc1 should be a priority in future work. 3.4.3. Distinct sorting functions for AP-1/AP-1R  These results support that the two alternate AP-1 complexes in yeast have largely non-overlapping functions. Deletion of AP-1R, but not AP-1, results in increased Snc1 surface levels. Conversely, deletion of AP-1R has no effect on the recycling of Chs3, which is mediated by AP-1 (Valdivia et al. 2002). As APM1 mutants, but not APM2 mutants display synthetic phenotypes in combination with a temperature sensitive allele of CLC1 (Stepp et al., 1995), it has been suggested that Apm2 may function in a non-clathrin-mediated pathway.  This seems unlikely, however, as Apm2 co-fractionates with clathrin-coated vesicles (Stepp et al., 1995), and the results reported here demonstrated that Apm2 co- localizes with intracellular clathrin.  As Apm1 and Apm2 have distinct co-fractionation profiles with clathrin, they likely function in different clathrin-mediated pathways.    65 Alternate forms of AP-1, formed by medium subunit exchange have been identified in other organisms, including C. elegans and mammalian polarized epithelial cells. In both examples, these complexes have largely non-overlapping roles.  In C. elegans, disruption of UNC-101 (the 1 homolog), and mutation of the alternate medium chain Apm1 have distinct effects on viability (Shim et al., 2000). In polarized epithelial cells, the ubiquitously expressed AP-1A mediates TGN to endosome transport of the proprotein convertase furin, while the epithelial cell-specific AP-1B is required for the polarized targeting of the transferrin and LDL receptors from recycling endosomes.  These complexes are not functionally interchangeable, as introduction of AP-1A cannot complement the sorting defects of AP-1B-deficient polarized cells, and vice versa.   3.4.4. AP-1/AP-1R localize to similar intracellular compartments The non-redundant cargo-specific functions of AP-1A and AP-1B in polarized cells have been partially explained by their differential localization to distinct membrane domains.  Although mammalian AP-1A and AP-1B were first shown to share a similar localization, further studies revealed by immunoelectron microscopy that they define partially distinct subdomains, with AP-1A localizing to the Golgi, and AP-1B localizing to a perinuclear region immediately adjacent to the Golgi (Fölsch et al., 2003).   Despite their specificity for distinct cargo, however, substantial overlap in the localization of Apm1 and Apm2 to Golgi/endosomal compartments was observed, suggesting that the two complexes may recognize distinct sets of cargo from a common membrane.  This overlap was not complete, however.  A small proportion of Apm2 puncta did not co-localize with Apm1, and it is therefore possible that AP-1R facilitates Snc1 recycling through a distinct endosomal population or membrane domain.  Further studies may help to resolve whether there are small-scale differences in AP-1 and AP-1R localization.  Currently, these studies are limited by the incomplete understanding of endosomal organization in yeast.  It is not known if there are functionally distinct populations of early endosomes, or if endosomal membranes contain subdomains, with different compositions.   3.4.5. Role of Ima1 in AP-1R regulation In this study, Ima1 was identified as a specific regulator of AP-1R.  Deletion of IMA1 resulted in increased Snc1 surface levels, and it shared a similar genetic interaction profile with AP-1R components based on E-MAP studies (Burston et al., 2009).  Both Ima1 and AP- 66 1R localize to Golgi/endosomal compartments.  Furthermore, a preferential and likely direct interaction between Ima1 with Apm2, but not Apm1 was demonstrated.   The interaction between Apm2 with Ima1 was surprising, as most AP-regulatory proteins associate with the appendage domains of the large subunits (Page et al., 1999; Hirst et al., 2003).  A few recent studies, however, have reported that the medium subunit also participates in regulatory interactions.  Many µ-binding regulators are enzymes that have important roles in lipid regulation. Some of these regulators are themselves tyrosine- based cargo proteins, and bind to the canonical µ binding pocket.  For example, the lipid kinase PIPKI gamma-p90 interacts with the AP-2 µ subunit. (Kahlfeldt et al., 2010).  Binding to AP-2 µ stimulates the kinase activity of PIPKI gamma-p90, facilitating localized PI(4,5)P2 synthesis activity at endocytic sites.  The increased PI(4,5)P2, in turn leads to enhanced AP-2 recruitment to these sites.  This interaction is therefore cooperative, and enhances the activity of both the adaptor and the regulator in a positive feedback loop. The interaction between Ima1 and Apm2 is mediated through the N-terminal 162 amino acids of Ima1.  Within the Apm2 µ2 C-terminal region, Ima1 binds subdomain B, and does not require its tyrosine motif-binding site.  Interestingly, this region is quite divergent between Apm1 and Apm2, suggesting that it could contribute to the sorting specificity of the two complexes due to differential interaction with Ima1.  In regions where µ1 homologs contain negatively charged residues, the corresponding residues in 2 homologs are often positively charged and vice-versa.  A recent study identified a patch of three positively charged residues within the corresponding region of the mammalian AP-1B µ1-B subunit, which are conserved among µ1-B homologs, but not with those of µ1-A homologs (Fields et al., 2010). This patch was required for the differential recruitment of AP-1R complexes to PI(3,4,5)P3-rich recycling endosomes, and upon mutation of these residues to the corresponding residues in 1-A, this localization was lost, resulting in missorting of AP-1B- dependent cargo.  Furthermore, AP-1B expression was required for the localization of PIPKI-gamma90, which generates PI(3,4,5)P3 at recycling endosomes.  This indicates that there is interdependence in the function of both AP-1B, and PIPKI-gamma90.  It was proposed that AP-1B either binds PI(3,4,5)P3 directly, or that it is recruited  by an unidentified protein that requires PI(3,4,5)P3 for its localization.  Since Ima1 binds to the region of Apm2 which by analogy to other µ subunits, contains residues important for lipid binding, it was hypothesized that Ima1 could be required for the membrane localization of AP-1R.  However, no decrease in membrane  67 binding of AP-1R in ima1∆ cells was observed by either microscopy or subcellular fractionation.  The possibility still remains that Ima1 is required for recruitment of AP-1R to the small population of compartments that do not contain Apm1.  It is also possible that Ima1 is necessary for recruitment of AP-1R to specialized lipid domains within membrane compartments containing both complexes.   This study also demonstrated that Ima1 is not required for Apm2 cargo binding.  The in vitro approach that was taken, which assessed the binding of Apm2 from cell lysates to an immobilized GST-Snc1 construct, suggesed that Ima1 does not form a direct link between Apm2 and Snc1, and is not required for any modification of Apm2 necessary for this binding.  It remains to be determined whether Ima1 is required for the interaction between Apm2 and Snc1 in vivo, as no reproducible interaction between these proteins was detected by coimmunoprecipitation. These results are consistent with a weak and transient interaction between Apm2 and Snc1 in vivo, as has been shown by multiple other studies for adaptors and their respective cargo.  It remains possible that Ima1 is required for a later step in AP-1R function, such as vesicle formation or un-coating.  Investigating these possibilities is of priority for future studies. 3.4.6. Ima1 has putative enzymatic activity The only previous study investigating the function of Ima1 was based on its interaction with the P0 subunit of the ribosomal stalk, which is translocated to the cell surface by unknown mechanisms (Aruna et al., 2004). The precise role of Ima1 in this process, however, has not been further investigated.   Our homology studies revealed that Ima1 is conserved among eukaryotes, and is a member of the α/β-hydrolase family.  This is a catalytic domain found in a wide-range of enzymes, including esterases, lipases, acetyltransferases, and peptidases, containing a unique structural fold, and encompassing a catalytic triad, consisting of the residues (Ser, Cys, or Asp), Asp/Glu, and His.  We identified a putative catalytic site in Ima1, conforming to this consensus.  This site is characteristic of serine hydrolases, and is 100% conserved among all considered sequences.  Serine hydrolases are generally cytoplasmically localized, and show transient recruitment to their sites of activity.  Although Ima1 is predicted to be a transmembrane protein, this work demonstrates that it is mainly cytosolic, and that it is likely has a dynamic localization to Golgi/endosomal compartments.  The conserved Ima1 catalytic residues appear to be required for Snc1 sorting, as a mutant version in which these  68 residues were mutated to alanine was unable to complement Snc1 surface levels in ima1∆ cells.  An important challenge in the future will be to characterize the precise enzymatic activity of Ima1 and to identify its biologically relevant substrates.  Based on its binding to the Apm2 B domain, Ima1 may play a role in lipid remodeling at Golgi/endosomal compartments.  A full understanding of Ima1 function will require the identification of its substrates, and a better understanding of the organization of endosomal membranes in yeast. In conclusion, this work has identified a role for the previously uncharacterized AP- 1R complex in Snc1 recycling, a function distinct from AP-1.  Furthermore, Ima1 was specifically required for AP-1R-mediated transport, and has putitive enzymatic activity related to this function.  These findings fit with a growing body of research suggesting that alternate isoforms carry out distinct sorting functions through participating in differential interactions with sorting determinants, and provide new evidence that AP medium subunits are the target of interactions by enzymatic regulators. 3.5. Materials and methods Construction of plasmids and yeast strains Plasmids and yeast strains constructed for this study, and details of their construction, are listed in Table B1. Unless otherwise indicated, plasmids were constructed by homologous recombination after cotransforming yeast with linearized vector and DNA fragments bearing 50–55-bp homology, and recovering recombinant plasmids in E. coli. The MATa yeast strain BY4741 and its gene deletion derivatives were obtained through Thermo Fisher Scientific. Unless otherwise stated, gene disruptions and tagging of genomic ORFs were performed by transformation of a PCR product containing a drug selection marker, flanked by 50–55 bp of homology to the region of interest.   Liquid invertase assay The liquid invertase assay used in this study is modified from that previously described (Darsow et al., 2000). Strains expressing either the GSS construct were inoculated into 2ml YP fructose cultures and allowed to grow for 20 hours to saturation (OD 600 ≈10). Cultures were diluted to 3OD/mL, and 5μl was mixed with 55μl 0.1M NaOAc buffer pH4.9 inside a well of a 96 well microtiter plate. With the use of a Victor3 multilabel counter and injectors (PerkinElmer, Waltham, Massachusetts), 13μl of freshly prepared 0.5M ultra pure sucrose was added to each well, and the plate was incubated for 5min. at 30°C. Following  69 sucrose incubation, 100μl of glucostat reagent (0.1M  K2HPO4  pH 7.0, 347.1 U Glucose Oxidase, 2.6 ng/ml Horseradish peroxidase (HRP), 102.6 nM N-ethylameide (NEM), 0.15 mg/ml O-Dianisidine) was added to each well, and  the plate incubated for an additional 7min. at 30°C. Finally, 100μl of 6N HCL was added to each well to stop the reaction. The absorbance of each well at 540nm was measured and used to determine glucose concentration. Results are reported as nM glucose produced per 1 OD600 of culture.  Glucose standards (ranging from 5-50nM) and blanks were included in each experiment to ensure accurate measurements that were within the linear range.  Calcofluor white screening Knockout strains were plated in 1,536-array format onto YPD plates containing 50 μg/ml CW (Sigma-Aldrich), using a Virtek automated colony arrayer (Bio-Rad Laboratories). After incubation at 30°C for 3 d, white-light images were acquired using a flat-bed scanner (model 2400; Epson), and fluorescent-light images were captured with a Fluor S Max MultiImager (Bio-Rad Laboratories) using the 530DF60 filter and Quantity One software (version 4.2.1; Bio-Rad Laboratories). The open-source spot-finding program GridGrinder (http://gridgrinder.sourceforge.net) was used for the densitometry of digital images. Average growth and fluorescence values from two independent screens were calculated for each strain using Excel (Microsoft).  Fluorescence microscopy  Indirect immunofluorescence microscopy, fluorescent microscopy of yeast cells expressing GFP-tagged proteins were carried out as described (Conibear and Stevens, 2000, 2002). Cells were viewed using a 100x oil-immersion objective on a Zeiss Axioplan2 fluorescence microscope, and images were captured with a CoolSnap camera using MetaMorph software and adjusted using Adobe Photoshop.  Immunofluorescence experiments involving BFA were carried out by incubating cells from early-log phase cultures in a final concentration of 100ug/mL BFA for 10 minutes.  Two color widefield images were acquired and processed as described in chapter 2.  Exposure times varied from 600-750ms.  TIRF images were collected with a 3i Marianas microscope (Intelligent Imaging Innovations, Denver, CO) equipped with an alpha Plan-Fluar 100x 1.46 NA objective and a Zeiss TIRF slider (Carl Zeiss, Thornwood, NY). Images were acquired with 488nm and/or 561nm laser excitation, with GFP and RFP emission split between two Cascade II 512  70 cameras with an Optical Insights Dual Cam  with an exposure time of 750ms. TetraSpeck 100nm beads (Invitrogen) were used to align the two channels and for subsequent registration in software. Slide-Book 4.2® software (Intelligent Imaging Innovations, Denver, CO) was used for image acquisition and dual channel image registration. Montages were created using the National Institute of Health ImageJ software (http://rsb.info.nih.gov/ij/) with the Kymograph plugins installed (http://www.embl.de/eamnet/html/kymograph.html). Live-cell imaging experiments involving LAT-A treatments were performed by incubating cells from early-log phase cultures in a final concentration of 200 μM LAT-A dissolved in DMSO for 30 min at 30°C. LAT-A treated early-log phase cultures were used for the total internal reflection microscopy (TIRF) experiments. For each TIRF experiment 200 μL of treated cells were spotted onto Conconavalin A-coated 8 well Lab-Tek dishes (Nalge Nunc, Rochester, NY).   Co-immunoprecipitation Log phase cells were converted to spheroplasts and stored at -85°C (Conibear and Stevens, 2000).  Spheroplasts from 20OD600 of cells were resuspended in 1mL lysis buffer (600mM Sorbitol, 50mM KH2PO4 pH7.5, 50mM NaCl, 1.5%TX-100), on ice for 10 minutes.  Lysates were incubated with 40ul IgG sepharose (75% slurry) for 2.5 hours, rotating at 4°C.  The pellets were washed two times with 1ml lysis buffer (50mM KH2PO4 pH 7.5, 75mM NaCl, 1.5% TX100), and were subjected to SDS-PAGE.  Co-precipitated proteins were detected by Western blotting with antibodies to GFP (mouse mαGFP 1:1000, Roche #1814460, monoclonal) HA (mouse mαHA 1:1000, Abcam #ab16918, monoclonal) or TAP (rabbit α-TAP 1:5000, Open biosystems #cab1001 polyclonal) followed by HRP-labelled secondary antibodies (GAR-HRP Biorad #170-6515 or GAM-HRP Biorad #170-5047).  Blots were developed with ECL and exposed to X-ray film (X-OMAT LS, Kodak).  In vitro Snc1-GST binding assays Truncated Snc1 lacking its transmembrane domain cloned into vector pETGEXCT (Sharrocks, 1994, gift from Anne Spang). Snc1-GST was expressed and purified from in E. coli BL21 using standard procedures. Bacterial Induction of GST proteins and immobilization on glutathione:  Cells were grown at 37°C to mid-log phase, and expression was induced at 30°C by addition of 1mM IPTG for 3 hours.  3 OD pellets were frozen at  71 stored at -85°C.  Cell pellets were lysed by sonication in PBS, on ice (in the presence of protease inhibitors).  Bacterial lysates were incubated with 20 ul of 50% glutathione Sepharose 4B for 1 hour at 4°C, while rotating.  Unbound proteins were removed with three washes in PBS. Incubation of yeast lysates with immobilized GST proteins: Yeast lysates were prepared as described above.  Lysates were incubated with GST proteins immobilized on glutathione sepharose beads for 2.5 hours at 4°C, while rotating (total volume of 1mL; NaCl adjusted to 150mM).  Following incubation, beads were washed two times with cold lysis buffer.  Samples were heated to 70°C in SDS sample buffer, and eluted proteins were analyzed by SDS-PAGE and Western Blotting, as described above.  Yeast two-hybrid screening PJ694a strains carrying pOAD-based vectors were mated to PJ694alpha strains carrying pOBD2-based plasmids expressing the indicated full length and truncation proteins (Tong et al. 2002).  Positive two-hybrid interactions were scored on minimal media lacking histidine (containing 5mM 3-AT) or adenine after growth at 30°C for 5 days.    Subcellular fractionation Fractionation of organelles was performed by differential centrifugation of cell lysates as described by Conibear and Stevens (2000).  20 OD600 of exponentially growing cells were spheroplasted, lysed and centrifuged for 5 min at 500 g to remove unbroken cells. The supernatant was centrifuged for 10 min at 13,000 g to generate the membrane pellet fraction (P13), and the supernatant (S13) was centrifuged at 100,000 g for 60 min generating the P100 pellet fraction and S100 supernatant. The membrane pellets were re- suspended in 300ul sample buffer. Proteins in the S100 fraction were precipitated by the addition of TCA to a final concentration of 5%, collected by centrifugation for 5 min at 13,000 g, washed twice with acetone, air dried and resuspended in 300ul sample buffer. The proteins in 10ul of each fraction were separated by 15% SDS-PAGE, transferred to nitrocellulose, and were subjected to western blotting, as described above.  Invertase plate assay Colony arrays of strains containing an integrated version of the GSS reporter plus the indicated pRS415-based plasmids were spotted on SC-LEU plates in 96-array format.  This array was then replicated to 384-array and then 1536-array formats on the same  72 media.  For screening, the 1536 array was replicated to YPF plates.  The invertase assay was carried out as described in chapter 2.  Snc1 palmitoylation assay Snc1 palmitoylation was assessed by acyl-biotin exchange (Politis et al., 2005), using a modified version of the Drisdel and Green method (Drisdel and Green, 2004).  Ima1 overexpression was carried out from GAL-based plasmids with a 4-hour galactose-induction period.  Overnight cultures grown in SC-URA+2% raffinose, and were then grown to early log phase, at which point they were transferred to either SC-URA +2% galactose or SC-URA +2% raffinose media for the 4 hour induction period. Denatured protein extracts were prepared from Snc1-GFP–expressing cells by glass bead lysis either with or without IMA1 overexpression. Extracts were subjected to the three steps of acyl-biotinyl exchange protocol.  The epitope-tagged Snc1 was immunoprecipitated with anti-GFP antibodies, and the resulting samples were run on a 10% SDS gel. Western blotting was then carried out with either anti–biotin-HRP or anti-GFP antibodies.       73 3.6. Figures                                        Figure 3.1. AP-1R is required for correct sorting of Snc1 (A) Quantification of cell surface levels of the Snc1 reporter (GSS) at the cell surface in AP-1R deletion strains by invertase assay of liquid cultures. Invertase activity is reported as nmol glucose release/OD600, and the mean +/-SD of 5 independent experiments is shown.  * P<0.001 by student t-test, as compared with WT. (B) Co-localization of Apm4-GFP and Apm2-GFP with Clc1-RFP at cortical actin patches in LAT-A-treated cells by wide-field microscopy (upper panels). Lower panels show TIRF microscopy and kymograph analysis of Apm2-GFP or Apm4-GFP relative to a single cortical clathrin patch marked by Clc1-RFP (sla2∆ cells) A B WT apm1∆ apm2∆ apl4∆ yap1801∆ * * *  74                                          Figure 3.2. AP-1R and Ima1 localize to Golgi and endosomal compartments Co-localization of Apm2-GFP or Ima1-GFP with the RFP-tagged markers Sec7-RFP (late Golgi), Clc1-RFP (clathrin), and Apm1-RFP (AP-1).    Ima1-GFP Ima1-GFP Apm1-RFP Clc1-RFP Apm2-GFP Apm2-GFP Apm2-GFP Sec7-RFP Clc1-RFP Apm1-RFP A  Apm2-GF P  B C D E  75                           Figure 3.3. Ima1 associates functionally and physically with AP-1R (A) Chs3 surface levels were quantified in chs6Δ cells in combination with mutations in AP-1 or AP-1R components and IMA1, based on Calcoflour White fluorescence assay.  Results are reported as spot median pixel intensity, as assessed by densitometry. 605246 +++ +++ +++ + +++ +++ +++ 1 AP-Binding Cargo (A)/lipid (B) binding 1-605 (FL) 246-605 391-605 A AB A AB AB Apl4 Ima1 Ima1-N N/A N/A N/A +++ +++ AD constructsApm2-BD constructs B389-562 B C D A Ima1-GFP: Apm1-HA: Apm2-HA: + + + + -+ - - -GFP -GFP -HA -HA Lysate IP - -GFP -GFP -HA -HA Ima1-GFP: Apl4-HA: Apl4Dear-HA: + + + + - - - + - Lysate IP chs6∆ ima1∆ WT chs6∆ ∆ chs6∆ apl2∆ chs6∆ apm1∆  chs6∆ apm2 ∆ chs6∆ apm1∆ apm2∆ chs6∆ ima1∆ apm2∆ M ed ia n  F lu or es ce n ce  in te n si ty   76 (B) Ima1 preferentially interacts with Apm2 versus Apm1 by co-immunoprecipitation.  Cells were grown to midlog phase and were processed for immunoprecipitation (see Materials and Methods). Immunoprecipitation (IP) was performed with anti-GFP antibodies, whereas Western blotting was performed with both anti-HA and anti-GFP antibodies. (C) Ima1 interaction does not require the Apl4 GAE domain. Immunoprecipitation was carried out as in (B). (D) Yeast two-hybrid assay between full- length Apm2-GAD and Ima1-GBD, and between full-length and N-terminal domain of Ima1 (1-262) with the indicated Apm2 truncations.  Apl4-GBD was used as a positive control for the expression of Full length Apm2.  The relative strength of interaction is indicated, as qualitatively assessed by growth on SC-HIS supplemented with 5mM 3AT.                                     77  ima 1∆ Im a1 -H A Ap m 2- H A  ima 1∆ Im a1 -H A A pm 2- H A           Figure 3.4. Ima1 is not required for Apm2 membrane recruitment or cargo binding (A) Localization of Apm2-GFP in WT vs. ima1Δ cells. (B) Membrane association of Apm2-3HA in WT versus ima1Δ cells, assessed by subcellular fractionation.  Apm2 is enriched in the high speed membrane fraction (P100). Markers of subcellular fractions are Vps10 (Golgi), ALP (vacuole), and PGK (cytosol).  (C) Apm2-3HA binds to immobilized GST- Snc1 in vitro, and does not require IMA1. Purified recombinant GST-Snc1 or GST alone were incubated with lysates prepared from Apm2-3HA WT or Apm2-3HA ima1Δ cells, and a GST- pull down assay was performed. Samples were subjected to SDS-PAGE and analyzed by immunoblotting with anti-HA antibodies. Ima1 interacts weakly with GST-Snc1, as assessed on the same blot.          S100 Apm2-HA Vps10 ALP PGK W T ima 1∆ W T ima 1∆ W T ima 1∆ W T ima 1∆ Lysate P13 P100 WT ima1∆ Apm2-GFP A B Ap m 2- H A Ap m 2- H A Ap m 2- H A Ap m 2- H A -GST SNC1-GST Ima1-TAP Apm2-TAP C WB: TAP   78                                    Figure 3.5. Ima1 contains putative catalytic residues, required for Snc1 sorting (A) Schematic of Ima1, indicating N-terminal Apm2-binding domain, and DUF726 domain (top) Sequence alignment of Ima1 C-terminal domain with conserved homologs, highlighting the conserved catalytic triad residues (bottom) (B) Subcellular fractionation of A Ima1 EtOH BFA (100ug/mL) Ima1- GFP Apl2 -GFP WT pRS415 Ima1∆ pRS415 Ima1∆ pIMA1 Ima1∆ pIMA1CM D A B A C A S100 W T ap m 2∆ W T ap m 2∆ W T ap m 2∆ W T ap m 2∆ Lysate P13 P100 Ima1- GFP Vps10 PGK ALP  79 Ima1).  Control markers for other subcellular fractions are Vps10 (P100; light membrane fraction), ALP (P13; heavy membrane fraction), and PGK (S100; soluble fraction).  (C) Microscopy of Ima1-GFP in cells treated with BFA (100ug/mL, 10 min). Apl2-GFP is included as a control for peripheral membrane association.  (D) Quantification of GSS surface levels in WT versus ima1Δ cells, containing plasmids for the expression of WT IMA1, IMACM (catalytic mutant) or empty vector (pRS415). (invertase overlay assay; n=7 replicates per group).  pRS415-based plasmids were introduced into a background strain expressing the GFP-Snc1-Suc2 (GSS) reporter, and were selected for based on growth on –LEU plates.  Strains were arrayed onto YPF plates in 1536 format, and were assessed for GSS surface levels as described in chapter 2 (genome-wide screening, materials and methods).  Boxes represent upper and lower quartiles.                                         80              Figure 3.6. Overexpression of Ima1 does not affect Snc1 palmitoylation (A) IMA1 GAL-induced overexpression. GAL-inducible plasmids expressing Ima1 (pIMA1GAL) or empty vector control (pBG1805) were introduced into WT cells. Cells grown overnight in SC + 2% raffinose were diluted and grown to mid-log phase (T0), at which point they were grown for 4 hours in SC + 2% galactose for 4 hours.  Overexpression of Ima1 was detected by immunoblotting to HA. (B) Snc1 palmitoylation status was assessed by Acyl- Biotin Exchange (ABE) in strains expressing GFP-Snc1 (endogenously tagged), and overexpressing either IMA1 (pIMA1GAL) or empty vector control (pBG1805) (4h gal induction, as described in A). Cells were were subjected to the acyl-biotin exchange reaction.  Protein extracts were treated with (+) or without (-) hydroxylamine (NH2OH).  Anti-GFP precipitates were blotted with anti-biotin and anti-GFP to detect palmitoylated and total Snc1, respectively.                  BA - + - + 81 CHAPTER 4: DISCUSSION AND FUTURE DIRECTIONS                  82 4.1. Overview The overall goal of this work was to identify the requirements for the endocytic recycling pathway of Snc1, the yeast VAMP2 homolog.   Towards this goal, a sensitive and quantitative assay was used to systematically identify genes required for this pathway, on a genome-wide level.  Genetic and bioinformatic approaches were used to infer functional relationships between top candidates, and to guide downstream molecular analysis of these genes. Through this work, multiple genes were identified that were predicted to function in endocytosis and recycling, but have not previously been shown to have sorting defects. A model that encompasses the findings from this work is proposed in illustration 4.1 Chapter 2 investigated the mechanisms regulating Snc1 endocytosis.  This study identified roles for many yeast homologs of mammalian endocytosis genes, including clathrin and the yeast AP180 clathrin adaptors.  The results showed that yAP1801 and yAP1802 are partially redundant in Snc1 internalization.  Furthermore, they have a cargo- selective function: combined deletion selectively blocked internalization of Snc1, but not other endocytic cargo.  Similarly, the synaptojanin Inp52 also had a cargo-selective function, likely through its role in the uncoating of AP180 from endocytic vesicles.  This study also identified a requirement for the previously uncharacterized protein Ldb17 in the regulation of coat and actin dynamics at endocytic sites. Chapter 3 focused on characterizing components required for Snc1 intracellular recycling, and demonstrated a role for the AP-1 complex variant, AP-1R in this process, and for the previously uncharacterized protein Ima1.  The results support that the closely related AP-1 and AP-1R have cargo-specific functions in Golgi/endosomal transport.  Ima1 was found to be a regulator of AP-1R function, and is specifically associated with AP-1R both functionally and physically, but not AP-1.  It is therefore likely to contribute to the specificity of the AP-1R complex.  Ima1 is highly conserved in eukaryotes, and has predicted enzymatic residues that are required for normal Snc1 surface levels.   Collectively, these studies show that considerable functional redundancy and weak endocytic defects at least partially explain the lack of observable defects for these components in previous studies, and demonstrate that endocytic mechanisms in yeast and man are more similar than previously appreciated. These studies are also consistent with the view that sorting of SNARE proteins is subject to highly specific mechanisms, and that the use of unconventional adaptors may be widespread for these recognition events.   83 Although this work has generated insight into mechanisms regulating Snc1 endocytic recycling, it also encourages new questions.  How is AP180 recruited to endocytic sites, and what is the mechanism by which Inp52 contributes to AP180 uncoating?  The signals in Snc1 that mediate its interaction with the endocytic machinery and with AP-1R also remain to be identified.  These questions, methods to address them, and ways to apply the insight generated here to future studies, are discussed in this chapter.  4.2. Mechanisms regulating Snc1 internalization 4.2.1. Role of clathrin and yeast AP180 homologs in Snc1 endocytosis  A requirement for clathrin and its adaptors in the internalization of Snc1 was a highly significant finding.  This study revealed that the yeast AP180 clathrin adaptor homologs yAP1801/1802 have a partially redundant role in Snc1 internalization. While individual deletion of yAP1801 or yAP1802 led to a relatively weak endocytic defect, combined deletion of yAP1801/1802 completely blocked internalization.  Furthermore, yAP180 was not required for the uptake of other commonly studied endocytic cargo.  The partial redundancy and cargo-specificity of these adaptors serve to explain why endocytic defects have not previously been identified for yAP1801 and yAP1802. This was significant because although clathrin contributes to the total number of endocytic sites and to the stability of endocytic complexes, no cargo has previously been shown to be dependent on clathrin or its adaptors for internalization in yeast (Newpher et al., 2005; Drubin et al., 2005). This discrepancy has remained unexplained in the field for decades, as it contrasts with the essential role for clathrin in mammalian cells.   There are many important questions raised by our work on yAP180 that should be addressed in future studies.  What are the mechanisms regulating its recruitment to endocytic sites, and release from endocytic vesicles?  Does AP180 bind to cargo directly, or through additional bridging interactions?  In this study, some of these questions were addressed.  In the context of our findings, future approaches that would be useful in further addressing these questions are discussed below. 4.2.2. How is yAP180 recruited to endocytic sites? We identified a strong requirement for clathrin in Snc1 uptake, but found that AP180 does not need to bind to clathrin directly to carry out internalization, as deletion of its clathrin binding site did not prevent Snc1 uptake.  This suggested that AP180 might be  84 linked to clathrin through additional proteins.  Although CLASPs generally bind to AP-2 for recruitment to endocytic sites (Maldonado-Báez and Wendland, 2006), we did not identify a requirement for AP-2 in Snc1 uptake.  It thus remains unclear how yAP180 is recruited.  The requirement for clathrin and AP-2 for AP180 recruitment appears to differ between organisms, and thus remains unclear.  In C. elegans, it is likely that AP180 works with AP-2 to direct internalization, as a similar increase in surface levels was shown in AP180 and AP- 2 mutants (Dittman and Kaplan, 2006).  In mammalian cells, however, the AP-2 binding sites within AP180 have only a minor contribution, suggesting that other factors regulate the recruitment of AP180 to endocytic sites (Harel et al., 2008). Although mutation of the known yAP180 clathrin-binding motif did not prevent Snc1 uptake, it remains possible that yAP180 contains additional clathrin binding motifs yet to be identified. Mammalian AP180/CALM contains multiple clathrin binding motifs (Legendre-Guillemin et al., 2004).  Whether the yAP180 clathrin binding mutant actually blocks interaction with clathrin has not been determined, and should be assessed in future studies.   Is yAP180 recruited to sites of internalization through association with proteins other than clathrin and AP-2? AP180 proteins contain binding sites for not only clathrin and AP-2, but also for PI(4,5)P2  (the ANTH domain), and for EH domain motif-containing proteins (NPF motifs) (Maldonado-Báez and Wendland, 2006).  It is therefore possible that yAP180 is recruited by lipid binding, or by EH-domain proteins. Interaction between the AP180 NPF motifs with EH-domain-containing scaffolding proteins seems to be important in mammalian cells: AP180 interacts with the EH-domain proteins eps15 and intersectin.  In yeast, the yAP180 NPF motifs bind to the EH-containing epsins (Ent1 and Ent2), and to yeast homologs of eps15 (Ede1) and intersectin (Pan1) (Maldonado-Báez L, and Wendland, B., 2006; Wendland and Emr, 1998; Aguilar et al., 2003; Miliaras and Wendland, 2004).  These EH domain proteins interact with multiple components of the endocytic machinery, and may be important in AP180 recruitment.  Additionally, Ent1, Ent2, and Ede1 all contain clathrin binding sites, and may therefore link AP180 to clathrin. How could the role of Ent1/2, Ede1, and Pan1 in the recruitment of yAP180 be determined? A first approach could be to investigate whether mutation of the AP180 NPF motifs causes defects in Snc1 internalization using the invertase assay, or microscopy.  If strong defects were observed, this would suggest an important function for association between the AP180 NPF motifs and one or more of these EH-motif containing proteins.   85 Further studies could help determine which of these proteins are important.  This could be accomplished by assessing the effects of mutating the EH-motifs in each of these proteins on Snc1 internalization.  Our screen results demonstrated that ede1∆ mutants have a relatively weak defect in Snc1 internalization, similar to that of the yap1801∆ and yAP1802∆ single mutants.  This demonstrates that Ede1 alone is not likely to be the only requirement for yAP180 recruitment.  Ent1 mutants had an even weaker phenotype, but Ent1 has been shown to be partially redundant with Ent2.  Although ent1∆/ent2∆ mutants are inviable (Wendland et al., 1999), assessment of Snc1 sorting in ent2∆ mutants in combination with a temperature sensitive ENT1 allele could reveal a role for these proteins in AP180 function.  PAN1 is an essential gene and was not assessed in our primary screen. The role of Pan1 could therefore also be assessed through the use of temperature sensitive alleles, overexpression studies, or through mutation of its EH motifs.  If mutation of any of these proteins is found to result in a strong endocytic defect, their effects on yAP180 endocytic patch recruitment could be evaluated by TIRF microscopy.  AP180 recruitment could alternatively be mediated though PI(4,5)P2 binding through its ANTH domain.  A similar strategy could therefore assess the effects of ANTH domain deletion on Snc1 internalization.  Although we may find that individual deletion of the NPF motifs, or the ANTH domain impairs the AP180 Snc1 sorting function, mutation of these domains may not be enough.  Since adaptors bind to multiple components simultaneously for membrane recognition, often mutations in multiple motifs are required to observe recruitment defects (Motley et al., 2006).  Therefore, the combinatorial effects of these mutations on yAP180 recruitment may also need to be assessed by the methods described above. 4.2.3. Role of synaptojanin in yAP180 vesicle un-coating  By screening for additional cargo-specific factors, a requirement for the PI(4,5)P2 lipid phosphatase, synaptojanin (Inp52) was identified. Loss of INP52 resulted in a cargo-specific internalization defect that was similar to the yap1802∆ mutant.  Further work showed that deletion of INP52 caused the accumulation of yAP180 on cytosolic vesicles, likely explaining the similar cargo-specific defect in Snc1 internalization that we observed for both yAP180 and INP52 mutants.    Inp52 has previously been shown to localize to endocytic patches, and to specifically control the dissociation of proteins that bind PI(4,5)P2 through ANTH or ENTH domains, including Sla1, and Ent1/2, respectively (Sun, Y., 2007). The ability of Inp52 to hydrolyze PI(4,5)P2 is important to release these ANTH/ENTH domain proteins from the vesicle,  86 following fission. This led us to propose that the similar cargo-specific defects observed in the absence of either INP52 or yAP180 is a result of failed disassembly of yAP180 from internalized vesicles.  An alternate explanation is that this accumulation is due to inappropriate recruitment of yAP180 to internal compartments.  To distinguish between these possibilities, yAP180-GFP patches could be tracked in inp52∆ mutants by TIRF microscopy.  A similar approach was used to demonstrate that in inp52∆ mutants, Sla2 patches are internalized normally, but that Sla2 remains associated with these vesicles following scission (Sun et al., 2007).  This showed that loss of Inp52 causes prolonged association of Sla2 with endocytic vesicles, and does not cause inappropriate recruitment of Sla2 to internal compartments.  Loss of INP52 did not completely block internalization of Snc1, as it showed a similar defect as a yap1802∆ single mutant, which is considerably weaker than the defect observed in yap1801∆/1802∆ double mutants.  This suggests that Inp52 may be partially redundant, and that other factors may facilitate PI(4,5)P2 hydrolysis in its absence.  In addition to Inp52, yeast expresses the related synaptojanin Inp51, which also localizes to endocytic sites, and Inp53, which is involved in sorting at the TGN (Bensen et al., 2000).  Inp53 is recruited to cortical actin patches under conditions of hyperosmotic stress (Ooms et al., 2000). None of these genes are essential for growth; however a triple deletion of INP51, INP52, and INP53 is lethal (Stolz et al., 1998).  Although loss of Inp52, but not Inp51, has previously been shown to result in the accumulation of ENTH/ANTH domain containing proteins, this could be due to the lower expression level of Inp51 relative to Inp52.  Our results suggest that Inp52 function may be partially substituted by Inp51 and possibly Inp53 for Snc1 internalization.  To investigate this, it could be tested whether combined deletion of INP51/INP52 or INP51/INP53 results in a more severe internalization defect than a single INP52 deletion.  The effect of the triple mutant could also be tested in inp51∆/inp53∆/inp52ts cells at a non-permissive temperature (Stefan et al., 2002).  It will be important to carry out these studies to better understand how AP180 and synaptojanin may function together in higher cells. The synaptojanins are evolutionarily conserved from yeast to humans, and their regulation of PI(4,5)P2 turnover at the cell surface is critical for cellular function, and relevant to human disease (Liu Y, Bankaitis VA, 2010).  Synaptojanin 1 null mice die shortly after birth and present neurological defects and accumulate clathrin-coated vesicles at nerve endings, due to failed disassembly of these coats (Cremona O., 1999, Kim WT., 2002). Interestingly, increased synaptojanin 1 activity is  87 directly associated with the brain dysfunction and cognitive defects manifested in some Down’s sydrome patients.  Synaptojanin1 resides in a genomic region present in trisomic rearrangement in Ts65Dn mice, a model for Down’s syndrome.  In these mice, homoeostasis of PI(4,5)P2 is disrupted.  Restoring the Synaptojanin gene to disomy in these mice is alone is sufficient to correct these altered levels of PI(4,5)P2, and the neurological defects observed in this model (Voronov SV, 2008).  Synaptojanin 2 functions in non-neuronal cells, and its disruption inhibits internalization of the epidermal growth factor and transferrin receptors, and has been shown to disrupt the formation of clathrin coated vesicles in lung carcinoma cells (Hill E., 2001, Malecz N., 2000, Rusk N., 2003).  Although defects in both synaptojanin and AP180 result in coated vesicle accumulation and neurological defects in multiple model organisms, it is unknown if synaptojanin contributes directly to the un- coating of AP180 proteins at the synapse.  The studies in yeast described here, could contribute important insight into the coordinated roles of synaptojanin and AP180 proteins, and guide future studies in mammalian cells. 4.2.4. How does yAP180 recognize Snc1 for internalization?  Another outstanding question regarding yAP180 function is whether it interacts directly with Snc1, or indirectly through additional factors.  An interaction between yAP180 and Snc1 could not be detected in vivo.  This is consistent with other studies, which have generally failed to detect interactions between adaptors and their cargo in vivo, due to their weak and transient nature. Generally, interactions between adaptors and their cargo have been more successful by in vitro methods using recombinant proteins.  An in vitro approach may therefore aid in determining whether yAP180 interacts directly with Snc1, or whether other proteins bridge this interaction.  If an interaction between AP180 and Snc1 were to be identified though these studies, the next step would be to identify the Snc1 sorting signal, as the signal recognized by AP180 has not yet been identified in any organism.   Two cytosolic residues have been defined that are required for internalization of both Snc1 and Vamp2.  In Snc1, mutation of V40A and M43A cause a complete endocytic block (Grote E., 1995, 2000; Lewis et al., 2000).  Although these residues are located on the same face of the amphipathic helix that binds to t-SNAREs, they are not required for SNARE complex assembly or function.  Currently, no sorting adaptor has been shown to bind to this motif.  It is also unknown whether these residues independently mediate internalization, or if they are part of a larger conformational epitope required for recognition by AP180 or other adaptors.    88  Whether the V40M43A mutation blocks the interaction between Snc1 and AP180 could be tested in vitro.  An alternate approach would be to identify putative Snc1 sorting signals by error-prone PCR to introduce random mutations in its cytosolic domain.  The effects of these mutations on Snc1 internalization could be tested systematically using our GSS invertase assay.  If candidate endocytic mutants are identified, they could then be tested individually for binding to yAP180 in vitro.  If a non-continuous set of mutations is found to block internalization, this could suggest that Snc1 is recognized by a conformational epitope.  To further investigate this, structural studies, like those carried out to determine the interaction surface of the SNARE Vti1 recognized by the epsin adaptor, would likely be required.   Currently, there is no evidence from our studies, or those of others, that yAP180 binds directly to Snc1; it is possible that other proteins could bridge this interaction.  yAP180 interacts with multiple endocytic proteins, as previously discussed.  It would therefore be useful to test if deletion of yAP180 binding partners, such as the epsins, blocks its interaction with Snc1.  A larger scale approach could also be used to identify binding partners of the Snc1 endocytic signal in vitro.  For example, total cell lysates could be passed through a GST-Snc1 column, and the purified components separated by SDS-PAGE.  The identity of each co-purifying protein could be identified by mass spectroscopy.  To identify proteins that bind to the endocytic signal, the profiles of binding partners could be compared between GST-Snc1 and GST-Snc1V40M43A mutant.  For example, if a protein is present in the WT, but not the mutant purification, it may be a candidate bridging protein. A similar approach was recently used to identify and compare the profiles of effectors for all 60 mammalian Rab proteins (Kanno et al., 2010). 4.2.5. Does AP-2 mediate endocytosis in yeast?  A requirement for AP-2 in yeast endocytosis has not yet been identified, in contrast to the essential role for this complex in mammalian endocytosis. Targeted disruption of AP-2 leads to embryonic lethality in mice (Mitsunari T, 2005), and has been shown to block the uptake of multiple cargo including the transferrin receptor (Conner, S. D., and S. L. Schmid. 2003), as well as a population of lysosome-associated membrane proteins that traffic via the plasma membrane (Janvier and Bonifacino, 2005). Yeast AP-2 deletion mutants, however, are viable, and have no clear defects in the internalization of commonly studied endocytic cargo.  This has led to the suggestion that AP-2 is unimportant for endocytosis in yeast (Sorkin, 2004; Yeung et al., 1999).  Could considering a broader range of cargo help us  89 identify an endocytic role for AP-2?  One recent study has shown that AP-2 also shows cargo-specific internalization defects, which may serve to explain this discrepancy.  A large-scale screen demonstrated that mutants lacking any of the four AP-2 subunits are resistant to K28, a virally encoded yeast killer toxin that enters the cells via endocytosis by binding to its unidentified receptor.  AP-2 mutants have a strong defect in uptake of K28 from the media, but do not affect the uptake of other endocytic markers, including the peptide cargo α-factor and of the lipophilic dye FM4-64 (Carroll et al., 2006). The authors thus proposed that AP-2 has a strong but cargo-specific effect on K28 endocytosis. This study also showed that AP-2 is recruited to endocytic sites concurrent with clathrin and other early coat components, suggesting that it likely has a direct role in uptake.    In contrast to what was previously believed, both this study and our screen for regulators of Snc1 internalization demonstrate that clathin and its associated adaptors are important in both yeast and mammalian cells.  Our understanding of these similarities has only become clear through the study of cargo proteins that have not been previously studied by genome-wide methods in yeast.  Further large-scale functional screens using additional non-conventional cargo will aid in the identification of proteins recognized by AP-2 and cargo-specific adaptors, and of new adaptor-related proteins required for internalization.   4.2.6. Role of actin and its regulators in Snc1 internalization  The results from our screen re-enforced the importance of dynamic actin regulation in the yeast endocytic process.  We identified multiple regulators of the actin cytoskeleton, for which no endocytic defects have previously been shown.  Abp1 and Crn1 are actin- binding proteins, and promote the activity of the Arp2/3 complex, a key regulator of actin polymerization.  The actin capping proteins Cap1/2 are thought to function in polymerization by limiting monomer addition to recently assembled ends, and increasing local polymerization rates (Kim K., 2004; 1990; Kaksonen M., 2005). We also identified a novel regulator of actin dynamics, Ldb17, and demonstrated that it is an important link between cargo selection and the regulation of actin polymerization.  The absence of Ldb17 resulted in defects in both vesicle internalization and actin morphology.  The mechanism by which Ldb17 promotes actin polymerization, however, is currently undefined.    Does Ldb17 promote actin polymerization through direct regulation of the Arp2/3 complex, or does it function indirectly in this regulation?  Like Ldb17, its mammalian  90 homolog, SPIN90, interacts with multiple components of the vesicle coat, and with the actin regulatory machinery.  SPIN90 has been proposed to carry out a similar role as Ldb17, linking coat and actin dynamics (Kim et al., 2005, 2006 (1), 2007, 2009).  SPIN90 stimulates actin polymerization both directly and indirectly, through binding to components of the Arp2/3 complex, as well as to its activators, including N-WASP (Kim et al., 2006; Lee et al., 2006).  The results of this study suggest that Ldb17 does not likely have a direct effect in Arp2/3 regulation.  Ldb17 did not bind to Las17, the yeast homolog of N-WASP or the Arp2/3 complex, likely because the regions important for binding to N-WASP and Arp2/3 in SPIN90 are only partially conserved in Ldb17.  This suggests that Ldb17 interacts with additional regulators to stimulate actin polymerization in yeast.  Interestingly, interactions were identified between the Ldb17 PRD with the SH3 domain-containing proteins Sla1, Lsb3, and Lsb4.  These proteins bind to Las17, and are important in stimulating actin polymerization.  Additionally, the PRD of Ldb17 interacts with the SH3 domain of Bzz1, the yeast syndapin homolog, and this interaction is required for membrane release of Ldb17.  Bzz1 interacts directly with Las17 via its SH3 domain, and with other components of the actin polymerization machinery (Soulard et al., 2002 and 2005).  These factors could thus be important in forming a link between Ldb17 and Arp2/3 regulation.  Whether Ldb17 can promote actin polymerization and the requirement for its interacting factors in this process could be assessed in future studies. The role for actin polymerization factors is often tested in vitro, and there are a variety of commercially available in vitro actin polymerization assays.  One of these assays is based on the enhanced fluorescence of pyrene-conjugated actin that occurs during polymerization, which can be detected using fluorimetry (Blader et al., 1999).  In this assay, purified Ldb17 could be added to the reaction mixture in the presence of Arp2/3, to determine if it has a direct effect on actin polymerization.  Ldb17 could also influence actin polymerization indirectly, through its association with Bzz1, Sla1, or Lsb3/4, which could be tested by addition of these factors in combination with Ldb17.  91 Yeast is an important model for understanding protein sorting in higher cells, and the underlying mechanisms that govern vesicle formation are generally well conserved. Our work and that of other groups has provided explanations for some of the apparent discrepancies between endocytic processes in yeast and man. This study has highlighted that specific mechanisms are in place for the endocytosis of different cargo proteins, which is true in both mammalian and yeast systems.  Each internalization pathway shows distinct requirements for clathrin, actin regulators, and lipids, and the use of these distinct pathways may also change in response to the context of the cellular environment.  Different cell types in mammals also appear to use specialized sorting mechanisms to suit their specific functions.  Elucidating the unique and conserved features of these processes will be essential in understanding the fundamental principles that underlie cargo selection, membrane deformation, and vesicle scission in all organisms and cell types. 4.3. Regulators of Snc1 recycling: AP-1R and Ima1  4.3.1. What is the role of AP-1R in Golgi/endosomal recycling?  In addition to the clathrin adaptor AP180, we identified a requirement for the alternate AP-1 isoform, AP-1R in Snc1 transport.  In contrast to the endocytic role of yAP180, AP-1R is involved in the intracellular recycling of Snc1.  Deletion of AP-1R components leads to a weak, yet reproducible increase in cell-surface localized Snc1.  Based on its co-localization with intracellular clathrin, and Golgi/endosomal markers, we have concluded that AP-1R likely functions in Snc1 intracellular recycling, and not in endocytosis.  How does loss of AP-1R lead to increased levels of Snc1 at the surface?  As all trafficking pathways in the cell are part of a network, and their interconnected nature allows cargo to follow alternate “bypass” routes, the increase in cell surface levels suggests that deletion of AP-1R allows Snc1 to transit to the plasma membrane by an alternate recycling bypass pathway, with faster recycling kinetics than the normal route.  We considered different mechanisms by which this might occur, which are discussed below and shown in illustrations 4.2 and 4.3.     92 Model 1: AP-1R mediates sorting to an intermediate compartment prior to surface delivery.  In this first model (Illustration 4.2), AP-1R is present on endosomes, and promotes Snc1 recycling at these compartments.  The recycling pathway regulated by AP-1R may be a ‘slow’ route, whereby AP-1R may transport Snc1 from endosomes to either the Golgi, or perhaps another intermediate compartment prior to cell surface delivery.  In the absence of AP-1R, Snc1 may be diverted along to a more rapid and direct recycling route, in which it bypasses the Golgi/intermediate compartment, and is recycled directly from endosomes.  As discussed in chapter 3, this bypass ability has been observed for other recycling cargo in yeast, including Chs3, which is able to recycle directly to the cell surface from early endosomes or the Golgi in the absence of AP-1 (Valdivia et al., 2002).  In mammalian cells, there are at least two main types of recycling pathways to the cell surface, each of which has different kinetics.  The rapid recycling route mediates transport of cargo such back to the plasma membrane from either early endosomes or an earlier stage in the endocytic pathway.  The so-called slow recycling route transports cargo from the early endosome to an intermediate endocytic recycling compartment (ERC), before re- delivery to the plasma membrane.  Kinetic studies measuring the recycling rates of the transferrin receptor (TfR) show that it follows both pathways.  Whether TfR follows the fast or slow pathway appears to be determined largely at the early endosome.  This endosomal compartment contains several Rab GTPases, including Rab4 and Rab5.  For TfR to undergo fast recycling, it must be quickly sorted away from Rab5, into a specialized Rab4-containing microdomain on the early endosome.  These GTPases likely recruit different regulators that sort cargo either directly back to the cell surface or to the recycling endosome (Grant and Donaldson, 2009).  The characterization of the mammalian endocytic system raises important questions about the nature of endosomal organization in yeast.  Currently, it is not clear whether yeast have kinetically distinct recycling pathways, or different populations of endosomes like those in mammals.  The current view of protein recycling in yeast is much simpler, in that cargo is thought to pass only through one type of endosome, and is returned to the plasma membrane following direct retrieval to the Golgi.  Furthermore, it is not known whether the early endosome contains distinct microdomains that are important for directing proteins to different locations.  Differential inclusion of AP-1 and AP-1R into distinct microdomains of a common membrane would be consistent with the overlap of these complexes at endosomal  93 compartments, and could thus explain their different sorting function.    Snc1 has previously been shown to recycle to the plasma membrane through bypass pathways in the absence of components required for it normal recycling itinerary. Mutation of certain components of the COPI B coat (sec27-1 and sec28), for example, results in increased surface levels of GFP-Snc1, and enrichment at bud sites.  This implies that Snc1 retrieval and recycling through early endosomes to the Golgi may require COP1B (Robinson et al. 2006), and that loss of this complex results in retargeting of Snc1 to the plasma membrane.  Despite the established role of the COPI coat in intra-Golgi and Golgi-ER retrograde transport, studies in both yeast and mammalian cells also describe a post-Golgi transport role for COPI (Whitney et al., 1995; Aniento et al., 1996; Gu and Gruenberg, 2000; Faure et al., 2004).  It would be interesting to test the relationship between AP-1R and COP1B in Snc1 intracellular recycling.  Although most components of this coat are essential, and therefore would not have been present in our screen, a strong requirement was identified for Sec28, the only non-essential COP1B component.  Genetic interaction studies between AP-1R and COPIB components could be used to determine whether they work in the same or parallel recycling pathways.  Snc1 surface levels could be compared in double mutant AP-1R/COP1B strains, using the invertase assay, but would require the use of temperature-sensitive alleles of most COP1B components. Model 2: AP-1R sorts Snc1 into a specific class of secretory vesicles  In contrast to an endosomal sorting role, AP-1R may function at the Golgi, and mediate inclusion of Snc1 into secretory vesicles (Illustration 4.3). There are two populations of vesicles that are targeted to the plasma membrane in yeast, each of which is enriched for distinct cargo.  As these vesicles have distinct densities (dense and light), they can be distinguished based on subcellular gradient separation in sec6∆ mutants, which prevent their fusion with the plasma membrane.  Snc1 is normally contained in the lighter vesicle fraction, as is the SNARE Tlg1, which partners with Snc1 in the fusion of vesicles derived from early endosomes with the Golgi (Harsay E., and Bretscher A., 1995). AP-1 is involved in the sorting of cargo into the light fraction, and in the absence of AP-1, both Chs3 and Tlg1 are missorted from the light to the dense fraction (Valdivia et al., 2002).   It would be interesting to test whether AP-1R is required for Snc1 incorporation into light vesicles, which could be done by determining if deletion of AP-1R shifts the incorporation of Snc1 from the light to the dense exocytic vesicle population by subcellular fractionation.  How  94 can this model explain the increased levels of Snc1 in the absence of AP-1R?  This could occur if the dense vesicle fraction can carry relatively more cargo than the light fraction over a given time frame.  Dense vesicles may have faster kinetics of transport.  One way that this could occur is if dense vesicles are transported directly to the cell surface, while light vesicles require an intermediate transport through endosomes prior to cell surface delivery. Alternatively, dense and light vesicles could both arise from the Golgi: dense vesicles, however, could carry a higher concentration of cargo, have or have higher fusion efficiency at the cell surface than the lighter fraction. Model 3: AP-1R has indirect effects on Snc1 recycling   Although localization studies suggest a role for AP-1R at Golgi/endosomal compartments, this is not sufficient to conclude that AP-1R has a direct role in Snc1 intracellular recycling.  Indirect effects resulting in increased Snc1 surface levels could reflect a variety of indirect mechanisms. For example, a partial defect in endocytosis could be a result of the mislocalization of a component required for Snc1 internalization in the absence of AP-1R.   It is also possible that the total cellular levels of Snc1 are increased in AP-1R mutants. Deletion of AP-1R may lead to either increased transcription or decreased degradation of Snc1.  These indirect effects should be considered in future studies.  4.3.2. What is the Snc1 recycling signal recognized by AP-1R?  In this study, an interaction between AP-1R and GST-Snc1 was identified vitro, but the Snc1 signal recognized by AP-1R for recycling remains to be determined.  Whether AP-1R recognizes Snc1 directly or indirectly is also unknown.   Like the signal required for Snc1 endocytosis the Snc1 recycling signal could be a yet unrecognized short cytosolic motif or a conformational epitope, consisting of a combination of folded residues.  Furthermore, Snc1 is both palmitoylated and ubiquitinated, post- translational modifications that have been found to affect the sorting of multiple other SNARE proteins (Valdez-Taubas and Pelham; He and Linder, 2009).  It is unlikely that the Snc1 sorting signal is a post translational modification, however, as the GST-Snc1 construct used for our in vitro assay was isolated from E. Coli, which lacks the machinery required for these modifications.  This suggests that the Snc1 sorting signal is likely an intrinsic part of the Snc1 cytosolic domain. To identify residues in Snc1 that are important for AP-1R recognition, alanine-scanning mutagenesis could be used to systematically replace regions of Snc1 with alanine.  The effects of these mutations on preventing the interaction between Apm2 and Snc1 could then be tested in vitro.    95  It will also be important to determine whether the interaction between Apm2 and Snc1 is direct or indirect.  The identification of a putative Snc1 recycling signal could help resolve this.  To identify potential bridging proteins, for example, the co-purification profiles of GST-tagged WT Snc1 vs. Snc1 containing a mutated recycling signal could be compared by mass spectroscopy.  An outstanding question in the field is whether Snc1 is transported as part of a trans or cis-SNARE complex.  It is possible that Apm2 may bind to other SNAREs in complex with Snc1 at the Golgi/endosomes, including the functionally redundant t-SNAREs Tlg1 and Tlg2.  Our in vitro Snc1 binding assay could be used to determine if Tlg1/2 is also present in the pulldown between Snc1 and Apm2, by blotting with anti-Tlg1 antibodies.  If this is found to be the case, it could be interesting to test whether Snc1 and Tlg need to be in a SNARE complex to bind Apm2.  Snc1 and Tlg interact though critical residues in their SNARE domain.  While Snc1 provides an arginine residue, Tlg1/2 provide a glatamine.  Mutation of either the Snc1 arginine or the Tlg glutamine prevents assembly of these proteins.  Our in vitro assay could therefore be used to determine if Snc1 binding to Apm2 is prevented in a TlgQ>A mutant strain, and if mutation of the Snc1 arginine shows the same effects.  If these mutations prevent interaction between Apm2 and Snc1, this would provide evidence that AP-1R sorts Snc1 as part of a trans-SNARE complex. 4.3.3. How do AP-1 and AP-1R regulate distinct sorting pathways?  As AP-1 and AP-1R show considerable co-localization to Golgi/endosomal compartments, it is unclear how they mediate largely non-overlapping transport functions.  In mammalian cells, AP-1A localizes to the TGN, wheras AP-1B localizes to the perinuclear recycling endosomes, adjacent to the TGN. This is not clearly the case for AP-1 and AP-1R in yeast, although, they may localize to slightly different membrane domains.  Studies in mammalian cells suggest that exchange of the medium subunit may confer alternate specificity to AP-1A and AP-1B by providing a novel interaction surface, which is able to associate with distinct sets of lipids and also with regulatory proteins.  AP- 1B specifically facilitates the recruitment of exocyst subunits Exo70 and Sec8, which mediate tethering and fusion from recycling endosomes to the cell surface (Fölsch et al., 2003).  The SNARE protein cellubrevin has also recently been shown to be required for AP- 1B-dependent sorting, and co-localizes with AP-1B within recycling endosomes (Fields et al., 2007).    96 Although these alternate complexes are not analogous to AP-1 and AP-1R in yeast based strictly on homology, important insights about the differential functions of AP-1 and AP-1R may be gained from these mammalian studies.  Apm2 is considerably larger than Apm1, and is only 30% identical on the amino acid level.  Inclusion of Apm2 therefore may confer alternate specificity to AP-1 through facilitating differential interaction with regulators, including Ima1, and possibly different membrane lipids. These ideas are expanded upon in the following sections. 4.3.4. Do AP-1 and AP-1R localize to different lipid domains?  Although we found that Apm1 and Apm2 show considerable overlap at Golgi/endosomal compartments, this overlap was not complete.  This could suggest that AP- 1R mediates Snc1 transport at these unique sites, or that the localization of these complexes may be more different than can be appreciated based on the resolution of techniques used in this study.  The differential localization of mammalian AP-1A and AP-1B has been at least explained by the differential preferences of the medium subunits for membrane lipids.  While 1A binds the Golgi-enriched PI(4)P, 1B binds PI(3,4,5)P3, enriched in recycling endosomes.  Interestingly, a patch of only three amino acids within the 1B C-terminal B domain was found to be necessary for its recruitment to recycling endosomes.  Switching this patch with the analogous residues of 1A both inhibited the ability for AP-1B to localize to recycling endosomes, and resulted in the mis-targeting of AP-1B-dependent cargo.  This suggests that differences in the lipid binding domains of these similar  subunits are important for their differential targeting and sorting function (Fields et al., 2010).    The analogous regions in Apm1 and Apm2 differ substantially, suggesting that this site may contribute to the distinct sorting functions of AP-1 and AP-1R.  This may also be explained by the ability of this region in Apm2 to associate with specific phospholipid domains.  In the future, it would be interesting to determine whether AP-1 and AP-1R localize to slightly different Golgi/endosomal sub-domains.  These studies will rely on a better understanding of membrane domains and their corresponding lipids within these compartments in yeast.  Powerful microscopy techniques and novel assays to detect these small-scale localization differences will likely be required.  It could, however, be investigated whether replacing these residues in Apm2 with the analogous residues in Apm1 result in the mis-sorting of Snc1.  If this is the case, this would be evidence that these complexes may be differentially targeted, by analogy to the mammalian AP-1 complexes.  97 4.3.5. Ima1 is a putative enzyme and binds the Apm2 C-terminal domain This study demonstrated that AP-1 and AP-1R participate in differential regulatory interactions, and the previously uncharacterized protein Ima1 was identified as a specific regulator of AP-1R.  Deletion of IMA1, which shares a similar genetic interaction profile with AP-1R components, also resulted in increased Snc1 surface levels.  Furthermore, Ima1 binds specifically to AP-1R vs. AP-1, and co-localizes to similar intracellular compartments.   Ima1 is not critical for the early steps of AP-1R vesicle formation, including membrane recruitment or cargo binding.   It may act at a later stage of AP function, possibly as a mediator of vesicle formation, or AP-1R un-coating.   As Apm2 has previously been shown to co-fractionate with clathrin-coated vesicles by gel filtration (Stepp et al., 1995), the role of Ima1 in Apm2 vesicle inclusion could be tested by this method.  This would involve comparing the quantity of Apm2 included in vesicles in the presence or absence of Ima1.  Decreased abundance of Apm2 vesicles in ima1∆ cells would provide evidence for a role for Ima1 in Apm2 vesicle formation.  Conversely, an increased abundance of these vesicles would suggest a role for Ima1 in AP-1R vesicle dissociation. An interesting finding is that Ima1 interacts with the Apm2 C-terminus, but not through the Apm2 tyrosine-binding pocket (subdomain A).  Rather, it binds to subdomain B, which has been shown by recent studies to associate with membrane lipids lipids and may be a target of regulatory interactions (Fields et al., 2010; Owen and Evans, 1998; Heldwein et al., 2004).  Evidence was provided that Ima1 may have enzymatic function related to AP- 1R function. The Ima1 C-terminal domain is remarkably conserved among eukaryotes, and contains a putative enzymatic motif, which is characteristic of serine hydrolases.  The Ima1 catalytic mutant failed to complement Snc1 surface levels in ima1∆ cells, suggesting that this motif may have catalytic activity required for AP-1R-mediated sorting.  Subcellular fractionation revealed that this enzymatic domain is not integral to the membrane, as predicted.  Together with the finding that the Ima1 N-terminal region binds to Apm2, it is conceivable that the Ima1 C-terminal enzymatic domain may be accessible to its substrates at sites of AP-1R function.  The finding that Ima1 is a candidate enzyme that binds to the Apm2 B-domain is interesting, as recent studies in mammalian cells have shown that the  subunit is an important target of regulation.  These studies are changing the canonical view of  subunit function, in which their primary role is to bind tyrosine-based cargo.  Interaction between the  subunit and specific lipids and lipid-regulatory enzymes is one recurrent theme of  98 these studies.  While some of these regulatory enzymes bind to the tyrosine cargo-binding site in a canonical manner, others bind to regions that are distinct from this site, like Ima1.  Interestingly, the subdomain B has been shown to regulate some of these interactions.  For example, differences in the B domain of AP-1A 1 and AP-1B 2 confer differential localization of these complexes in polarized cells (Fields et al., 2010).  Understanding the mechanisms by which these -binding proteins regulate AP function could thus inform us how Ima1 may contribute to AP-1R sorting, and how we can best direct future experiments to identify this role.  These mechanisms are reviewed below. AP complexes – Interactions with lipids and lipid-regulatory enzymes AP complexes can influence lipid metabolism, and can specifically participate in the generation of lipids that recruit them to their target membranes, through interaction with lipid regulatory enzymes.  APs and lipid regulators have been shown to interact in positive feedback loops; binding of an enzyme to its target AP has been shown to stimulate enzymatic activity, which can result in the localized generation of phospholipids (Fields et al., 2010; Kahlfeldt et al., 2010).  In turn, the increased lipids generated through this binding leads to further AP recruitment and membrane stabilization. The  subunit appears to be an important target for these interactions, and multiple  subunits have now been shown to bind lipid kinases.  PI(3,4,5)P3 enrichment at recycling endosomes is required for recruitment of AP-1B.  In turn, PI(3,4,5)P3 accumulation is dependent on the recruitment of the lipid  kinase PIPKI-p90 to recycling endosomes by AP-1B (Fields et al., 2010).  PIPKI- p90 interacts directly with 1B via a tyrosine-based motif, and this interaction stimulates the kinase activity of the enzyme.  Furthermore, -binding enzymes can have additional roles in AP regulation.  PIPKI-p90, for example, also binds to E-cadherin, an AP-1B-specific cargo.  The dual interaction supports that PIPK serves as both a scaffold, linking E-cadherin to AP-complexes, and a regulator of spatially restricted lipid generation (Ling et al., 2007). PIPKI-p90 also binds directly to AP-2 2, and is required for the generation of PI(4,5)P2 during endocytosis (Bairstow et al, 2006; Krauss et al., 2006).  The mechanism of this interaction is unclear.  One study has suggested that PIPKI-p90 interacts with the cargo- binding pocket of 2 through a tyrosine motif (Bairstow et al, 2006).  In contrast, a second study has shown that this interaction is not dependent on the tyrosine motif, and may therefore involve a site of 2 that does not include the cargo-binding pocket (Krauss et al., 2006).  Endocytic cargo protein binding to 2 leads to a potent stimulation of PIPK activity. These data thus identify a positive feedback loop consisting of endocytic cargo proteins, AP- 99 2µ, and PIPK type I, which may provide a specific pool of PI(4,5)P2 dedicated to clathrin/AP- 2-dependent receptor internalization. The mechanism by which binding of PIPKI to the  subunit stimulates its kinase activity remains to be determined.   The AP-2  subunit has also recently been shown to interact directly with phospholipase D (PLD1), a receptor-associated signaling protein and this facilitates the membrane recruitment of AP2 and the endocytosis of epidermal growth factor receptor (EGFR).  PLD catalyzes the hydrolysis of phosphatidylcholine (PC) to choline and phosphatidic acid (PA) (Lee et al., 2009).  Interestingly, like Ima1, PLD is also a serine hydrolase. The PLD1-2 interaction requires the binding of PLD1 with phosphatidic acid, its own product.  A model was proposed, in which auto-regulatory interactions beween PLD1 and PA promote 2 binding, which subsequently facilitates EGFR endocytosis in response to receptor activation. It has been hypothesized that PA, in turn, stimulates a phosphoinositide kinase to generate PI(4,5)P2 at the plasma membrane.  It was therefore suggested that PA generation by PLD1 activation is a key molecular event that causes the local accumulation of PI(4,5)P2 through direct activation of a kinase and enhancing the AP-2/kinase pathway by placing these two molecules in close proximity to facilitate EGFR endocytosis.    Members of the Dishevelled family of proteins have been found to bind directly to AP- 2 2 in both mammals and C. elegans.   Dishevelled (Dvl) functions as an adaptor between AP-2 and other components of the Wnt signaling pathway.  This interaction is required for internalization of the Wnt signaling protein Frizzled.  The interaction between Dvl and AP2  is bipartite, and requires simultaneous association of the Dvl DEP domain and a tyrosine- based signal.  The tyrosine-based signal interacts with the 2 cargo binding pocket, while the DEP domain binds at one end of the elongated, C-terminal domain of 2. This domain:domain interface further reinforces that parts of the 2 surface distinct from the tyrosine-motif pocket can help recruit specific receptors or adaptors into a clathrin coated pit.   It is also considered likely that other parts of this surface may also have partners, as yet unidentified. The incorporation of two interaction modes into one cargo molecule further suggests that combinatorial recognition (and combinatorial cargo addressing) may be more widespread than previously suspected (Yu et al., 2007 and 2010).  Wnt signaling stimulates the production of PI(4,5)P2 through Frizzled and Dvl, which activates the lipid kinases phosphoinositide kinases 4 and 5. (MacDonald et al., 2009; Qin et al., 2009). This further supports the direct role for lipids and lipid-regulatory enzymes in driving the membrane recruitment and function of AP complexes.  100 4.3.6. Is Ima1 important for the generation of lipids required for AP-1R function?  What is the enzymatic function of Ima1, and could it regulate the generation of lipids important in AP-1R-mediated sorting?  The finding that Ima1 binds to the Apm2 B domain suggests this possibility, in light of the work described in the previous section.  The serine hydrolase family includes many proteins that can influence lipid metabolism, including esterases and lipases.  Confirming that Ima1 is a serine hydrolase and identifying its potential substrates could help elucidate how it contributes to AP-1R function.  Experimental strategies to dissect its enzymatic function are discussed below.  The first step will be to verify that Ima1 is a serine hydrolase, as predicted based on homology.  To address this central question, we can take advantage of a chemical strategy referred to as activity-based protein profiling (ABPP) that uses active site-directed probes to profile the functional state of enzymes. ABPP probes label active enzymes by binding covalently to the active site.  They bind enzymes only in their active state, but not their inactive precursor or inhibitor-bound forms.  ABPP probes remain covalently bound to the active site, and in this way impede catalytic activity.  These probes contain a tag or label, such as biotinylation, providing a means to detect them (Barglow and Cravatt, 2007; Heal et al., 2011). Fluorophosphonate (FP) probes have been developed that target active serine hydrolases (Simon and Cravatt., 2010). In order to determine if Ima1 is a serine hydrolase, the FP probe would be added to cell lysates.  Ima1 would then be affinity purified, and western blotting would be carried out to determine if the probe was incorporated by detection with anti-biotin.  As the probe only labels active enzymes, we could test whether mutation of the potential catalytic residues prevents probe incorporation.    Other questions that could be addressed by ABPP are whether AP-1R binds the active or inactive form of Ima1, and whether binding to AP-1R stimulates Ima1 enzymatic activity. Since FP probes inhibit enzymatic activity, whether Apm2 preferentially co- immunoprecipitates with the labeled or non-labeled form of Ima1 could be investigated. Whether binding to AP-1R stimulates Ima1 enzymatic activity could also be evaluated, by comparing the amount of probe that is incorporated into Ima1 upon deletion or over- expression of APM2.   4.3.7. Determination of Ima1 substrates  If Ima1 were confirmed to be a serine hydrolase by the studies described above, it would next be important to identify its biologically relevant substrate. Serine hydrolases comprise a large class of enzymes, incuding proteases, esterases, lipases, peptidases, and  101 aminases, and therefore have diverse substrate specificity.   In recent years high-throughput screening assays have been developed to identify substrates of hydrolytic enzymes.  The majority of these assays are based on screening an enzyme in question against a library of structurally diverse synthetic substrates.  Upon reaction with the enzyme, its substrates release a colored or fluorescent product, permitting their identification.  Many of these substrates are now commercially available, and can be tested in parallel in 96-well microtiter plates.  This method, called enzyme activity fingerprinting (Reymond, 2008), has been used to classify different types of enzymes, including lipases, proteases, and peptidases, and to differentiate between closely related enzymes within these groups (Wahler et al., 2002; Konarzycka-Bessler and Bornscheuer, 2003). By screening a diverse library of these compounds in the presence of Ima1, we may be able to refine the class of enzyme to which Ima1 belongs, by identifying which of these substrates it reacts with.  This could help us to identify potentially biologically relevant substrates.  By doing so, we may be able to decipher whether Ima1 has a role in the remodeling of lipid membranes, and which lipids are potential substrates.  This would be beneficial in understanding the role of lipid regulation in endosomal sorting, and could help us formulate directed hypotheses about how Ima1 activity may regulate the AP-1R sorting pathway.  4.3.8. Investigating the role of TMC04 in higher cells  Identifying the enzymatic activity and substrates of Ima1 could help us understand the potential role of its mammalian homolog TMCO4.  Like most other mammalian serine hydrolases, the role of TMCO4 remains uncharacterized. Although serine hydrolases make up 1% of the mammalian proteome, nearly half of them remain completely uncharacterized with respect to substrates and functions.  Of the enzymes that have been characterized, many have been shown to have important biological functions.  They are important targets of several pharmaceutical agents, including proteases involved in the coagulation cascade, and amidases required for the metabolism of signaling molecules.  Widely used drugs targeted against specific human serine hydrolases include Angiomax for cardiovascular disease, Xenical for obesity, and Aricept and Cognex for Alzheimer’s disease, as well as drugs in development for diabetes, arthritis, and cancer (Baxter et al., 2004).  It is of great interest in the field to gain a more complete understanding of these enzymes, and our work on Ima1 may contribute important insight into the function of TMCO4. One perplexing issue is that while Ima1 is highly conserved in all organisms, Apm2 is not.  Apm2 is unique as a medium chain, as it is considerably larger than, and shares only  102 30% homology to other  subunits.  This may suggest that although AP-1R is not conserved strictly based on similarity, it may carry out an analogous role to an AP complex in higher cells.  Alternatively, Ima1 may have evolved to carry out function unrelated to AP-mediated sorting in multi-cellular organisms.  To investigate these possibilities, methods such as mass spectroscopy could be used to identify TMCO4-interacting factors in mammalian cells.  A more directed approach could also be used to determine if Ima1 interacts with specific AP complex components by co-immunoprecipitation. 4.4. Genetic interaction profiling to identify complexes and pathways required for Snc1 transport 4.4.1. Phenotypic profiling and the construction of genetic interaction networks Genetic interaction profiling was used to screen the top candidates from the primary screen against a panel of query mutants in multiple trafficking pathways.  This analysis allowed these candidates to be classified based on shared genetic interactions with these query genes, and enabled discovery of a set of genes enriched for functions in Snc1 endocytic transport.   In this case, the cell surface levels of the GSS reporter in each double mutant served as a quantitative phenotypic readout.  These results re-enforce the power of genetic interaction profiling in identifying genes that are highly influential to a given biological process after performing a genomic screen, and how these genes are interrelated. Many previous studies have used genetic interaction profiling to infer functional relationships between genes required for a given process (reviewed in Boone et al., 2007). In the vast majority of these studies, however, growth is used as a phenotypic readout.  The resulting networks from these studies therefore leave out processes that have no effect on cell viability or growth (Dixon et al., 2009). The quantitative nature of our assay was beneficial in overcoming this limitation, allowing for more precise determination of phenotypes directly related to Snc1 transport, and the accurate assessment of their genetic relationships.  This study took advantage of recent advances in technology, which have made it possible to measure large numbers of genetic interactions systematically and in parallel (Dixon et al., 2009).   An E-Mapping approach was used to determine the genetic interaction profile between the top candidates from the primary screen, and a selected panel of mutants representing a variety of intracellular transport pathways, instead of the whole genome. This approach has several advantages beyond decreasing the number of  103 interactions that require analysis.  It also increases the signal to noise ratio because the frequency of genetic interactions is higher between genes acting in related pathways, and provides a richer set of patterns for analysis.  In previous studies, this subset of genes has been selected based on multiple criteria, including shared protein localization (Schuldiner et al., 2005), or protein-protein interaction data (Collins et al., 2007).  This selection process has multiple limitations.  Selecting genes based purely on either of these criteria would miss important regulatory factors, such as signaling proteins, which may mediate strong effects on spatially distant processes.  As large-scale protein interaction data suffers from a high degree of false positive and false negative interactions (Szilágyi et al., 2005), starting with this dataset may miss important factors, or may include factors that are not relevant to the process in question. For example, the interactions found in two independent genome-wide Y2H studies in S. cerevisiae show little overlap and are estimated to have a 50% false- positive rate (von Mering et al., 2002; Ito et al., 2001). We took advantage of the E-Mapping approach to investigate the profile of genetic interactions of our top candidates, in combination with a panel of query mutants with established function in diverse intracellular transport pathways.  In our approach, we selected our gene set based on a sensitive and quantitative assay.  By selecting our gene set based on this criteria, we avoided many of the limitations that have been observed in other less stringent methods such as protein localization or interaction data.  Furthermore, an integrative approach, which incorporated both genetic and physical interaction data, was used to refine the network of genes important for regulating Snc1 surface levels into discrete complexes and pathways.  Integration of multiple data sets have generally been shown to add to the confidence of inferred related functions, and reduce the noise associated with individual genome-scale approaches.  By using this integrative approach, we were able to conceive strong hypotheses about the function of uncharacterized genes, based on both a shared genetic interaction profile, and physical interaction with other well- studied genes.   Despite the insight generated by this study, this screening approach had important limitations.  First, there could have been errors in the deletion collections.  It is widely known that these mutant arrays are subject to genetic changes as a result of manipulation and selective pressure, including aneuploidy and second site mutations (Rancati et al., 2008; Yuen et al., 2007).  As a multi-step selection process was required to generate double mutants for the interaction analysis, undesired mutations and rearrangements could have  104 been introduced.  This would lead to false interpretation of the phenotypic data for some of these genes.  A gene involved in Snc1 transport could have been missed, for example, if a second site mutation suppressed the defect caused by deletion of the gene in question (false negative).  A gene with no role in this process could also be falsely interpreted to perturb this process if a second site mutation occurs in a functionally relevant gene (false positive).  Screening two independent genome wide collections and averaging the results for both helped address this issue.  Furthermore, many candidates were also verified by independent knockout or complementation. 4.4.2. Endocytic processes are part of a broader cellular context  The systems-level approach allowed us to identify factors involved in Snc1 endocytic recycling, and also to determine how these factors are interrelated in a broad cellular context.  This work revealed surprising diversity among the processes involved.  In addition to cellular transport, we identified proteins involved in roles including signaling, chromatin modification, transcription and translation, and lipid regulation.   The role of some of these components can be readily explained by the current knowledge of the regulation of intracellular transport pathways, such as the critical role of actin polymerization and phospholipid distribution.  We identified a strong requirement for the cytosolic prefoldin-GimC complex, which acts as a co-chaperone in actin folding (Siegers et al., 1999).  Some of the transcripional/translational factors identified regulate the expression of specific phospholipid species known to be important for endocytic processes Ikeda et al., 2008). Some identified genes, however, have molecular functions that are not immediately reconcilable with membrane trafficking, including various signaling proteins.  Recent studies have uncovered a wealth of evidence that endocytic transport and signaling are deeply integrated in the cellular program, and that these processes are closely connected.  (Scita and Di Fiore, 2010; Sorkin and von Zastrow, 2009).   Despite evidence for connections between transport and other cellular processes, a caveat of our study is that the increased surface levels of our Snc1 reporter could be an indirect result of increased expression in some mutant strains.  Although we did not directly address this issue, the effect of our candidates on GSS reporter expression will be important to address in future studies.  This could be accomplished by creating a transcriptional reporter, in which the upstream regions of the GSS integration site are fused with LacZ.  Expression of this reporter could be evaluated by a B-galactosidase assay in candidate mutants.  Increased B-galactosidase levels in these mutants could inform us whether these  105 mutants are involved in the transciption of Snc1. 4.4.3. Assessing the role of essential genes in Snc1 transport  Another important limitation of this screening approach is that it considered the ~5000 non-essential genes, but not the ~1000 essential genes in yeast. Therefore, our view of Snc1 endocytic recycling is incomplete.  Essential genes, by definition, encode critical cellular functions that are not buffered by redundant functions or pathways (Ben-Aroya et al., 2010).  Inclusion of essential genes would be expected to have a significant impact on the size and complexity of our Snc1 sorting network, as multiple studies have demonstrated that they exhibit significantly more genetic interactions than nonessential genes, and the essential network is therefore significantly denser than the nonessential network. (Davierwala et al, 2005).  Furthermore, essential genes tend to be more highly conserved in evolution; 38% of essential yeast proteins have easily identifiable counterparts in humans, versus 20% for nonessential genes (Ben-Aroya et al., 2010).   Inclusion of essential genes could have therefore improved our study by adding to the connectivity between relevant pathways, and by expediting the analysis of critically important genes involved in endocytic recycling.  As many genome-wide studies have faced this limitation, this issue has prompted the development of genome-wide collections that facilitate the investigation of essential gene function.  Most notably, temperature-sensitive (ts) mutants have been used with great success to analyze essential genes, and current work is in progress to develop ts alleles covering the yeast genome.  Ts mutations are typically missense mutations, which retain the function of a specific essential gene at standard (permissive) temperatures, but lack that function at a defined high (non permissive) temperature.  These mutants therefore facilitate analysis of physiologic changes that follow controlled inactivation of a gene by shifting cells to a non-permissive temperature. A subset of 250 ts mutants, including alleles for all uncharacterized essential genes and genes with human counterparts, is now ready for distribution (Ben-Aroya et al., 2008 and 2010).  A complete set of these genes is expected to be available shortly, and will be tested for a role in Snc1 endocytic transport.  Another approach involves the replacement of the native promoter of each gene with one that can be rapidly repressed.  This includes the use of the tetracycline (tet)-regulatable promoter (Mnaimneh et al., 2004).  In this system, the expression of each gene is controlled by a promoter that can be shut off by adding the tetracycline analog doxycyline, to the growth medium.  Currently, TetO-promoter alleles have been created for over two-thirds of all  106 essential yeast genes.  A major advantage of this system is that the native open reading frame of each gene is maintained. The addition of doxycycline to the growth media has also been shown to have little effect on yeast physiology at concentrations used for promoter shutoff. These genes have been developed for two-thirds of all yeast essential genes.  4.4.4. Relationships between endocytic recycling factors; implications in disease  A better understanding of the machinery regulating the selective transport of proteins within the endosomal system, and their relationships is critical for deciphering the genetic causes of diseases relating to trafficking malfunction.  One feature common among diseases of intracellular transport is the considerable underlying genetic heterogeneity, which is a direct result of the complex regulatory mechanisms involved in these pathways. Many of these transport diseases present common clinical phenotypes, but are due to defects in seemingly unrelated gene products. As a result of this heterogeneity, it is difficult to carry out studies based purely on clinical phenotypes because of variable underlying mutations. More complete knowledge of how candidate genes could be related will therefore aid in the interpretation of the results from studies investigating diseases of intracellular transport (Howell et al., 2006; Olkkonen and Ikonen, 2006).  This study demonstrated unanticipated links between factors required for endocytic recycling.  One example is the coordinated roles of yAP180 and synaptojanin in Snc1 internalization.  Neurological defects are observed in the absence of both AP180 and synaptojanin in mouse models, although these defects have not previously been linked (Cao et al., 2010; Kim et al., 2002).  Altered levels of clathrin regulatory proteins, including dynamin I, AP180, and synaptophysin have been observed in AD patients and mouse models, as compared to controls, suggesting that malfunctioning of clathrin dynamics may contribute to disease pathology. This example illustrates how a better understanding of relationships between transport factors could generate a more complete picture of the mechanisms underlying disorders of intracellular transport.   Therapeutic intervention for the manipulation of endocytic transport pathways could provide a means for treating diseases resulting from defects in these transport processes.  In Alzheimer’s patients, for example, defective transport of amyloid precursor protein (APP) in axons leads to the generation of AB plaques and the progression of neurodegenerative disease (Mayeux and Hyslop, 2008).  Manipulating the transport of AB- containing vesicles in the endosomal system may therefore facilitate clearance of accumulated APP.  There has been some significant progress towards this goal.  It has been  107 found that APP processing to its plaque producing form is enhanced by inhibition of cholesterol transport, and that treatments that restore normal cholesterol levels and enhance APP transport to rab7-positive late endosomes may reduce aberrant APP processing (Stein et al., 2003; Huttunen et al., 2009).  Furthermore, many cancers result from the increased recycling of growth factor receptors to the cell surface (Hyun and Ross., 2004; Rao et al., 2003).  Implementing therapies that result in receptor down-regulation through shifting the balance between recycling and degradation may therefore positively impact outcomes.  It is therefore of interest to develop gene therapies that effectively target the specific pathway in question, without significantly affecting other important transport steps.  Current work in the field aims to develop therapies that selectively block or enhance Rab protein function, or stimulate cofactors that shunt cargo along the desired pathway, including increased expression at the cell surface, or down-regulation via enhancing degradation.  This approach would benefit significantly from a greater understanding of cargo-specific cellular transport pathways, which was an important issue addressed by this study. 4.4.5. Future perspectives   The main theme that has been highlighted by this work is that many genes involved in endocytic recycling remain unidentified, due to functional redundancy, or cargo-specific effects.  These findings highlight the importance of considering multiple cargo proteins, and the development of highly sensitive quantitative assays to detect defects in this transport process. Future application of our genome-wide analysis to different reporter proteins is expected to aid in the identification of additional cargo-specific machinery.  Furthermore, the effects of different environmental conditions should also be considered. The endocytosis of some cargo is directly regulated by environmental conditions, including many nutrient and amino acid transporters, whose cell surface expression is regulated based on external nutrient availability (Nikko and Pelham, 2009).  Studies of the same cargo under different conditions may help us determine if genes involved in their uptake are context-dependent.  Although the vast majority of functional genetic screens have been carried out in yeast, with the advent of RNAi and other knockdown techniques, it is expected that it will not be long before these types of screens could be applied to multi-cellular systems.  Our quantitative phenotypic and genetic interaction approaches will provide considerable guidance in the identification of transport components in higher cells, and the relationships between them.  Together, the emerging development of technology to study genetic  108 interactions in mammalian cells, combined with the analytical methods used in this study, could provide us with considerable insight into how defects in cellular transport pathways can contribute to human disease.  Furthermore, application of these studies to different cell types could provide insight into the similarities and differences in endocytic transport in cell types that contain specialized organelles and pathways, such as neurons and polarized epithelial cells.   109 4.4. Illustrations        Illustration 4.1. New factors required for Snc1 endocytic recycling.  A proposed model summarizing the findings from this study regarding the functional requirements for clathrin and the clathrin adaptors yAP180s and Ldb17 in Snc1 internalization and AP-1R/Ima1 in Snc1 recycling.  (1) yAP180 is recruited to the plasma membrane by combinatorial recognition of the membrane lipid PI(4,5)P2 and cargo.  Snc1, but not all endocytic cargo (including NPF-Sso1) is recognized by yAP180 for internalization. Additional components of the early coat complex are subsequently recruited and clathrin assembly begins (2) Late coat components are then recruited, including components of the actin polymerization machinery.  Ldb17 joins the late coat complex, just before the onset of actin polymerization, and is required for both normal coat and actin dynamics.  (3) Actin polymerization begins, and the vesicle begins to internalize.  (4) Inp52/synaptojanin mediates the hydrolysis of PI(4,5)P2 to PI(3), leading to uncoating of yAP180.  (5) The free vesicle fuses with the early endosome to which it delivers Snc1.  (6) Snc1 is recognized by AP-1R, possibly at the early endosome.  Ima1 associates with the AP- 1R-specific medium subunit Apm2.  AP-1R/Ima1 mediate Snc1 recycling to the Trans Golgi  Network (TGN), from which it is Snc1 is subsequently re-delivered to the plasma membrane. PI(4,5)P2 PI(3)P Snc1 NPF-Sso1 yAP180 Ldb17 Clathrin WASP/Myo Actin Amphyphysin Inp52/Synaptojanin Ldb17 Chs3 LEGEND AP-1R/ IMA1 AP-1 1 2 4 5 6 7 3 Plasma Membrane EE TGN  110               Illustration 4.2. AP-1R transport function: Model 1  In this model, AP-1R is present on early endosomes (EE), and directs internalized Snc1 to either the TGN or an intermediate recycling endosome (RE), from which Snc1 recycles back to the cell surface.  In the absence of AP-1, Snc1 may avoid transport through these intermediate compartments and recycle back to the surface direcly from EEs (hatched arrow).      Illustration 4.3. 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The resulting plasmid was digested with XbaI/SmaI, end-filled, and ligated to SUC2 sequences on a SmaI- HpaI fragment from pSEYC306 (Darsow et al., 2000)c Plasmid pMD9 GFP-SNC1(V40A M43A)- SUC2 in pRS306 (GSS en-; TPI1 promoter) This study V40A and M43A mutations were introduced into the SNC1 coding region of pCS30 by site-directed mutagenesis Plasmid pHB4 SUC2 5'UTR-ADHpr- NATR-GFP-SNC1-SUC2 (GSS; ADH promoter) This study pHB4 was created in a multi-step process. pHB1 was first created by co-transformation of SacI/Kpn1-cut pRS416 with the following PCR products: (1) the NATR selection marker, ADH promoter and yeGFP coding sequence amplified from pYMN9 (Janke et al., 2004)h and (2) a 2378 bp fragment amplified from yeast genomic DNA after integration of pCS30, encoding the SNC1-SUC2 fusion and including 458 bp of SUC2 3’UTR. A PCR fragment encoding the  131 Type Name Description/Genotype Source Notes Nyv1 cytosolic domain (aa 1-229), amplified from yeast genomic DNA, was used to replace the Snc1 cytosolic domain (aa 1- 90) by co- transformation with EcoR1-digested pHB1, creating pHB2. To facilitate integration into the SUC2 locus, 252bp of SUC2 5’UTR were amplified by PCR and incorporated upstream of the NATR cassette in BglII- digested pHB2, creating pHB3. This introduced a unique NotI restriction site upstream of the SUC2 5’UTR, such that NotI/SnaB1 digestion of pHB3 (or its derivatives) releases the chimeric reporter and the NATR marker on a cassette that is targeted to the SUC2 locus. pHB4 was then created by co- transforming ClaI/SalI- digested pHB3 with a PCR fragment containing the SNC1 sequence from pCS30. Plasmid pMD65 SUC2 5'UTR-ADHpr- NATR-GFP-NPFxD-SSO1 (NPF-Sso1) This study pMD51 was created by co-transforming ClaI/SalI-digested pHB3 with a PCR fragment containing the SNC1(V40A M43A) sequence from pMD9. The NPFxD endocytosis signal was appended to the N-terminus of the SNC1(V40A M43A) sequence in pMD51 by  132 Type Name Description/Genotype Source Notes co-transforming SpeI- digested pMD51 with a PCR product encoding MVLTNANPFSD, to generate pMD52. The SNC1(V40A M43A) coding sequence was then replaced with that of SSO1 by co- transforming ClaI/SalI digested pMD52 with a PCR fragment containing the SSO1 sequence amplified from yeast genomic DNA to create pMD60. pMD65 was made by co-transforming ClaI/SalI-digested pMD52 with a PCR fragment that directed replacement of SNC1- SUC2 sequences with the SSO1 coding sequence.   Plasmid pMD69 SUC2 5'UTR-ADHpr- NATR-GFP-3xNPFxD- SSO1-SUC2 in pRS416 (NGSS) This study pMD67 was created by insertion of two additional NPFxD motifs N-terminal in tandem with the existing NPFxD motif in pMD52 by synthesizing a PCR product containing 2 VLTNANPFSD motifs by primer extension, using overlapping oligonucleotides with 5’ homology to the ADH promoter and 3’ homology to the NPFxD motif in pMD52.  The SNC1(V40A M43A) sequence of pMD67 was then replaced with SSO1 by co- transforming ClaI/SalI digested pMD67 with PCR-amplified SSO1,  133 Type Name Description/Genotype Source Notes resulting in pMD69.   Plasmid pSM1493 STE6-GFP in pRS426 Huyer et al., 2004d gift from Susan Michaelis Plasmid pBW1427 LDB17-4XGFP tagging construct This study A plasmid for C- terminal tagging of LDB17 with 4 tandem copies of GFP+ was created in a multistep process. Site directed mutagenesis was first used to convert the ApaLI site in pGFP+(NATR) (Scholz et al., 2000)e to an HpaI site, and the SacI site to a PmlI site, generating pBW1395. The 1014bp PmlI/HpaI fragment from pBW1395 was cloned into PmlI- linearized pBW1395 to generate pBW1396, which has two copies of GFP+ flanked by unique HpaI and PmlI sites. The 2028bp PmlI/HpaI 2xGFP+ fragment from pBW1396 was then cloned into PmlI- linearized pBW1396, generating pBW1397, which has four copies of GFP+ flanked by unique HpaI and PmlI sites. PCR amplification and TA cloning was used to clone 349 bp of the LDB17 3'UTR immediately following the LDB17 ORF while introducing flanking BglII/XbaI sites. The 353bp BglII/XbaI fragment was verified by DNA sequencing and ligated into BglII/XbaI- cut pBW1397,  134 Type Name Description/Genotype Source Notes generating pBW1426. The LDB17 ORF from nt 10 to 1473 was amplified by PCR, introducing an in- frame PvuII site immediately preceding the stop codon, subjected to TA cloning, and sequenced. The 1352bp PvuII/HpaI fragment was then ligated into HpaI-cut pBW1398, generating the pBW1427, which contains a 6970bp 4xGFP+-NATR cassette flanked by LDB17 sequences that can be released by HpaI/XbaI digestion. Plasmid pOAD pOAD Uetz et al., 2000f gift from Stan Fields Plasmid pOBD2 pOBD2 Uetz et al., 2000f gift from Stan Fields Plasmid p3384 Yfr024c(291-373) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3388 Abp1(351-592) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3390 Bzz1(476-564) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3391 Bzz1(562-633) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3392 Bzz1(476-633) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3497 Myo3(1054-1271) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3519 Bem1(51-240) in pOBD2 Tong et al., gift from Charlie Boone.  135 Type Name Description/Genotype Source Notes 2002g Plasmid p3520 Bem1(1-551) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3697 Rvs167(401-482) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3699 Sla1(336-435) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3700 Sla1(1-150) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3735 Sla1(1-435) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3737 Sla1(61-150) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3755 Ysc84(391-468) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3771 Bbc1(1-90) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Plasmid p3842 Hof1(576-669) in pOBD2 Tong et al., 2002g gift from Charlie Boone. Yeast Strain BY4741 MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0 Open Biosystems Yeast Strain BY4742 MATa his3Δ1 leu2Δ0 lys2∆0 ura3Δ0 Open Biosystems Yeast Strain HBY280 BY4741  suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain HBY222 BY4741 rvs167∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY448 BY4741 ldb17∆::KAN suc2::GFP-SNC1- This study The GSS reporter plasmid pCS30 was  136 Type Name Description/Genotype Source Notes SUC2::URA3 linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY461 BY4741 bzz1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY520 BY4741 lsb3∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY453 BY4741 inp52∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY451 BY4741 abp1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain HBY277 BY4741 myo5∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain HBY282 BY4741 fus3∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast HBY278 BY4741 ede1∆::KAN This The GSS reporter  137 Type Name Description/Genotype Source Notes Strain suc2::GFP-SNC1- SUC2::URA3 study plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain HBY279 BY4741 sla1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain HBY281 BY4741 vrp1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain HBY284 BY4741 yol098c∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY452 BY4741 crn1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY455 BY4741 twf1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY449 BY4741 rvs161∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.   138 Type Name Description/Genotype Source Notes Yeast Strain CSY521 BY4741 bbc1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY435 BY4741 yap1802∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY522 BY4741 syp1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY523 BY4741 cap1∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY525 BY4741 cap2∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY444 BY4741 yap1801∆::KAN suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in BY4741 and its knockout derivatives.  Yeast Strain CSY462 BY4741 suc2::GFP- snc1(V40A,M43A)- SUC2::URA3 This study The GSS EN- reporter plasmid pMD9 was linearized with XbaI and integrated at the SUC2 locus in BY4741 Yeast MDY581 BY4741 yap1801∆::KAN This The YAP1802 ORF was  139 Type Name Description/Genotype Source Notes Strain yap1802∆::HPH  study replaced with the hygromycin resistance marker in BY4741 yap1801::KAN  by transformation of a PCR fragment amplified from pFA6- hphNT1 (Janke et al., 2004)h, generating MDY581.  Yeast Strain HBY323 BY4741 yap1801∆::KAN yap1802∆::HPH suc2::GFP- SNC1-SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in MDY581 Yeast Strain MDY582 BY4741 yap1801∆::KAN yap1802∆CBM-3HA::HIS3 This study The final 4 C-terminal residues of Yap1802 (564-568) were replaced with a 3xHA tag in BY4741 yap1801::KAN  to make MDY582 Yeast Strain MDY583 BY4741 yap1801∆::KAN YAP1802-3HA::HIS3 This study  Yeast Strain CSY462 BY4741  suc2::GFP- SNC1(V40A,M43A)- SUC2::URA3 This study The GSS EN- reporter plasmid pMD9 was linearized with XbaI and integrated at the SUC2 locus in BY4741 to create CSY462 Yeast Strain HBY333 BY4741 suc2∆::NAT-GFP- 3xNPFxD-SSO1-SUC2 This study The 3xNGSS reporter was integrated at the SUC2 locus in BY4741 and derivatives by transformation with a NotI/SnaBI fragment released from pMD69 to create strains HBY333-HBY338. Integration of reporters was confirmed by colony PCR.  Yeast Strain HBY334 BY4741 yap1801∆::KAN suc2∆::NAT-GFP-3xNPFxD- SSO1-SUC2 This study The 3xNGSS reporter was integrated at the SUC2 locus in BY4741 and derivatives by transformation with a  140 Type Name Description/Genotype Source Notes NotI/SnaBI fragment released from pMD69 to create strains HBY333-HBY338. Integration of reporters was confirmed by colony PCR.  Yeast Strain HBY335 BY4741 yap1802∆::KAN suc2∆::NAT-GFP-3xNPFxD- SSO1-SUC2 This study The 3xNGSS reporter was integrated at the SUC2 locus in BY4741 and derivatives by transformation with a NotI/SnaBI fragment released from pMD69 to create strains HBY333-HBY338. Integration of reporters was confirmed by colony PCR.  Yeast Strain HBY336 BY4741 yap1801∆::KAN yap1802∆::HPH suc2∆::NAT-GFP-3xNPFxD- SSO1-SUC2 This study The 3xNGSS reporter was integrated at the SUC2 locus in BY4741 and derivatives by transformation with a NotI/SnaBI fragment released from pMD69 to create strains HBY333-HBY338. Integration of reporters was confirmed by colony PCR.  Yeast Strain HBY337 BY4741 ldb17∆::KAN suc2∆::NAT-GFP-3xNPFxD- SSO1-SUC2 This study The 3xNGSS reporter was integrated at the SUC2 locus in BY4741 and derivatives by transformation with a NotI/SnaBI fragment released from pMD69 to create strains HBY333-HBY338. Integration of reporters was confirmed by colony PCR.  Yeast HBY338 BY4741 sla1∆::KAN This The 3xNGSS reporter  141 Type Name Description/Genotype Source Notes Strain suc2∆::NAT-GFP-3xNPFxD- SSO1-SUC2 study was integrated at the SUC2 locus in BY4741 and derivatives by transformation with a NotI/SnaBI fragment released from pMD69 to create strains HBY333-HBY338. Integration of reporters was confirmed by colony PCR.  Yeast Strain LCY1785 BY4741 LDB17- 13MYC::KAN This study C-terminal tag encoding a 13xmyc epitope was integrated at the LDB17 locus as previously described (Longtine et al., 1998)i Yeast Strain LCY1786 BY4741 ldb17∆PRD- 13MYC::KAN This study C-terminal tag encoding a 13xmyc epitope was integrated at the LDB17 locus before Pro475, truncating Ldb17 and removing the proline- rich domain (Longtine et al., 1998)i Yeast Strain LCY1797 BY4741 LDB17- 13MYC::KAN BZZ1- 3HA::HIS3 This study C-terminal tag encoding a 3xHA epitope (Longtine et al., 1998)i was integrated at the BZZ1 locus in LCY1786 Yeast Strain LCY1798 BY4741 ldb17∆PRD- 13MYC::KAN BZZ1- 3HA::HIS3 This study C-terminal tag encoding a 3xHA epitope (Longtine et al., 1998)i was integrated at the BZZ1 locus in LCY1786 Yeast Strain CSY76 BY4741 LDB17-GFP::HIS3 This study To create the control strains (CSY76 and CSY78), the GFP-HIS3 cassette was integrated before the LDB17 stop codon.  Yeast Strain CSY80 BY4741 ldb17∆PRD- GFP::HIS3 This study Expression of Ldb17- PRD∆ in CSY80 and CSY79 was  142 Type Name Description/Genotype Source Notes accomplished by integration of a GFP- HIS3 cassette pGFP+; (Scholz et al., 2000)e before Pro475, truncating Ldb17 and removing the proline- rich domain.  Yeast Strain CSY78 BY4741 bzz1∆::KAN LDB17-GFP::HIS3 This study To create the control strains (CSY76 and CSY78), the GFP-HIS3 cassette was integrated before the LDB17 stop codon.  Yeast Strain CSY79 BY4741 bzz1∆::KAN ldb17∆PRD-GFP::HIS3  This study Expression of Ldb17- PRD∆ in CSY80 and CSY79 was accomplished by integration of a GFP- HIS3 cassette pGFP+; (Scholz et al., 2000)e before Pro475, truncating Ldb17 and removing the proline- rich domain.  Yeast Strain HBY377 CSY76 suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in the indicated strain Yeast Strain HBY378 CSY80 suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in the indicated strain Yeast Strain HBY379 CSY78 suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in the indicated strain Yeast Strain HBY380 CSY79 suc2::GFP-SNC1- SUC2::URA3 This study The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus in the  143 Type Name Description/Genotype Source Notes indicated strain Yeast Strain MDY620 BY4741 LDB17- 4XGFP::NAT  This study MDY620 and MDY628 were constructed by transforming BY4741 and BY4741 sla1∆ with HpaI/XbaI digested pBW1427.  Yeast Strain MDY628 BY4741 sla1∆::KAN LDB17-4XGFP::NAT  This study MDY620 and MDY628 were constructed by transforming BY4741 and BY4741 sla1∆ with HpaI/XbaI digested pBW1427.  Yeast Strain CSY84 BY4741 LDB17-GFP::NAT SLA1-RFP::HIS3 This study C-terminal tag encoding mRFP1.5 (Campbell et al., 2002)j was integrated as previously described (Longtine et al., 1998)i Yeast Strain CSY85 BY4741 LDB17-GFP::NAT MYO5-RFP::HIS3 This study C-terminal tag encoding mRFP1.5 (Campbell et al., 2002)j was integrated as previously described (Longtine et al., 1998)i Yeast Strain CSY86 BY4741 LDB17-GFP::NAT ABP1-RFP::HIS3 This study C-terminal tag encoding mRFP1.5 (Campbell et al., 2002)j was integrated as previously described (Longtine et al., 1998)i Yeast Strain SEY6210 MATa leu2-3,112  ura3-52  his3-∆200  trp1-∆901  lys2-801 suc2-∆9  Met- S. Emr  Yeast Strain BWY2563 SEY6210 yap1801∆::HIS3 Wendla nd and Emr, 1998k BY2563, BY2565 and BY2567 were backcrossed from strains described in (Wendland and Emr, 1998)k Yeast Strain BWY2565 SEY6210 yap1802∆::LEU2 Wendla nd and Emr, 1998k BY2563, BY2565 and BY2567 were backcrossed from strains described in (Wendland and Emr, 1998)k Yeast Strain BWY2567 SEY6210 yap1801∆::HIS3 yap1802∆::LEU2 Wendla nd and BY2563, BY2565 and BY2567 were  144 Type Name Description/Genotype Source Notes Emr, 1998k backcrossed from strains described in (Wendland and Emr, 1998)k Yeast Strain BWY2552 SEY6210 ldb17∆::NAT This study LDB17 was replaced by NATR MX4 amplified from p4339 (Tong and Boone, 2006)l in SEY6210 to create BWY2552 Yeast Strain BWY2068 SEY6210 end3∆::KAN This study END3 was replaced by KANR MX6 amplified from pFA6a-KanMX6 (Longtine et al., 1998)i to create BY2068 Yeast Strain HBY551 SEY6210 ABP1-GFP::HIS3 This study C-terminal tag encoding an improved version of GFP (GFP+) (Scholz et al., 2000)e was integrated in SEY6210 Yeast Strain HBY552 BWY2552 ABP1- GFP::HIS3  This study C-terminal tag encoding an improved version of GFP (GFP+) (Scholz et al., 2000)e was integrated in WY2552 Yeast Strain MDY562 SEY6210 SLA1-RFP::HIS3 This study C-terminal tag encoding mRFP1.5 (Campbell et al., 2002)j was integrated as previously described (Longtine et al., 1998) in SEY6210 Yeast Strain MDY564 SEY6210 ldb17∆::NAT SLA1-RFP::HIS3 This study C-terminal tag encoding mRFP1.5 (Campbell et al., 2002)j was integrated in BWY2552 as previously described (Longtine et al., 1998)i Yeast Strain PJ694a MATa trp1-901 leu2-3,112 ura3-52  his3-200 gal4∆ gal80∆ LYS::GAL1-HIS3 GAL2-ADE2 met2::GAL7- lacZ James et al., 1996m  Yeast Strain PJ694a MATa trp1-901 leu2-3,112 ura3-52 his3-200 gal4∆ James et al., 1996m  145 Type Name Description/Genotype Source Notes gal80∆ LYS::GAL1-HIS3 GAL2-ADE2 met2::GAL7- lacZ Yeast Strain Y2H- LDB17 PJ694a pOAD-LDB17 S. Fields PJ69-4a containing pOAD-LDB17 was obtained from the genome wide Y2H activation domain collection (gift from Stan Fields, U of Washington). Yeast Strain BMY102 PJ694a pOAD-ldb17∆PRD This study PJ69-4a containing pOAD-ldb17 ∆PRD was generated by co- transformation of PJ694-a with an LDB17  PCR fragment lacking the C-term PRD domain (Pro475-Lys491) and PvuII/NcoI-linearized pOAD, and was subsequently confirmed by sequencing and western blotting. Yeast Strain Y6613 MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0  lyp1∆::STE3pr-LEU2 cyh C. Boone gift from Charlie Boone. Yeast Strain MDY220 Y6613 suc2::GFP-SNC1- SUC2::URA3 This study Synthetic genetic analysis (SGA) starting strains Y6613 (Tong and Boone, 2006)g and Y7043 (gift of C. Boone) were transformed with Xba1-linearized pCS30, yielding MDY220 and MDY519.  Yeast Strain Y7043 MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0 can1::STE2pr-LEU2  lyp1 cyh2 C. Boone gift from Charlie Boone. Yeast Strain MDY519 Y7043 suc2::GFP-SNC1- SUC2::URA3 This study Synthetic genetic analysis (SGA) starting strains Y6613 (Tong and Boone, 2006)g and Y7043 (gift of C. Boone) were  146 Type Name Description/Genotype Source Notes transformed with Xba1-linearized pCS30, yielding MDY220 and MDY519.  Yeast Strain MDY525 Y7043 suc2::GFP-SNC1- SUC2::NAT This study Y7043 was transformed with pHB4 was digested with NotI and SnaB1  Yeast Strain MDY59 Y7043 suc2::GFP- SNC1(S59A)-SUC2::NAT This study pHB4 was mutated to introduce the SNC1 S59A mutation, digested with NotI/SnaBI and transformed into Y7043 Yeast Strain MDY79 Y7043 suc2::GFP- SNC1(S59D)-SUC2::NAT This study pHB4 was mutated to introduce the SNC1 S59D mutation, digested with NotI/SnaBI and transformed into Y7044 Yeast Strain MDY324 Y7043 suc2::GFP- SNC1(V40A,M43A)- SUC2::URA3 pNAT This study The GSS EN- reporter plasmid pMD9 was linearized with XbaI and integrated at the SUC2 locus in the indicated strain Yeast Strain MDY48 MDY519 apm1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY46 MDY519 apm2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY47 MDY519 apl4∆::NAT  This study Gene replacement with the NATR MX4 marker  147 Type Name Description/Genotype Source Notes was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY35 MDY519 yap1801∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY47 MDY519 apl4∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY48 MDY519 apm1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY46 MDY519 apm2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY34 MDY519 ent1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with  148 Type Name Description/Genotype Source Notes appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY35 MDY519 ent2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY36 MDY519 ent4∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY53 MDY519 glc8∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY43 MDY519 inp52∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY37 MDY519 prk1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and  149 Type Name Description/Genotype Source Notes Boone, 2006)l.  Yeast Strain MDY44 MDY519 sec28∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY41 MDY519 syp1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY45 MDY519 ubi4∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY52 MDY519 vps13∆::NAT This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY33 MDY519 yap1801∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY40 MDY519 yap1802∆::NAT  This study Gene replacement with the NATR MX4 marker  150 Type Name Description/Genotype Source Notes was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY38 MDY519 ydr348c∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY54 MDY519 yvh1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY88 MDY519 apl6∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY14 MDY519 atg20∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY87 MDY519 ent5∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with  151 Type Name Description/Genotype Source Notes appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY129 MDY519 gga2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY131 MDY519 inp53∆::NAT This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY127 MDY519 nhx1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY10 MDY519 snx4∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY169 MDY519 snx41∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and  152 Type Name Description/Genotype Source Notes Boone, 2006)l.  Yeast Strain MDY271 MDY519 vam3∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY92 MDY519 vps4∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY39 MDY519 vps5∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY270 MDY519 vps9∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY95 MDY519 vps54∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain CSY56 MDY519 vps55∆::NAT  This study Gene replacement with the NATR MX4 marker  153 Type Name Description/Genotype Source Notes was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain CSY57 MDY519 vps68∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY125 MDY519 yfr043c∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY170 MDY519 ypt31∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY16 MDY519 ypt35∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY292 MDY519 trp1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with  154 Type Name Description/Genotype Source Notes appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY282 MDY519 age2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY171 MDY519 cka1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY280 MDY519 ckb1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY13 MDY519 ent3∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY85 MDY519 erg4∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and  155 Type Name Description/Genotype Source Notes Boone, 2006)l.  Yeast Strain MDY133 MDY519 fks1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY279 MDY519 gcs1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY277 MDY519 gef1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY42 MDY519 hul5∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY83 MDY519 las21∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY82 MDY519 lcb4∆::NAT  This study Gene replacement with the NATR MX4 marker  156 Type Name Description/Genotype Source Notes was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY265 MDY519 sak1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY268 MDY519 scy1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY284 MDY519 vam7∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY283 MDY519 vps8∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY286 MDY519 vps17∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with  157 Type Name Description/Genotype Source Notes appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY134 MDY519 vps21∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY278 MDY519 vps38∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY281 MDY519 vps51∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY287 MDY519 ykr078w∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY285 MDY519 ypr097w∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and  158 Type Name Description/Genotype Source Notes Boone, 2006)l.  Yeast Strain MDY80 MDY519 ypt6∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY360 MDY519 apm3∆::NAT This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY389 MDY519 arf1∆::NAT This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY332 MDY519 arr4∆::NAT This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY333 MDY519 bsd2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY415 MDY519 hap4∆::NAT  This study Gene replacement with the NATR MX4 marker  159 Type Name Description/Genotype Source Notes was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY371 MDY519 lsp1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY413 MDY519 mon2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY357 MDY519 mvp1∆::NAT This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY372 MDY519 pil1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY383 MDY519 ptc1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with  160 Type Name Description/Genotype Source Notes appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY391 MDY519 rav1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY366 MDY519 rts1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY421 MDY519 sft2∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY400 MDY519 vrp1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY51 MDY519 akr1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and  161 Type Name Description/Genotype Source Notes Boone, 2006)l.  Yeast Strain MDY332 MDY519 get3∆::NAT This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY393 MDY519 stv1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY398 MDY519 ubp3∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY385 MDY519 vps1∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.  Yeast Strain MDY417 MDY519 vps27∆::NAT  This study Gene replacement with the NATR MX4 marker was accomplished by transformation of MDY519 with appropriate PCR products amplified from p4339 (Tong and Boone, 2006)l.     162 Table A2. Full list of mutants with cell surface GSS levels greater to or equal to the median value for all strains. Note that a low densitometry value indicates a high level of cell surface reporter. Densitometry values were subtracted from the median value for all strains to generate "SCORE".  Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1 YCR009C RVS161 0.11 0.04 0.07 0.93 2 YDR207C UME6 0.05 0.10 0.07 0.93 3 YOR035C SHE4 0.14 0.08 0.11 0.90 4 YLR337C VRP1 0.14 0.12 0.13 0.87 5 YAL013W DEP1 0.13  0.13 0.87 6 YPL045W VPS16 0.13  0.13 0.87 7 YNL069C RPL16B 0.03 0.24 0.13 0.87 8 YDR388W RVS167 0.13  0.13 0.87 9 YMR198W CIK1 0.14  0.14 0.87 10 YDL146W LDB17  0.14 0.14 0.86 11 YKR094C RPL40B 0.06 0.22 0.14 0.86 12 YBL007C SLA1 0.14 0.15 0.15 0.86 13 YCR044C PER1 0.10 0.20 0.15 0.86 14 YIL049W DFG10 0.16  0.16 0.85 15 YKL002W DID4 0.16  0.16 0.85 16 YIL154C IMP2' 0.18  0.18 0.82 17 YDR276C PMP3 0.07 0.35 0.21 0.80 18 YLR370C ARC18 0.18 0.24 0.21 0.80 19 YLR056W ERG3 0.21 0.22 0.21 0.79 20 YIL128W MET18 0.32 0.13 0.23 0.78 21 YHR026W PPA1 0.23  0.23 0.77 22 YER056C- A RPL34A 0.23 0.24 0.23 0.77 23 YLR338W  0.28 0.19 0.24 0.77 24 YLR399C BDF1 0.10 0.40 0.25 0.75 25 YMR311C GLC8 0.14 0.36 0.25 0.75 26 YGR240C PFK1  0.26 0.26 0.75 27 YDR442W  0.26  0.26 0.75 28 YOL004W SIN3 0.26  0.26 0.75 29 YHR161C YAP1801 0.06 0.45 0.26 0.75 30 YEL031W SPF1 0.15 0.38 0.27 0.74 31 YBL047C EDE1 0.21 0.33 0.27 0.74 32 YJL080C SCP160  0.27 0.27 0.73 33 YNL215W IES2 0.15 0.42 0.28 0.72 34 YMR091C NPL6 0.29  0.29 0.71 35 YIL090W ICE2 0.29  0.29 0.71 36 YDR364C CDC40 0.29  0.29 0.71 37 YPL031C PHO85 0.32 0.29 0.30 0.70  163 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  38 YLR119W SRN2 0.31  0.31 0.70 39 YDL081C RPP1A 0.30 0.33 0.32 0.69 40 YNR006W VPS27 0.43 0.21 0.32 0.69 41 YIL076W SEC28 0.32  0.32 0.68 42 YGR241C YAP1802 0.35 0.29 0.32 0.68 43 YLR025W SNF7  0.33 0.33 0.68 44 YPR029C APL4 0.23 0.44 0.33 0.67 45 YKL007W CAP1 0.26 0.42 0.34 0.67 46 YIL093C RSM25 0.34  0.34 0.66 47 YGL058W RAD6 0.25 0.46 0.35 0.65 48 YJL176C SWI3 0.71 0.00 0.35 0.65 49 YER074W RPS24A 0.39 0.33 0.36 0.65 50 YBR127C VMA2 0.36  0.36 0.64 51 YAL047C SPC72 0.37  0.37 0.64 52 YNL079C TPM1 0.50 0.24 0.37 0.63 53 YJR121W ATP2 0.37  0.37 0.63 54 YCR088W ABP1 0.32 0.42 0.37 0.63 55 YKL119C VPH2  0.38 0.38 0.62 56 YGR242W  0.43 0.33 0.38 0.62 57 YPL178W CBC2 0.38  0.38 0.62 58 YHL002W HSE1 0.30 0.47 0.39 0.62 59 YHL025W SNF6 0.39  0.39 0.62 60 YMR116C ASC1 0.17 0.61 0.39 0.62 61 YMR109W MYO5 0.35 0.43 0.39 0.61 62 YLR425W TUS1 0.40 0.39 0.39 0.61 63 YNL105W  0.25 0.54 0.40 0.61 64 YBL027W RPL19B 0.42 0.38 0.40 0.61 65 YDL002C NHP10 0.26 0.56 0.41 0.59 66 YNR010W CSE2 0.26 0.57 0.42 0.59 67 YIL084C SDS3 0.43  0.43 0.58 68 YNL106C INP52 0.29 0.56 0.43 0.58 69 YFL025C BST1 0.35 0.51 0.43 0.58 70 YNR023W SNF12 0.65 0.21 0.43 0.57 71 YNR052C POP2 0.86 0.00 0.43 0.57 72 YGL168W HUR1 0.36 0.51 0.43 0.57 73 YJL062W LAS21 0.50 0.38 0.44 0.57 74 YIR034C LYS1 0.57 0.31 0.44 0.56 75 YMR263W SAP30 0.56 0.32 0.44 0.56 76 YGL084C GUP1 0.38 0.51 0.44 0.56 77 YEL013W VAC8 0.38 0.51 0.45 0.56 78 YIR003W  0.51 0.39 0.45 0.55 79 YKR035C  0.50 0.40 0.45 0.55 80 YLR171W  0.26 0.64 0.45 0.55 81 YPL002C SNF8  0.45 0.45 0.55  164 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  82 YCR028C- A RIM1 0.45  0.45 0.55 83 YGR101W PCP1 0.24 0.67 0.46 0.54 84 YLR200W YKE2 0.46  0.46 0.54 85 YGL027C CWH41 0.32 0.60 0.46 0.54 86 YDL243C AAD4  0.47 0.47 0.53 87 YLR170C APS1 0.27 0.67 0.47 0.53 88 YDL160C DHH1  0.47 0.47 0.53 89 YOR209C NPT1 0.34 0.61 0.48 0.53 90 YER092W IES5 0.36 0.60 0.48 0.53 91 YAL068C  0.35 0.61 0.48 0.52 92 YGL219C MDM34 0.53 0.43 0.48 0.52 93 YGR204W ADE3 0.32 0.64 0.48 0.52 94 YLR169W  0.33 0.63 0.48 0.52 95 YGL066W SGF73 0.43 0.54 0.48 0.52 96 YKR001C VPS1 0.42 0.55 0.48 0.52 97 YOR275C RIM20 0.39 0.59 0.49 0.51 98 YPL100W ATG21 0.37 0.62 0.49 0.51 99 YPR067W ISA2 0.50  0.50 0.51 100 YKL204W EAP1 0.33 0.66 0.50 0.51 101 YNL219C ALG9 0.55 0.45 0.50 0.51 102 YBL083C  0.50  0.50 0.51 103 YPL042C SSN3 0.50  0.50 0.51 104 YJL175W  0.84 0.16 0.50 0.50 105 YNL197C WHI3 0.97 0.04 0.51 0.50 106 YDR226W ADK1  0.51 0.51 0.50 107 YOR126C IAH1 0.19 0.83 0.51 0.50 108 YBL058W SHP1  0.51 0.51 0.49 109 YOL129W VPS68 0.39 0.64 0.52 0.49 110 YGR206W  0.51 0.53 0.52 0.48 111 YML019W OST6 0.44 0.60 0.52 0.48 112 YDL194W SNF3 0.54 0.51 0.52 0.48 113 YNR005C  0.66 0.39 0.52 0.48 114 YBL006C LDB7 0.53  0.53 0.48 115 YKL041W VPS24 0.53  0.53 0.48 116 YNL111C CYB5 0.48 0.58 0.53 0.48 117 YFR031C- A RPL2A 0.27 0.80 0.53 0.47 118 YBR095C  0.44 0.64 0.54 0.47 119 YBR156C SLI15 0.84 0.23 0.54 0.47 120 YGR100W MDR1 0.52 0.56 0.54 0.47 121 YBL082C ALG3 0.52 0.56 0.54 0.46 122 YLL030C  0.06 1.03 0.55 0.46 123 YLR417W VPS36  0.55 0.55 0.46  165 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  124 YIL020C HIS6 0.20 0.90 0.55 0.46 125 YNR030W ALG12 0.53 0.57 0.55 0.45 126 YKR100C SKG1 0.58 0.52 0.55 0.45 127 YIL034C CAP2 0.46 0.64 0.55 0.45 128 YLR139C SLS1 0.55  0.55 0.45 129 YIL163C  0.12 1.00 0.56 0.45 130 YPL256C CLN2 0.62 0.50 0.56 0.45 131 YPR030W CSR2 0.39 0.73 0.56 0.45 132 YHL019C APM2 0.59 0.53 0.56 0.44 133 YML014W TRM9 0.56  0.56 0.44 134 YJL153C INO1 0.24 0.88 0.56 0.44 135 YHR030C SLT2 0.64 0.48 0.56 0.44 136 YPR164W MMS1 0.36 0.76 0.56 0.44 137 YPL179W PPQ1 0.63 0.50 0.56 0.44 138 YDR006C SOK1 0.53 0.60 0.56 0.44 139 YJR073C OPI3  0.56 0.56 0.44 140 YML008C ERG6 1.04 0.09 0.57 0.44 141 YER120W SCS2 0.49 0.64 0.57 0.44 142 YKL073W LHS1 0.67 0.47 0.57 0.44 143 YGL076C RPL7A 0.52 0.62 0.57 0.43 144 YPR070W MED1 0.73 0.41 0.57 0.43 145 YNL248C RPA49 0.57  0.57 0.43 146 YPR024W YME1 0.80 0.35 0.57 0.43 147 YKR099W BAS1 0.53 0.62 0.58 0.43 148 YCL005W LDB16 0.13 1.02 0.58 0.43 149 YDR074W TPS2 0.64 0.52 0.58 0.43 150 YLR428C  0.64 0.52 0.58 0.43 151 YNL016W PUB1 0.50 0.66 0.58 0.42 152 YIR023W DAL81 0.14 1.02 0.58 0.42 153 YNL252C MRPL17 0.58  0.58 0.42 154 YML048W GSF2 0.49 0.68 0.58 0.42 155 YGR080W TWF1 0.43 0.74 0.59 0.42 156 YNL269W BSC4 0.13 1.04 0.59 0.42 157 YPL158C  0.59 0.59 0.59 0.42 158 YNL238W KEX2 0.59  0.59 0.42 159 YER130C  0.60 0.57 0.59 0.42 160 YKL074C MUD2 0.47 0.71 0.59 0.41 161 YBR289W SNF5 0.59  0.59 0.41 162 YMR272C SCS7 0.37 0.82 0.59 0.41 163 YCR063W BUD31 0.57 0.62 0.59 0.41 164 YHL027W RIM101 0.45 0.74 0.59 0.41 165 YPL057C SUR1 0.46 0.73 0.60 0.41 166 YLR403W SFP1 0.39 0.80 0.60 0.41 167 YPL118W MRP51 0.60  0.60 0.41  166 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  168 YGR256W GND2 0.47 0.72 0.60 0.41 169 YLL033W  0.69 0.50 0.60 0.41 170 YNL097C PHO23 0.61 0.59 0.60 0.41 171 YGR061C ADE6 0.63 0.58 0.60 0.40 172 YCL007C  0.60  0.60 0.40 173 YJL183W MNN11 0.88 0.33 0.60 0.40 174 YHR081W LRP1 0.29 0.92 0.60 0.40 175 YDR448W ADA2 0.57 0.64 0.61 0.40 176 YIL027C KRE27 0.70 0.51 0.61 0.40 177 YGR157W CHO2 0.65 0.57 0.61 0.40 178 YOL108C INO4 0.61  0.61 0.40 179 YOR030W DFG16 0.77 0.45 0.61 0.39 180 YOR008C SLG1 0.73 0.49 0.61 0.39 181 YPR101W SNT309 0.47 0.75 0.61 0.39 182 YGR056W RSC1 0.56 0.67 0.61 0.39 183 YCR002C CDC10 0.61  0.61 0.39 184 YDL176W  0.01 1.22 0.62 0.39 185 YEL036C ANP1  0.62 0.62 0.39 186 YFR001W LOC1 0.62  0.62 0.38 187 YJL060W BNA3 0.81 0.43 0.62 0.38 188 YBR229C ROT2  0.62 0.62 0.38 189 YLL038C ENT4 0.66 0.58 0.62 0.38 190 YLL039C UBI4 0.56 0.68 0.62 0.38 191 YOR026W BUB3 0.70 0.54 0.62 0.38 192 YLR087C CSF1 0.66 0.58 0.62 0.38 193 YOL036W  0.14 1.11 0.62 0.38 194 YGR122W  0.42 0.82 0.62 0.38 195 YBR097W VPS15  0.62 0.62 0.38 196 YOR274W MOD5 0.65 0.61 0.63 0.38 197 YJR075W HOC1 0.66 0.59 0.63 0.38 198 YNL284C MRPL10 0.63  0.63 0.38 199 YPL027W SMA1 0.54 0.71 0.63 0.38 200 YNL220W ADE12 0.52 0.74 0.63 0.38 201 YHR082C KSP1 0.59 0.67 0.63 0.37 202 YJR034W PET191 0.63  0.63 0.37 203 YNL280C ERG24 1.09 0.18 0.63 0.37 204 YDL075W RPL31A 0.61 0.66 0.63 0.37 205 YCR028C FEN2 0.63  0.63 0.37 206 YLR069C MEF1 0.64  0.64 0.37 207 YDL073W  0.22 1.05 0.64 0.37 208 YLR358C   0.64 0.64 0.37 209 YDR129C SAC6 1.11 0.17 0.64 0.37 210 YPR052C NHP6A 0.73 0.55 0.64 0.36 211 YIR026C YVH1 0.91 0.38 0.64 0.36  167 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  212 YMR023C MSS1 0.26 1.02 0.64 0.36 213 YGL127C SOH1 0.41 0.88 0.64 0.36 214 YLR382C NAM2 0.64  0.64 0.36 215 YGL167C PMR1 0.56 0.73 0.65 0.36 216 YCR030C SYP1 0.51 0.78 0.65 0.36 217 YML017W PSP2 0.69 0.60 0.65 0.36 218 YMR063W RIM9 0.34 0.96 0.65 0.36 219 YBR255W  0.67 0.63 0.65 0.35 220 YOR141C ARP8 1.03 0.28 0.65 0.35 221 YLR150W STM1 0.63 0.67 0.65 0.35 222 YGL200C EMP24  0.65 0.65 0.35 223 YGL014W PUF4 0.65 0.66 0.65 0.35 224 YGL072C  0.34 0.97 0.65 0.35 225 YEL063C CAN1 0.33 0.98 0.65 0.35 226 YAL055W PEX22 0.72 0.58 0.65 0.35 227 YDR532C  1.22 0.09 0.65 0.35 228 YNL153C GIM3 0.66  0.66 0.35 229 YJL124C LSM1 0.68 0.64 0.66 0.35 230 YDR346C SVF1 0.61 0.70 0.66 0.35 231 YJL020C BBC1 0.75 0.57 0.66 0.35 232 YEL060C PRB1 0.64 0.68 0.66 0.35 233 YJL128C PBS2 0.59 0.73 0.66 0.34 234 YEL067C  0.53 0.80 0.66 0.34 235 YBR150C TBS1 0.54 0.79 0.66 0.34 236 YKL081W TEF4 0.43 0.90 0.66 0.34 237 YPL034W  0.66 0.68 0.67 0.34 238 YDL005C MED2  0.67 0.67 0.34 239 YPR006C ICL2 0.75 0.58 0.67 0.34 240 YGL016W KAP122 0.50 0.83 0.67 0.34 241 YIR009W MSL1 0.43 0.90 0.67 0.34 242 YJR116W  0.80 0.54 0.67 0.34 243 YLR412W  0.70 0.64 0.67 0.34 244 YPL129W TAF14 0.67  0.67 0.33 245 YPL066W  0.93 0.41 0.67 0.33 246 YNR031C SSK2 0.66 0.69 0.67 0.33 247 YJL067W  0.47 0.88 0.67 0.33 248 YBR144C  0.76 0.58 0.67 0.33 249 YJL068C  0.38 0.97 0.67 0.33 250 YFL013W- A  0.57 0.78 0.67 0.33 251 YMR031W -A  0.56 0.79 0.67 0.33 252 YLR149C  0.56 0.79 0.67 0.33 253 YIL116W HIS5 0.25 1.10 0.68 0.33  168 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  254 YLR113W HOG1 0.75 0.60 0.68 0.33 255 YLR422W  0.65 0.70 0.68 0.33 256 YMR024W MRPL3 0.34 1.01 0.68 0.33 257 YNL199C GCR2 0.66 0.69 0.68 0.33 258 YHR092C HXT4 0.85 0.51 0.68 0.32 259 YFL034W  0.70 0.66 0.68 0.32 260 YKL065C  0.72 0.64 0.68 0.32 261 YMR038C CCS1 0.68  0.68 0.32 262 YGR160W  0.40 0.97 0.68 0.32 263 YOR067C ALG8 0.65 0.72 0.68 0.32 264 YJL056C ZAP1 0.51 0.85 0.68 0.32 265 YKL063C  0.68 0.69 0.68 0.32 266 YGR126W  0.92 0.45 0.68 0.32 267 YDR225W HTA1 0.81 0.56 0.69 0.32 268 YBR106W PHO88 0.75 0.62 0.69 0.32 269 YGR259C  0.58 0.80 0.69 0.32 270 YPL212C PUS1 0.55 0.83 0.69 0.32 271 YDR233C RTN1 0.54 0.84 0.69 0.32 272 YGL045W RIM8 0.55 0.83 0.69 0.31 273 YIL130W  0.66 0.72 0.69 0.31 274 YOL009C MDM12 0.53 0.85 0.69 0.31 275 YKR035W -A DID2 0.66 0.73 0.69 0.31 276 YLR120C YPS1 0.58 0.80 0.69 0.31 277 YJR055W HIT1 0.42 0.96 0.69 0.31 278 YCR048W ARE1 0.63 0.75 0.69 0.31 279 YGL149W  0.52 0.86 0.69 0.31 280 YJL120W  0.66 0.73 0.69 0.31 281 YDL161W ENT1 0.66 0.73 0.69 0.31 282 YFL013C IES1 0.79 0.59 0.69 0.31 283 YPR173C VPS4 0.72 0.67 0.69 0.31 284 YML012W ERV25 0.73 0.66 0.70 0.31 285 YIR005W IST3 0.71 0.68 0.70 0.31 286 YHR079C IRE1 0.79 0.60 0.70 0.31 287 YCL046W  0.66 0.73 0.70 0.31 288 YLR136C TIS11 0.83 0.56 0.70 0.31 289 YPL036W PMA2 0.57 0.83 0.70 0.31 290 YDR072C IPT1 0.78 0.62 0.70 0.31 291 YCL008C STP22 1.03 0.37 0.70 0.31 292 YDR335W MSN5  0.70 0.70 0.31 293 YNL264C PDR17 0.51 0.89 0.70 0.30 294 YOR189W IES4 0.52 0.88 0.70 0.30 295 YPL227C ALG5 0.73 0.68 0.70 0.30 296 YDR455C  0.44 0.97 0.70 0.30  169 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  297 YMR032W HOF1 0.70  0.70 0.30 298 YNL266W  0.70  0.70 0.30 299 YMR316C- A  0.47 0.94 0.70 0.30 300 YPL049C DIG1 0.46 0.95 0.70 0.30 301 YLR262C YPT6 0.54 0.87 0.70 0.30 302 YMR139W RIM11 0.67 0.74 0.70 0.30 303 YCR060W TAH1 0.47 0.94 0.71 0.30 304 YOR255W OSW1 0.21 1.20 0.71 0.30 305 YDR414C ERD1 0.75 0.67 0.71 0.29 306 YPL145C KES1 0.73 0.69 0.71 0.29 307 YOR211C MGM1 0.44 0.99 0.71 0.29 308 YOL007C  0.51 0.91 0.71 0.29 309 YAL010C MDM10 0.71  0.71 0.29 310 YOR127W RGA1 0.52 0.91 0.71 0.29 311 YGR078C PAC10 0.61 0.82 0.71 0.29 312 YPL079W RPL21B 0.14 1.28 0.71 0.29 313 YBL016W FUS3 0.63 0.79 0.71 0.29 314 YER155C BEM2 0.95 0.48 0.71 0.29 315 YNL084C END3 1.20 0.23 0.71 0.29 316 YDL023C  0.70 0.73 0.71 0.29 317 YMR126C  0.71 0.72 0.72 0.29 318 YGR036C CAX4 0.95 0.48 0.72 0.29 319 YPL101W ELP4 0.71 0.72 0.72 0.29 320 YOR036W PEP12 0.72  0.72 0.29 321 YGL012W ERG4  0.72 0.72 0.29 322 YDR368W YPR1 0.46 0.97 0.72 0.29 323 YOR016C ERP4 0.69 0.74 0.72 0.29 324 YNL004W HRB1 0.62 0.81 0.72 0.29 325 YPL239W YAR1 0.64 0.79 0.72 0.29 326 YER154W OXA1 0.75 0.69 0.72 0.29 327 YJR088C  0.64 0.80 0.72 0.28 328 YDR221W  0.79 0.65 0.72 0.28 329 YMR307W GAS1 0.74 0.71 0.72 0.28 330 YNR050C LYS9 0.72  0.72 0.28 331 YDR424C DYN2 0.31 1.14 0.72 0.28 332 YDL231C BRE4 0.86 0.58 0.72 0.28 333 YAL053W  0.56 0.89 0.72 0.28 334 YDL096C  0.68 0.76 0.72 0.28 335 YBR266C SLM6 0.48 0.97 0.72 0.28 336 YKL001C MET14 0.62 0.83 0.72 0.28 337 YJR106W ECM27 0.58 0.86 0.72 0.28 338 YFR024C- A LSB3 0.73 0.72 0.72 0.28  170 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  339 YGL198W YIP4 0.66 0.79 0.73 0.28 340 YBR248C HIS7 0.41 1.04 0.73 0.28 341 YNL294C RIM21 0.62 0.83 0.73 0.28 342 YGR143W SKN1 0.64 0.82 0.73 0.28 343 YKL072W STB6 0.73 0.73 0.73 0.28 344 YEL045C   0.73 0.73 0.28 345 YKL071W  0.72 0.73 0.73 0.28 346 YOL072W THP1 1.01 0.45 0.73 0.28 347 YLR006C SSK1 0.80 0.66 0.73 0.27 348 YJR082C EAF6 0.71 0.75 0.73 0.27 349 YBR019C GAL10 0.64 0.82 0.73 0.27 350 YLR371W ROM2 0.73  0.73 0.27 351 YJR118C ILM1 0.24 1.23 0.73 0.27 352 YPL193W RSA1 0.26 1.21 0.73 0.27 353 YDR234W LYS4 0.73  0.73 0.27 354 YER117W RPL23B 1.04 0.43 0.73 0.27 355 YER087W  0.73  0.73 0.27 356 YJR010C-A SPC1 0.53 0.94 0.73 0.27 357 YPR131C NAT3 0.89 0.58 0.73 0.27 358 YFL016C MDJ1 0.74  0.74 0.27 359 YGR058W  0.69 0.78 0.74 0.27 360 YKL139W CTK1 0.74  0.74 0.27 361 YNL198C  0.73 0.74 0.74 0.27 362 YLR262C- A  0.58 0.89 0.74 0.27 363 YKL032C IXR1 0.75 0.72 0.74 0.27 364 YOL006C TOP1 0.45 1.03 0.74 0.27 365 YLR429W CRN1 0.64 0.83 0.74 0.27 366 YNR021W  0.74 0.73 0.74 0.27 367 YML094W GIM5 0.69 0.79 0.74 0.27 368 YMR092C AIP1 0.72 0.75 0.74 0.27 369 YFL031W HAC1 0.75 0.73 0.74 0.26 370 YGL109W  0.57 0.91 0.74 0.26 371 YJL095W BCK1 0.71 0.77 0.74 0.26 372 YIR021W MRS1 1.01 0.47 0.74 0.26 373 YER187W  0.52 0.96 0.74 0.26 374 YLR320W MMS22 0.46 1.03 0.74 0.26 375 YNL050C  0.92 0.57 0.74 0.26 376 YPL226W NEW1 0.52 0.96 0.74 0.26 377 YMR289W  0.97 0.52 0.74 0.26 378 YGR254W ENO1 0.91 0.57 0.74 0.26 379 YGR138C TPO2 0.89 0.59 0.74 0.26 380 YKL160W ELF1 0.75 0.74 0.74 0.26 381 YMR074C  0.62 0.86 0.74 0.26  171 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  382 YBR235W  0.85 0.63 0.74 0.26 383 YHR114W BZZ1 0.79 0.70 0.74 0.26 384 YGR252W GCN5 0.93 0.56 0.74 0.26 385 YIL085C KTR7 0.85 0.64 0.75 0.26 386 YNL196C  0.51 0.98 0.75 0.26 387 YJR044C VPS55 0.85 0.64 0.75 0.26 388 YNL123W  0.91 0.58 0.75 0.26 389 YER069W ARG5,6 0.37 1.12 0.75 0.26 390 YJL121C RPE1 0.75 0.74 0.75 0.26 391 YDL047W SIT4 0.70 0.79 0.75 0.26 392 YJL215C  0.54 0.95 0.75 0.26 393 YJL038C  0.75  0.75 0.26 394 YCR017C CWH43 0.76 0.74 0.75 0.26 395 YDR050C TPI1 0.75  0.75 0.26 396 YOL100W PKH2 0.75  0.75 0.26 397 YJL065C DLS1 0.72 0.78 0.75 0.26 398 YGL256W ADH4 0.61 0.89 0.75 0.25 399 YLL014W  0.66 0.84 0.75 0.25 400 YKL136W  0.66 0.84 0.75 0.25 401 YJL185C  0.94 0.56 0.75 0.25 402 YNL043C  1.03 0.47 0.75 0.25 403 YLR455W  0.64 0.86 0.75 0.25 404 YNL165W  0.75  0.75 0.25 405 YBR036C CSG2 0.91 0.59 0.75 0.25 406 YBR114W RAD16 1.02 0.48 0.75 0.25 407 YER175C TMT1 0.56 0.94 0.75 0.25 408 YDR028C REG1 0.82 0.69 0.75 0.25 409 YMR242C RPL20A 0.60 0.90 0.75 0.25 410 YMR145C NDE1 0.80 0.70 0.75 0.25 411 YGR135W PRE9 0.89 0.62 0.75 0.25 412 YDL184C RPL41A 0.53 0.97 0.75 0.25 413 YBR220C  0.79 0.71 0.75 0.25 414 YLL054C  0.69 0.81 0.75 0.25 415 YPL064C CWC27 0.63 0.88 0.75 0.25 416 YDR329C PEX3 0.98 0.53 0.75 0.25 417 YNL070W TOM7 1.34 0.17 0.75 0.25 418 YPL061W ALD6 0.65 0.86 0.76 0.25 419 YOL098C  0.66 0.85 0.76 0.25 420 YJL182C  0.67 0.84 0.76 0.25 421 YBR294W SUL1 0.41 1.10 0.76 0.25 422 YOR128C ADE2 0.64 0.87 0.76 0.25 423 YKR021W  1.00 0.52 0.76 0.25 424 YNL324W  0.71 0.81 0.76 0.25 425 YKR096W  0.75 0.77 0.76 0.25  172 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  426 YOL028C YAP7 0.81 0.71 0.76 0.25 427 YFL003C MSH4 0.97 0.54 0.76 0.25 428 YGL231C  0.75 0.77 0.76 0.25 429 YPL165C SET6 0.82 0.70 0.76 0.24 430 YAL035W FUN12 0.60 0.92 0.76 0.24 431 YIL011W TIR3 0.88 0.64 0.76 0.24 432 YKL213C DOA1 0.77 0.75 0.76 0.24 433 YPR074C TKL1 0.80 0.73 0.76 0.24 434 YJR010W MET3 0.48 1.05 0.76 0.24 435 YNL148C ALF1 0.76 0.76 0.76 0.24 436 YDR293C SSD1 0.81 0.72 0.76 0.24 437 YBR059C AKL1 0.72 0.81 0.76 0.24 438 YCL058C FYV5 0.64 0.89 0.76 0.24 439 YGR023W MTL1 0.76 0.77 0.76 0.24 440 YOR002W ALG6 0.74 0.79 0.76 0.24 441 YML055W SPC2 0.75 0.78 0.76 0.24 442 YKL064W MNR2 0.81 0.72 0.76 0.24 443 YBL025W RRN10 0.86 0.67 0.76 0.24 444 YPL240C HSP82 0.49 1.04 0.76 0.24 445 YCR011C ADP1 0.73 0.80 0.77 0.24 446 YOL076W MDM20 0.77  0.77 0.24 447 YBR301W DAN3 0.52 1.01 0.77 0.24 448 YOR345C  0.56 0.97 0.77 0.24 449 YMR317W  0.77  0.77 0.24 450 YLR099C ICT1 0.56 0.97 0.77 0.24 451 YIL025C  0.85 0.68 0.77 0.24 452 YGR155W CYS4 0.77 0.76 0.77 0.24 453 YCL045C  0.81 0.73 0.77 0.24 454 YOL059W GPD2 0.80 0.74 0.77 0.24 455 YIL132C CSM2 0.86 0.68 0.77 0.24 456 YMR275C BUL1 0.82 0.72 0.77 0.24 457 YOL013C HRD1 0.76 0.78 0.77 0.24 458 YDR011W SNQ2 0.97 0.57 0.77 0.24 459 YMR148W  0.76 0.78 0.77 0.23 460 YDR265W PEX10 0.66 0.88 0.77 0.23 461 YKL066W  0.77 0.77 0.77 0.23 462 YDL076C RXT3 0.43 1.11 0.77 0.23 463 YMR179W SPT21 0.83 0.71 0.77 0.23 464 YJR105W ADO1  0.77 0.77 0.23 465 YDR071C PAA1 0.60 0.94 0.77 0.23 466 YMR027W  0.67 0.88 0.77 0.23 467 YMR241W YHM2 0.35 1.19 0.77 0.23 468 YLR386W VAC14 0.73 0.81 0.77 0.23 469 YHR087W  0.50 1.04 0.77 0.23  173 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  470 YOR130C ORT1 0.56 0.99 0.77 0.23 471 YLL047W  0.95 0.60 0.77 0.23 472 YFL032W  0.80 0.75 0.77 0.23 473 YML084W  0.62 0.93 0.77 0.23 474 YPL041C  0.49 1.06 0.77 0.23 475 YOR378W  0.73 0.82 0.77 0.23 476 YGL015C  0.49 1.07 0.78 0.23 477 YNL089C  0.69 0.86 0.78 0.23 478 YCL074W  1.00 0.55 0.78 0.23 479 YPL017C  0.55 1.00 0.78 0.23 480 YNL255C GIS2 0.93 0.62 0.78 0.23 481 YGR215W RSM27 0.72 0.84 0.78 0.23 482 YEL054C RPL12A 0.43 1.13 0.78 0.23 483 YER161C SPT2 0.72 0.83 0.78 0.23 484 YPR053C  0.62 0.93 0.78 0.23 485 YDR010C  0.86 0.69 0.78 0.23 486 YMR031C  0.71 0.84 0.78 0.23 487 YPL077C  0.77 0.78 0.78 0.23 488 YGR130C  0.78 0.77 0.78 0.23 489 YPR065W ROX1 0.81 0.74 0.78 0.23 490 YGL024W  0.92 0.63 0.78 0.23 491 YOL152W FRE7 0.60 0.96 0.78 0.23 492 YMR252C  0.56 1.00 0.78 0.23 493 YNL042W BOP3 1.20 0.36 0.78 0.22 494 YML029W USA1 0.76 0.80 0.78 0.22 495 YDR209C  0.96 0.60 0.78 0.22 496 YOL001W PHO80 0.48 1.08 0.78 0.22 497 YML083C  0.81 0.75 0.78 0.22 498 YNL192W CHS1 0.78  0.78 0.22 499 YNL299W TRF5 0.54 1.02 0.78 0.22 500 YPL139C UME1 0.78 0.79 0.78 0.22 501 YKR097W PCK1 0.77 0.79 0.78 0.22 502 YER068W MOT2 0.58 0.98 0.78 0.22 503 YFL004W VTC2 0.89 0.68 0.78 0.22 504 YGR069W  0.94 0.63 0.78 0.22 505 YJL127C SPT10 0.76 0.80 0.78 0.22 506 YPL004C LSP1 0.65 0.92 0.78 0.22 507 YLR152C  0.86 0.71 0.78 0.22 508 YPL102C  0.70 0.87 0.78 0.22 509 YNL316C PHA2 0.54 1.03 0.78 0.22 510 YER122C GLO3 0.52 1.05 0.78 0.22 511 YJL130C URA2 0.78  0.78 0.22 512 YBR141C  0.84 0.73 0.78 0.22 513 YPL262W FUM1 0.84 0.73 0.78 0.22  174 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  514 YML099C ARG81 0.65 0.92 0.78 0.22 515 YBR139W  0.82 0.75 0.79 0.22 516 YPL062W  0.82 0.75 0.79 0.22 517 YJR102C VPS25 1.24 0.33 0.79 0.22 518 YPL056C  0.61 0.97 0.79 0.22 519 YJR122W CAF17 0.79  0.79 0.22 520 YKL098W  0.67 0.90 0.79 0.22 521 YGL160W  0.78 0.80 0.79 0.22 522 YMR315W  0.59 0.99 0.79 0.22 523 YDR477W SNF1 0.79  0.79 0.22 524 YOR331C  0.79  0.79 0.22 525 YGR020C VMA7 0.79  0.79 0.22 526 YGR188C BUB1 0.90 0.68 0.79 0.21 527 YJR052W RAD7 0.67 0.91 0.79 0.21 528 YGL205W POX1 0.79  0.79 0.21 529 YHR178W STB5 0.68 0.91 0.79 0.21 530 YIL155C GUT2 0.83 0.75 0.79 0.21 531 YDR192C NUP42 0.93 0.66 0.79 0.21 532 YKL075C  0.87 0.72 0.79 0.21 533 YOR366W  0.72 0.86 0.79 0.21 534 YGR184C UBR1 0.96 0.63 0.79 0.21 535 YPR069C SPE3 0.77 0.82 0.79 0.21 536 YDR005C MAF1 0.83 0.76 0.79 0.21 537 YHR110W ERP5 0.88 0.71 0.79 0.21 538 YLR027C AAT2 0.72 0.87 0.79 0.21 539 YMR251W  0.77 0.82 0.80 0.21 540 YGR208W SER2 0.80 0.79 0.80 0.21 541 YBL044W  0.94 0.65 0.80 0.21 542 YCR053W THR4 0.61 0.98 0.80 0.21 543 YNL246W VPS75 0.84 0.75 0.80 0.21 544 YKL029C MAE1 0.69 0.90 0.80 0.21 545 YPR063C  0.85 0.74 0.80 0.21 546 YDR241W BUD26 0.85 0.75 0.80 0.21 547 YJL139C YUR1 0.76 0.84 0.80 0.21 548 YKL174C TPO5 0.81 0.78 0.80 0.21 549 YPR153W  0.84 0.76 0.80 0.21 550 YKL207W  0.83 0.76 0.80 0.21 551 YOR182C RPS30B 0.73 0.87 0.80 0.21 552 YGR260W TNA1 0.78 0.82 0.80 0.21 553 YHR003C  0.74 0.86 0.80 0.21 554 YJL071W ARG2 0.76 0.84 0.80 0.21 555 YGR154C  0.73 0.87 0.80 0.20 556 YGL246C RAI1 0.84 0.76 0.80 0.20 557 YMR154C RIM13 0.72 0.88 0.80 0.20  175 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  558 YDR525W API2 0.67 0.93 0.80 0.20 559 YDR440W DOT1  0.80 0.80 0.20 560 YPL234C TFP3 0.80  0.80 0.20 561 YCR076C  0.86 0.74 0.80 0.20 562 YOL060C MAM3 1.02 0.58 0.80 0.20 563 YER184C  0.89 0.71 0.80 0.20 564 YGR269W  0.90 0.70 0.80 0.20 565 YHR050W SMF2 0.81 0.79 0.80 0.20 566 YPR091C  0.79 0.81 0.80 0.20 567 YER176W ECM32 0.72 0.89 0.80 0.20 568 YNL250W RAD50 0.83 0.77 0.80 0.20 569 YLR226W BUR2 0.80  0.80 0.20 570 YBR023C CHS3 0.66 0.94 0.80 0.20 571 YPR166C MRP2 0.59 1.02 0.80 0.20 572 YLR354C TAL1 0.74 0.87 0.80 0.20 573 YJL027C  1.02 0.59 0.80 0.20 574 YMR123W PKR1 1.10 0.51 0.80 0.20 575 YBR201W DER1 0.80 0.81 0.80 0.20 576 YGL161C YIP5 0.87 0.74 0.80 0.20 577 YMR269W  0.96 0.65 0.80 0.20 578 YDR372C VPS74 0.64 0.97 0.81 0.20 579 YOL104C NDJ1 0.72 0.89 0.81 0.20 580 YNL325C FIG4 0.79 0.83 0.81 0.20 581 YOR288C MPD1 0.54 1.07 0.81 0.20 582 YOR285W  0.84 0.77 0.81 0.20 583 YGL174W BUD13 0.76 0.85 0.81 0.20 584 YNL010W  0.73 0.88 0.81 0.20 585 YFR034C PHO4 0.90 0.72 0.81 0.20 586 YMR316C- B  0.54 1.08 0.81 0.20 587 YLL002W RTT109 0.67 0.94 0.81 0.20 588 YIL056W  0.79 0.83 0.81 0.20 589 YNR002C ATO2 1.01 0.60 0.81 0.20 590 YOR239W ABP140 0.68 0.94 0.81 0.20 591 YLR192C HCR1 0.70 0.92 0.81 0.20 592 YGR153W  0.69 0.92 0.81 0.20 593 YDR466W PKH3 0.79 0.83 0.81 0.20 594 YDR181C SAS4 0.79 0.83 0.81 0.19 595 YGL105W ARC1 1.07 0.55 0.81 0.19 596 YHR100C  0.81  0.81 0.19 597 YLR434C  0.61 1.01 0.81 0.19 598 YMR077C VPS20 0.81  0.81 0.19 599 YJL212C OPT1 0.67 0.95 0.81 0.19 600 YOR312C RPL20B  0.81 0.81 0.19  176 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  601 YFR011C  0.97 0.65 0.81 0.19 602 YNR022C MRPL50 0.92 0.70 0.81 0.19 603 YDR360W  0.85 0.77 0.81 0.19 604 YOL016C CMK2 0.75 0.87 0.81 0.19 605 YDR289C RTT103 0.83 0.79 0.81 0.19 606 YJR131W MNS1 0.92 0.71 0.81 0.19 607 YOR267C HRK1 0.82 0.81 0.81 0.19 608 YLR325C RPL38 0.82 0.80 0.81 0.19 609 YJR107W  0.74 0.88 0.81 0.19 610 YEL042W GDA1 0.75 0.88 0.81 0.19 611 YNL009W IDP3 0.80 0.83 0.81 0.19 612 YOL093W TRM10 0.68 0.95 0.81 0.19 613 YDR315C IPK1 0.70 0.93 0.81 0.19 614 YKL025C PAN3 0.81 0.82 0.81 0.19 615 YPL070W MUK1 0.82 0.81 0.81 0.19 616 YFR043C  0.70 0.92 0.81 0.19 617 YIL038C NOT3 0.95 0.68 0.81 0.19 618 YLR207W HRD3 0.82 0.81 0.81 0.19 619 YIL139C REV7 1.05 0.58 0.81 0.19 620 YLR164W  0.90 0.73 0.81 0.19 621 YDR159W SAC3 0.85 0.78 0.81 0.19 622 YPR009W SUT2 1.09 0.54 0.81 0.19 623 YDR171W HSP42 1.04 0.59 0.81 0.19 624 YOL126C MDH2 0.68 0.95 0.82 0.19 625 YKL031W  0.84 0.79 0.82 0.19 626 YBR082C UBC4 0.90 0.73 0.82 0.19 627 YNL268W LYP1 0.76 0.88 0.82 0.19 628 YGR227W DIE2 0.82 0.81 0.82 0.19 629 YOR043W WHI2 0.74 0.90 0.82 0.19 630 YJL211C  0.74 0.90 0.82 0.19 631 YJL055W  0.67 0.97 0.82 0.19 632 YPR179C HDA3 0.78 0.85 0.82 0.19 633 YJR108W ABM1 0.78 0.85 0.82 0.19 634 YLR052W IES3 0.89 0.75 0.82 0.19 635 YDR382W RPP2B 0.62 1.02 0.82 0.19 636 YLR138W NHA1 0.95 0.69 0.82 0.19 637 YGR228W  0.94 0.70 0.82 0.19 638 YKL003C MRP17 0.82  0.82 0.19 639 YPL092W SSU1 0.59 1.05 0.82 0.19 640 YGR263C  0.88 0.76 0.82 0.19 641 YLR133W CKI1 0.34 1.30 0.82 0.19 642 YNL047C SLM2 0.81 0.83 0.82 0.19 643 YBR125C PTC4 1.00 0.64 0.82 0.19 644 YDR461W MFA1  0.82 0.82 0.19  177 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  645 YKR030W GMH1 0.97 0.67 0.82 0.19 646 YLR432W IMD3 0.71 0.93 0.82 0.18 647 YGL141W HUL5 0.88 0.76 0.82 0.18 648 YDL162C  0.87 0.77 0.82 0.18 649 YJR109C CPA2 0.85 0.79 0.82 0.18 650 YFR019W FAB1 0.95 0.69 0.82 0.18 651 YGL146C  0.68 0.96 0.82 0.18 652 YMR312W ELP6 0.77 0.87 0.82 0.18 653 YBR014C  0.68 0.96 0.82 0.18 654 YNL270C ALP1 0.51 1.13 0.82 0.18 655 YEL007W  0.82  0.82 0.18 656 YOR273C TPO4 1.08 0.56 0.82 0.18 657 YKL008C LAC1 0.73 0.92 0.82 0.18 658 YLR356W  0.70 0.94 0.82 0.18 659 YDR444W  0.98 0.66 0.82 0.18 660 YDL197C ASF2 1.01 0.64 0.82 0.18 661 YKL069W  0.86 0.79 0.82 0.18 662 YHR163W SOL3 0.50 1.15 0.82 0.18 663 YDR057W YOS9 0.78 0.87 0.82 0.18 664 YPL078C ATP4 0.78 0.87 0.82 0.18 665 YMR044W IOC4 1.02 0.63 0.82 0.18 666 YGL129C RSM23 0.96 0.69 0.82 0.18 667 YBL033C RIB1 0.49 1.16 0.82 0.18 668 YML128C MSC1 0.78 0.87 0.83 0.18 669 YPL154C PEP4 1.03 0.62 0.83 0.18 670 YBR286W APE3 0.90 0.75 0.83 0.18 671 YNL121C TOM70 0.94 0.71 0.83 0.18 672 YJL088W ARG3 0.55 1.10 0.83 0.18 673 YJL216C  0.63 1.02 0.83 0.18 674 YDR063W  0.75 0.90 0.83 0.18 675 YIL005W EPS1 0.88 0.78 0.83 0.18 676 YLR082C SRL2 0.91 0.74 0.83 0.18 677 YHR151C  0.75 0.90 0.83 0.18 678 YOR270C VPH1 0.93 0.73 0.83 0.18 679 YNL091W NST1 0.83 0.83 0.83 0.18 680 YDL128W VCX1 0.88 0.78 0.83 0.18 681 YIL133C RPL16A 0.97 0.68 0.83 0.18 682 YNL164C IBD2 0.83  0.83 0.18 683 YCL051W LRE1 0.72 0.94 0.83 0.18 684 YGL108C  0.97 0.69 0.83 0.17 685 YOR271C  1.11 0.55 0.83 0.17 686 YOR124C UBP2 0.79 0.87 0.83 0.17 687 YLR143W  0.84 0.82 0.83 0.17 688 YCL025C AGP1 0.65 1.01 0.83 0.17  178 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  689 YJL178C ATG27 0.79 0.87 0.83 0.17 690 YLL053C  0.81 0.85 0.83 0.17 691 YOR333C  0.89 0.77 0.83 0.17 692 YNL214W PEX17 0.89 0.77 0.83 0.17 693 YGR127W  1.03 0.63 0.83 0.17 694 YDL136W RPL35B 0.59 1.07 0.83 0.17 695 YJL030W MAD2 0.74 0.92 0.83 0.17 696 YJR087W  0.79 0.87 0.83 0.17 697 YEL015W EDC3 1.00 0.67 0.83 0.17 698 YPR068C HOS1 0.91 0.76 0.83 0.17 699 YAL016W TPD3 0.83  0.83 0.17 700 YAL062W GDH3 0.85 0.82 0.83 0.17 701 YDR330W UBX5 0.94 0.73 0.83 0.17 702 YDR042C  0.83 0.84 0.83 0.17 703 YJL016W  0.84 0.83 0.83 0.17 704 YNL169C PSD1 0.83  0.83 0.17 705 YGL107C RMD9 0.93 0.74 0.83 0.17 706 YJR100C  0.74 0.92 0.83 0.17 707 YNL146W  0.95 0.72 0.83 0.17 708 YBL101C ECM21 1.01 0.66 0.83 0.17 709 YBR128C ATG14 0.88 0.79 0.84 0.17 710 YER177W BMH1 0.84 0.83 0.84 0.17 711 YOR325W  0.86 0.81 0.84 0.17 712 YLR031W  0.87 0.80 0.84 0.17 713 YBR228W SLX1 1.00 0.67 0.84 0.17 714 YEL056W HAT2 0.69 0.99 0.84 0.17 715 YER179W DMC1 0.79 0.88 0.84 0.17 716 YGL126W SCS3 0.87 0.81 0.84 0.17 717 YNL040W  0.93 0.74 0.84 0.17 718 YLR384C IKI3 0.86 0.81 0.84 0.17 719 YMR026C PEX12 0.73 0.94 0.84 0.17 720 YHL011C PRS3 0.84  0.84 0.17 721 YKR028W SAP190 0.85 0.82 0.84 0.17 722 YGR261C APL6 0.77 0.90 0.84 0.17 723 YER167W BCK2 1.06 0.62 0.84 0.17 724 YHR015W MIP6 0.95 0.73 0.84 0.17 725 YER119C- A  0.82 0.86 0.84 0.17 726 YNL008C ASI3 0.77 0.91 0.84 0.17 727 YER085C  0.98 0.70 0.84 0.17 728 YML082W  0.69 0.99 0.84 0.16 729 YIL112W HOS4 0.74 0.94 0.84 0.16 730 YNR074C AIF1 0.65 1.03 0.84 0.16 731 YPL246C RBD2 0.92 0.77 0.84 0.16  179 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  732 YCL026C- A FRM2 0.64 1.04 0.84 0.16 733 YDR247W VHS1 0.84 0.84 0.84 0.16 734 YOL105C WSC3 0.75 0.93 0.84 0.16 735 YLR151C PCD1 0.94 0.74 0.84 0.16 736 YLR402W  0.86 0.82 0.84 0.16 737 YCL036W GFD2 0.77 0.91 0.84 0.16 738 YNL045W  1.02 0.66 0.84 0.16 739 YBR233W PBP2 1.01 0.68 0.84 0.16 740 YHR035W  1.21 0.48 0.84 0.16 741 YCR068W ATG15 0.87 0.82 0.84 0.16 742 YLR450W HMG2 0.75 0.93 0.84 0.16 743 YIL008W URM1 0.97 0.72 0.84 0.16 744 YOR024W  1.01 0.68 0.84 0.16 745 YPR152C  0.85 0.83 0.84 0.16 746 YAL005C SSA1 0.76 0.92 0.84 0.16 747 YNL259C ATX1 0.70 0.99 0.84 0.16 748 YLL052C AQY2 0.84 0.85 0.84 0.16 749 YGL210W YPT32 1.07 0.62 0.84 0.16 750 YLR333C RPS25B 0.70 0.98 0.84 0.16 751 YBR022W POA1 0.66 1.03 0.84 0.16 752 YMR099C  0.86 0.83 0.84 0.16 753 YMR068W AVO2 0.79 0.90 0.84 0.16 754 YMR067C UBX4 0.96 0.73 0.84 0.16 755 YPL018W CTF19 0.86 0.83 0.84 0.16 756 YPL059W GRX5 0.84  0.84 0.16 757 YLR444C  1.10 0.59 0.85 0.16 758 YHR029C YHI9 0.99 0.70 0.85 0.16 759 YDL189W RBS1 0.65 1.04 0.85 0.16 760 YDR507C GIN4  0.85 0.85 0.16 761 YAL061W  0.85 0.85 0.85 0.16 762 YPL230W  0.91 0.78 0.85 0.16 763 YOL058W ARG1 0.88 0.81 0.85 0.16 764 YBR238C  0.77 0.92 0.85 0.16 765 YBR001C NTH2 0.93 0.76 0.85 0.16 766 YER059W PCL6 0.75 0.94 0.85 0.16 767 YNL099C OCA1 0.59 1.10 0.85 0.16 768 YGR037C ACB1 0.93 0.77 0.85 0.16 769 YML058W SML1 0.75 0.94 0.85 0.16 770 YFL049W  0.84 0.86 0.85 0.16 771 YGL017W ATE1 0.88 0.82 0.85 0.16 772 YDL072C  0.89 0.81 0.85 0.16 773 YMR172W HOT1 0.68 1.02 0.85 0.16 774 YOL052C SPE2 0.72 0.98 0.85 0.16  180 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  775 YKL110C KTI12 0.84 0.85 0.85 0.16 776 YNL241C ZWF1 0.86 0.83 0.85 0.16 777 YJL172W CPS1 0.92 0.78 0.85 0.16 778 YOR129C  0.80 0.89 0.85 0.16 779 YDR069C DOA4 0.85  0.85 0.16 780 YDR273W DON1 0.68 1.01 0.85 0.16 781 YBR224W  0.98 0.71 0.85 0.16 782 YNL273W TOF1 0.85  0.85 0.16 783 YBL056W PTC3 1.00 0.70 0.85 0.16 784 YDR127W ARO1 0.76 0.93 0.85 0.16 785 YER080W  1.02 0.68 0.85 0.16 786 YDR017C KCS1 1.04 0.65 0.85 0.16 787 YDR245W MNN10 0.75 0.95 0.85 0.16 788 YGR200C ELP2 1.00 0.70 0.85 0.16 789 YDR379W RGA2 0.79 0.91 0.85 0.16 790 YBR219C  0.85 0.85 0.85 0.16 791 YEL018W EAF5  0.85 0.85 0.15 792 YLR332W MID2 0.97 0.73 0.85 0.15 793 YDL018C ERP3 0.91 0.79 0.85 0.15 794 YJL122W  0.88 0.82 0.85 0.15 795 YLR263W RED1 0.86 0.84 0.85 0.15 796 YMR302C PRP12 1.02 0.68 0.85 0.15 797 YPL222W  0.69 1.01 0.85 0.15 798 YNL296W  0.57 1.13 0.85 0.15 799 YLR199C  0.88 0.82 0.85 0.15 800 YDR290W  0.88 0.82 0.85 0.15 801 YNR008W LRO1 0.97 0.73 0.85 0.15 802 YPR026W ATH1 0.92 0.78 0.85 0.15 803 YKL070W  0.86 0.84 0.85 0.15 804 YOR137C SIA1 0.89 0.81 0.85 0.15 805 YKL168C KKQ8 0.49 1.21 0.85 0.15 806 YDR313C PIB1 0.83 0.87 0.85 0.15 807 YOR363C PI(4,5)P2 0.95 0.75 0.85 0.15 808 YOL116W MSN1 0.89 0.81 0.85 0.15 809 YDL239C ADY3 0.90 0.80 0.85 0.15 810 YGR125W  1.09 0.61 0.85 0.15 811 YDR015C  1.01 0.69 0.85 0.15 812 YOL064C MET22 1.03 0.68 0.85 0.15 813 YBL107C  0.78 0.92 0.85 0.15 814 YGR212W SLI1 0.85 0.86 0.85 0.15 815 YJR110W YMR1 0.93 0.78 0.85 0.15 816 YDR043C NRG1 0.86 0.84 0.85 0.15 817 YEL023C  0.96 0.75 0.85 0.15 818 YPR188C MLC2 0.67 1.04 0.85 0.15  181 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  819 YHR041C SRB2 0.27 1.44 0.85 0.15 820 YKL047W  0.52 1.19 0.86 0.15 821 YFR010W UBP6 0.99 0.72 0.86 0.15 822 YPR060C ARO7 0.87 0.84 0.86 0.15 823 YGR229C SMI1 1.00 0.71 0.86 0.15 824 YDR323C PEP7 0.73 0.98 0.86 0.15 825 YLR242C ARV1 0.79 0.92 0.86 0.15 826 YDL238C GUD1 0.85 0.86 0.86 0.15 827 YNL155W  0.95 0.76 0.86 0.15 828 YLR146C SPE4 1.04 0.67 0.86 0.15 829 YJL210W PEX2 0.79 0.93 0.86 0.15 830 YDR470C UGO1 0.71 1.00 0.86 0.15 831 YGR123C PPT1 0.98 0.73 0.86 0.15 832 YLR191W PEX13 0.90 0.81 0.86 0.15 833 YGL079W  0.89 0.83 0.86 0.15 834 YJL082W IML2 0.84 0.88 0.86 0.15 835 YMR025W CSI1 0.74 0.98 0.86 0.15 836 YPL054W LEE1 0.68 1.03 0.86 0.15 837 YCR045C  0.97 0.74 0.86 0.15 838 YOL044W PEX15 0.93 0.78 0.86 0.15 839 YDR048C  0.59 1.13 0.86 0.15 840 YGR163W GTR2 0.84 0.87 0.86 0.15 841 YMR297W PRC1 1.01 0.70 0.86 0.15 842 YOL099C  0.77 0.95 0.86 0.15 843 YKL027W  0.85 0.87 0.86 0.15 844 YGL133W ITC1 0.81 0.91 0.86 0.15 845 YLR046C  0.92 0.80 0.86 0.15 846 YNL044W YIP3 1.02 0.70 0.86 0.15 847 YMR316W DIA1 0.74 0.97 0.86 0.15 848 YMR284W YKU70 0.97 0.75 0.86 0.15 849 YEL062W NPR2 0.84 0.88 0.86 0.15 850 YMR195W ICY1 1.00 0.72 0.86 0.15 851 YDR099W BMH2 0.89 0.83 0.86 0.14 852 YEL068C  0.67 1.05 0.86 0.14 853 YPR132W RPS23B 0.91 0.81 0.86 0.14 854 YLL007C  1.07 0.65 0.86 0.14 855 YDR024W FYV1 0.47 1.25 0.86 0.14 856 YJL161W  0.89 0.83 0.86 0.14 857 YER182W  0.98 0.74 0.86 0.14 858 YNL265C IST1 0.86  0.86 0.14 859 YNL275W  0.72 1.01 0.86 0.14 860 YGL144C ROG1 0.82 0.90 0.86 0.14 861 YDR257C SET7 0.80 0.93 0.86 0.14 862 YGL244W RTF1 0.86  0.86 0.14  182 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  863 YER111C SWI4 0.82 0.91 0.86 0.14 864 YJR084W CSN12 0.69 1.03 0.86 0.14 865 YGL242C  0.99 0.73 0.86 0.14 866 YEL071W DLD3 0.65 1.08 0.86 0.14 867 YHL017W  0.92 0.80 0.86 0.14 868 YCR024C- A PMP1 0.78 0.95 0.86 0.14 869 YPR046W MCM16 1.02 0.70 0.86 0.14 870 YEL009C GCN4 0.72 1.00 0.86 0.14 871 YNL100W  0.58 1.15 0.86 0.14 872 YIL105C SLM1 0.87 0.86 0.86 0.14 873 YLR351C NIT3 0.95 0.78 0.86 0.14 874 YGR137W  1.10 0.63 0.86 0.14 875 YJR015W  0.91 0.82 0.86 0.14 876 YGR063C SPT4 0.99 0.74 0.86 0.14 877 YFR032C  0.87 0.86 0.86 0.14 878 YOL057W  1.08 0.65 0.86 0.14 879 YDR264C AKR1 0.87  0.87 0.14 880 YGR088W CTT1 0.83 0.91 0.87 0.14 881 YER144C UBP5 0.85 0.88 0.87 0.14 882 YGR170W PSD2 0.84 0.90 0.87 0.14 883 YBR262C  0.88 0.85 0.87 0.14 884 YJR094W- A RPL43B 1.16 0.57 0.87 0.14 885 YNL225C CNM67 0.87  0.87 0.14 886 YEL025C  1.00 0.73 0.87 0.14 887 YLR296W  0.86 0.87 0.87 0.14 888 YJR031C GEA1 0.86 0.88 0.87 0.14 889 YPL208W RKM1 0.74 0.99 0.87 0.14 890 YOR078W BUD21 0.72 1.01 0.87 0.14 891 YNL315C ATP11 0.45 1.29 0.87 0.14 892 YIL140W AXL2 0.97 0.77 0.87 0.14 893 YBR226C  0.91 0.82 0.87 0.14 894 YOR032C HMS1 0.86 0.88 0.87 0.14 895 YDR184C ATC1 0.98 0.76 0.87 0.14 896 YOL103W ITR2 0.78 0.96 0.87 0.14 897 YGR223C HSV2 0.90 0.83 0.87 0.14 898 YDR249C  0.73 1.00 0.87 0.14 899 YMR022W QRI8 0.84 0.90 0.87 0.14 900 YJR119C  0.72 1.02 0.87 0.14 901 YOL125W  0.87  0.87 0.14 902 YCR089W FIG2 0.80 0.94 0.87 0.14 903 YMR081C ISF1 0.98 0.75 0.87 0.14 904 YFR040W SAP155 0.88 0.85 0.87 0.14  183 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  905 YPL223C GRE1 0.75 0.99 0.87 0.14 906 YBR065C ECM2 0.86 0.87 0.87 0.14 907 YLR154C RNH203 0.97 0.77 0.87 0.14 908 YNR075W COS10 0.74 1.00 0.87 0.14 909 YGR235C  0.76 0.98 0.87 0.14 910 YDR009W GAL3 0.94 0.80 0.87 0.14 911 YPR079W MRL1 0.91 0.83 0.87 0.13 912 YPL112C PEX25 0.68 1.06 0.87 0.13 913 YKR041W  0.79 0.95 0.87 0.13 914 YEL066W HPA3 0.78 0.96 0.87 0.13 915 YAL058W CNE1 0.90 0.84 0.87 0.13 916 YNL136W EAF7 0.67 1.07 0.87 0.13 917 YKL090W CUE2 0.93 0.81 0.87 0.13 918 YDR479C PEX29 0.81 0.93 0.87 0.13 919 YPL159C PET20 0.96 0.78 0.87 0.13 920 YBR230C  1.06 0.68 0.87 0.13 921 YAL067C SEO1 0.78 0.96 0.87 0.13 922 YLR098C CHA4 0.83 0.91 0.87 0.13 923 YNL012W SPO1 0.79 0.96 0.87 0.13 924 YER010C  0.63 1.11 0.87 0.13 925 YOR379C  0.85 0.90 0.87 0.13 926 YBR176W ECM31 0.63 1.11 0.87 0.13 927 YKR007W MEH1 0.95 0.79 0.87 0.13 928 YLR324W PEX30 0.94 0.80 0.87 0.13 929 YOR028C CIN5 0.95 0.79 0.87 0.13 930 YDR250C  0.70 1.04 0.87 0.13 931 YLL061W MMP1 1.09 0.66 0.87 0.13 932 YER001W MNN1 0.77 0.98 0.87 0.13 933 YEL014C  1.05 0.70 0.87 0.13 934 YDR443C SSN2 0.52 1.23 0.87 0.13 935 YDR203W  1.15 0.60 0.87 0.13 936 YCL035C GRX1 0.98 0.76 0.87 0.13 937 YLR353W BUD8 0.68 1.07 0.87 0.13 938 YGL173C KEM1 0.63 1.12 0.87 0.13 939 YFR044C  0.89 0.86 0.87 0.13 940 YGL059W  0.95 0.80 0.87 0.13 941 YDR421W ARO80 0.80 0.95 0.87 0.13 942 YPL084W BRO1 0.87  0.87 0.13 943 YPR156C TPO3 0.92 0.83 0.87 0.13 944 YLR461W PAU4 0.96 0.79 0.87 0.13 945 YLL056C  0.95 0.80 0.87 0.13 946 YIL162W SUC2 0.88  0.88 0.13 947 YHR200W RPN10 0.82 0.93 0.88 0.13 948 YDR539W  0.96 0.79 0.88 0.13  184 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  949 YGR266W  0.96 0.79 0.88 0.13 950 YAL020C ATS1 0.75 1.00 0.88 0.13 951 YOR276W CAF20 0.67 1.08 0.88 0.13 952 YDR217C RAD9 0.71 1.04 0.88 0.13 953 YGR164W  0.81 0.94 0.88 0.13 954 YPR151C SUE1 0.78 0.97 0.88 0.13 955 YIL141W  1.01 0.74 0.88 0.13 956 YMR189W GCV2 0.88 0.88 0.88 0.13 957 YKL026C GPX1 0.89 0.87 0.88 0.13 958 YDL149W ATG9 0.93 0.82 0.88 0.13 959 YMR062C ECM40 0.88  0.88 0.13 960 YML075C HMG1 0.86 0.89 0.88 0.13 961 YKL005C BYE1 0.85 0.90 0.88 0.13 962 YMR262W  0.73 1.02 0.88 0.13 963 YOR292C  0.89 0.86 0.88 0.13 964 YHR184W SSP1 0.76 1.00 0.88 0.13 965 YDR377W ATP17 1.05 0.70 0.88 0.13 966 YNL291C MID1 0.69 1.07 0.88 0.13 967 YGR248W SOL4 0.92 0.84 0.88 0.13 968 YAL065C  0.84 0.91 0.88 0.13 969 YMR036C MIH1 0.76 1.00 0.88 0.13 970 YGL025C PGD1 0.95 0.81 0.88 0.13 971 YGR118W RPS23A 0.84 0.92 0.88 0.13 972 YHR018C ARG4 1.06 0.70 0.88 0.13 973 YML122C  0.88 0.88 0.88 0.13 974 YDL012C  0.87 0.89 0.88 0.12 975 YLR032W RAD5 0.90 0.86 0.88 0.12 976 YBR084W MIS1 0.76 1.00 0.88 0.12 977 YNL001W DOM34 0.71 1.05 0.88 0.12 978 YIL002C INP51 0.95 0.81 0.88 0.12 979 YKR044W UIP5 0.93 0.83 0.88 0.12 980 YPL216W  0.89 0.88 0.88 0.12 981 YOR132W VPS17 0.68 1.08 0.88 0.12 982 YJL170C ASG7 1.07 0.70 0.88 0.12 983 YKL067W YNK1 1.02 0.74 0.88 0.12 984 YER005W YND1 0.75 1.01 0.88 0.12 985 YGL208W SIP2 0.88 0.89 0.88 0.12 986 YGR015C  0.93 0.83 0.88 0.12 987 YGL261C  0.76 1.00 0.88 0.12 988 YIR004W DJP1 0.88  0.88 0.12 989 YPL021W ECM23 1.07 0.70 0.88 0.12 990 YDR239C  0.96 0.81 0.88 0.12 991 YPL111W CAR1 0.80 0.96 0.88 0.12 992 YER097W  0.77 1.00 0.88 0.12  185 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  993 YPL155C KIP2 1.12 0.65 0.88 0.12 994 YJL214W HXT8 0.72 1.04 0.88 0.12 995 YPL156C PRM4 1.02 0.74 0.88 0.12 996 YLL055W  0.93 0.84 0.88 0.12 997 YFR038W  1.17 0.59 0.88 0.12 998 YAL060W BDH1 0.95 0.82 0.88 0.12 999 YGL053W PRM8 0.86 0.90 0.88 0.12 1000 YGL197W MDS3 0.86 0.91 0.88 0.12 1001 YPL058C PDR12 0.76 1.01 0.88 0.12 1002 YDR521W  0.90 0.86 0.88 0.12 1003 YOL063C  1.02 0.75 0.88 0.12 1004 YHR137W ARO9 0.92 0.85 0.88 0.12 1005 YDL091C UBX3 0.87 0.90 0.88 0.12 1006 YPR120C CLB5 0.87 0.90 0.88 0.12 1007 YLR453C RIF2 0.90 0.87 0.88 0.12 1008 YJL023C PET130 1.06 0.70 0.88 0.12 1009 YCR106W RDS1 0.91 0.86 0.88 0.12 1010 YDL167C NRP1 0.92 0.85 0.88 0.12 1011 YLR427W MAG2 0.79 0.98 0.88 0.12 1012 YOL055C THI20 1.03 0.74 0.88 0.12 1013 YBR168W PEX32 0.79 0.98 0.88 0.12 1014 YLR093C NYV1 0.87 0.90 0.88 0.12 1015 YJL037W  0.85 0.92 0.88 0.12 1016 YGR159C NSR1 0.69 1.08 0.89 0.12 1017 YKL077W  1.09 0.68 0.89 0.12 1018 YOR073W SGO1 0.96 0.81 0.89 0.12 1019 YBL091C MAP2 0.88 0.89 0.89 0.12 1020 YJR018W  0.89  0.89 0.12 1021 YGR168C  0.66 1.11 0.89 0.12 1022 YMR182C RGM1 1.06 0.71 0.89 0.12 1023 YDL204W RTN2 0.81 0.96 0.89 0.12 1024 YKL123W  0.69 1.08 0.89 0.12 1025 YDR193W  0.95 0.82 0.89 0.12 1026 YNL083W SAL1 0.90 0.88 0.89 0.12 1027 YPR149W NCE102 0.89 0.88 0.89 0.12 1028 YOR279C RFM1 0.85 0.92 0.89 0.12 1029 YJR070C LIA1 0.81 0.96 0.89 0.12 1030 YMR011W HXT2 0.88 0.89 0.89 0.12 1031 YBR025C  0.93 0.85 0.89 0.12 1032 YJL134W LCB3 0.84 0.94 0.89 0.12 1033 YLR421C RPN13 0.85 0.93 0.89 0.12 1034 YLR258W GSY2 0.99 0.79 0.89 0.12 1035 YJL043W  0.83 0.95 0.89 0.12 1036 YMR111C  0.95 0.82 0.89 0.12  186 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1037 YMR141C  1.08 0.70 0.89 0.12 1038 YLR219W MSC3 0.93 0.85 0.89 0.12 1039 YGR192C TDH3 0.96 0.82 0.89 0.12 1040 YLR074C BUD20 0.72 1.06 0.89 0.12 1041 YJR050W ISY1 0.74 1.04 0.89 0.12 1042 YJR062C NTA1 0.85 0.93 0.89 0.12 1043 YJL177W RPL17B 0.97 0.81 0.89 0.12 1044 YBL095W  0.87 0.91 0.89 0.12 1045 YER055C HIS1 0.86 0.91 0.89 0.12 1046 YGR087C PDC6 0.98 0.80 0.89 0.12 1047 YOR375C GDH1 0.95 0.83 0.89 0.12 1048 YKR055W RHO4 0.81 0.96 0.89 0.12 1049 YDR344C  0.90 0.88 0.89 0.12 1050 YMR016C SOK2 0.85 0.93 0.89 0.12 1051 YNL293W MSB3 0.87 0.91 0.89 0.12 1052 YKL184W SPE1 1.01 0.77 0.89 0.12 1053 YFR013W IOC3 0.91 0.87 0.89 0.11 1054 YMR243C ZRC1 0.74 1.04 0.89 0.11 1055 YHL013C  0.85 0.93 0.89 0.11 1056 YDL127W PCL2 0.92 0.86 0.89 0.11 1057 YML121W GTR1 0.89 0.89 0.89 0.11 1058 YJR059W PTK2 0.89 0.90 0.89 0.11 1059 YLR110C CCW12 0.80 0.98 0.89 0.11 1060 YDR262W  0.88 0.91 0.89 0.11 1061 YIL160C POT1 1.09 0.69 0.89 0.11 1062 YJL024C APS3 1.02 0.77 0.89 0.11 1063 YDR073W SNF11 0.93 0.85 0.89 0.11 1064 YLR456W  0.88 0.90 0.89 0.11 1065 YLR365W  0.72 1.06 0.89 0.11 1066 YJL007C  1.04 0.74 0.89 0.11 1067 YKL159C RCN1 0.91 0.87 0.89 0.11 1068 YGL226C- A OST5 0.94 0.84 0.89 0.11 1069 YPL213W LEA1 0.89  0.89 0.11 1070 YPR150W  0.74 1.05 0.89 0.11 1071 YOL115W PAP2 1.01 0.78 0.89 0.11 1072 YLR266C PDR8 1.12 0.67 0.89 0.11 1073 YER123W YCK3 0.81 0.98 0.89 0.11 1074 YJR039W  0.89 0.90 0.89 0.11 1075 YBL043W ECM13 0.80 0.98 0.89 0.11 1076 YBR138C  0.95 0.84 0.89 0.11 1077 YIL156W UBP7 0.92 0.87 0.89 0.11 1078 YJL137C GLG2 1.05 0.74 0.89 0.11 1079 YOR263C  0.89 0.90 0.89 0.11  187 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1080 YLR280C  0.70 1.08 0.89 0.11 1081 YDR270W CCC2 0.81 0.97 0.89 0.11 1082 YOR025W HST3 0.99 0.80 0.89 0.11 1083 YBL063W KIP1 0.96 0.82 0.89 0.11 1084 YHR158C KEL1 0.93 0.86 0.89 0.11 1085 YKL091C  1.00 0.79 0.89 0.11 1086 YPR039W  1.00 0.79 0.89 0.11 1087 YBR005W RCR1 1.05 0.74 0.89 0.11 1088 YGL218W  0.89  0.89 0.11 1089 YBR245C ISW1 0.94 0.85 0.89 0.11 1090 YER156C  0.88 0.91 0.89 0.11 1091 YIL024C  0.99 0.80 0.89 0.11 1092 YJR021C REC107 0.80 0.99 0.89 0.11 1093 YOR134W BAG7 0.81 0.98 0.89 0.11 1094 YGR027C RPS25A 1.04 0.74 0.89 0.11 1095 YBR287W  0.88 0.91 0.89 0.11 1096 YDR186C  0.96 0.83 0.90 0.11 1097 YOR229W WTM2 0.95 0.84 0.90 0.11 1098 YJL012C VTC4 0.99 0.80 0.90 0.11 1099 YPL127C HHO1 0.90 0.89 0.90 0.11 1100 YGR124W ASN2 1.03 0.76 0.90 0.11 1101 YCR077C PAT1 1.01 0.78 0.90 0.11 1102 YOL065C INP54 1.00 0.79 0.90 0.11 1103 YMR121C RPL15B 0.90 0.90 0.90 0.11 1104 YOR290C SNF2  0.90 0.90 0.11 1105 YBR204C  0.99 0.80 0.90 0.11 1106 YHL003C LAG1 0.66 1.13 0.90 0.11 1107 YMR223W UBP8 0.71 1.08 0.90 0.11 1108 YDR348C  0.83 0.97 0.90 0.11 1109 YOR286W  0.68 1.11 0.90 0.11 1110 YDR080W VPS41 0.67 1.12 0.90 0.11 1111 YPR171W BSP1 0.90 0.89 0.90 0.11 1112 YMR070W MOT3 0.87 0.92 0.90 0.11 1113 YFR032C- A RPL29 0.94 0.86 0.90 0.11 1114 YHR191C CTF8 1.07 0.73 0.90 0.11 1115 YLR017W MEU1 1.01 0.78 0.90 0.11 1116 YHR146W CRP1 0.97 0.82 0.90 0.11 1117 YOL011W PLB3 0.86 0.94 0.90 0.11 1118 YGR066C  1.02 0.78 0.90 0.11 1119 YDR269C  0.84 0.96 0.90 0.11 1120 YJL218W  0.75 1.04 0.90 0.11 1121 YLR426W  0.75 1.05 0.90 0.11 1122 YBL100C   0.90 0.90 0.11  188 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1123 YNL329C PEX6 0.94 0.86 0.90 0.11 1124 YOR029W  1.05 0.74 0.90 0.11 1125 YNL208W  0.90  0.90 0.11 1126 YBR275C RIF1 0.91 0.88 0.90 0.11 1127 YOR170W  0.96 0.84 0.90 0.11 1128 YMR078C CTF18 0.95 0.85 0.90 0.11 1129 YNR032C- A HUB1 1.04 0.76 0.90 0.11 1130 YPR092W  0.86 0.94 0.90 0.11 1131 YDR369C XRS2 0.73 1.07 0.90 0.11 1132 YPR045C  1.09 0.70 0.90 0.11 1133 YKL170W MRPL38  0.90 0.90 0.11 1134 YLR346C  0.98 0.81 0.90 0.11 1135 YOR192C  0.83 0.97 0.90 0.11 1136 YKL151C  0.83 0.97 0.90 0.11 1137 YCL047C  0.81 0.99 0.90 0.11 1138 YBL078C ATG8 0.90 0.90 0.90 0.10 1139 YOR052C  0.92 0.88 0.90 0.10 1140 YOR111W  0.78 1.02 0.90 0.10 1141 YDR524C AGE1 0.88 0.92 0.90 0.10 1142 YLR404W  0.91 0.89 0.90 0.10 1143 YPR109W  0.98 0.82 0.90 0.10 1144 YMR254C  0.75 1.05 0.90 0.10 1145 YNL029C KTR5 0.97 0.83 0.90 0.10 1146 YML079W  0.68 1.12 0.90 0.10 1147 YCL010C SGF29 0.82 0.99 0.90 0.10 1148 YLR142W PUT1 0.96 0.84 0.90 0.10 1149 YOR044W  0.83 0.97 0.90 0.10 1150 YOR177C MPC54 0.80 1.00 0.90 0.10 1151 YBL010C  0.90 0.90 0.90 0.10 1152 YHR176W FMO1 0.81 1.00 0.90 0.10 1153 YBR197C  0.92 0.88 0.90 0.10 1154 YMR319C FET4 0.83 0.98 0.90 0.10 1155 YNR027W BUD17 0.92 0.88 0.90 0.10 1156 YGL021W ALK1 0.95 0.85 0.90 0.10 1157 YCR105W ADH7 1.06 0.74 0.90 0.10 1158 YIL059C  0.96 0.85 0.90 0.10 1159 YJR150C DAN1 0.95 0.85 0.90 0.10 1160 YJR115W  1.00 0.80 0.90 0.10 1161 YOR293W RPS10A 0.71 1.09 0.90 0.10 1162 YOR230W WTM1 0.94 0.86 0.90 0.10 1163 YER180C ISC10 1.03 0.78 0.90 0.10 1164 YKL179C COY1 1.04 0.77 0.90 0.10 1165 YGL131C SNT2 0.66 1.14 0.90 0.10  189 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1166 YMR251W -A HOR7 0.81 1.00 0.90 0.10 1167 YJR035W RAD26 1.00 0.81 0.90 0.10 1168 YGL202W ARO8 0.90 0.91 0.90 0.10 1169 YGR239C PEX21 0.95 0.86 0.90 0.10 1170 YGL140C  0.89 0.92 0.90 0.10 1171 YKL107W  0.97 0.84 0.90 0.10 1172 YGL157W  0.92 0.89 0.90 0.10 1173 YMR007W  0.92 0.89 0.90 0.10 1174 YOR245C DGA1 0.88 0.93 0.90 0.10 1175 YOR184W SER1 0.90 0.91 0.90 0.10 1176 YGL152C  0.88 0.93 0.90 0.10 1177 YGL181W GTS1 0.85 0.96 0.90 0.10 1178 YGR133W PEX4 1.02 0.79 0.90 0.10 1179 YDR497C ITR1 0.96 0.84 0.90 0.10 1180 YOR306C MCH5 0.97 0.84 0.91 0.10 1181 YDR173C ARG82 0.91  0.91 0.10 1182 YDR058C TGL2 0.96 0.85 0.91 0.10 1183 YEL041W  0.81 1.00 0.91 0.10 1184 YPL170W DAP1 1.02 0.79 0.91 0.10 1185 YAR031W PRM9 0.85 0.96 0.91 0.10 1186 YIL071C PCI8 0.81 1.00 0.91 0.10 1187 YLR435W TSR2 0.73 1.08 0.91 0.10 1188 YNR024W  0.96 0.85 0.91 0.10 1189 YDL039C PRM7 0.93 0.88 0.91 0.10 1190 YMR303C ADH2 1.11 0.70 0.91 0.10 1191 YLR410W VIP1 0.85 0.96 0.91 0.10 1192 YML018C  1.02 0.80 0.91 0.10 1193 YPR018W RLF2 0.76 1.06 0.91 0.10 1194 YOL041C NOP12 0.81 1.01 0.91 0.10 1195 YER039C- A  1.20 0.62 0.91 0.10 1196 YBL104C  0.96 0.85 0.91 0.10 1197 YJL186W MNN5 1.08 0.73 0.91 0.10 1198 YLL012W YEH1 0.93 0.88 0.91 0.10 1199 YOR318C  1.00 0.82 0.91 0.10 1200 YLR104W  0.88 0.94 0.91 0.10 1201 YDL242W  1.05 0.77 0.91 0.10 1202 YBR147W  0.93 0.89 0.91 0.10 1203 YFR009W GCN20 0.92 0.89 0.91 0.10 1204 YDR482C CWC21 0.91 0.91 0.91 0.10 1205 YPL133C RDS2 0.95 0.87 0.91 0.10 1206 YBR131W CCZ1 0.91 0.91 0.91 0.10 1207 YHR021W ECM12 1.00 0.82 0.91 0.10  190 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  -A 1208 YBR227C MCX1 0.96 0.85 0.91 0.10 1209 YGL170C SPO74 0.90 0.92 0.91 0.10 1210 YOR280C FSH3 0.98 0.84 0.91 0.10 1211 YBR276C PPS1 0.94 0.88 0.91 0.10 1212 YBR222C PCS60 0.87 0.95 0.91 0.10 1213 YBL062W  1.01 0.81 0.91 0.10 1214 YNL212W VID27 0.95 0.87 0.91 0.10 1215 YER081W SER3 0.99 0.83 0.91 0.10 1216 YKL216W URA1 0.91  0.91 0.10 1217 YGR250C  1.03 0.79 0.91 0.10 1218 YDR261C EXG2 0.85 0.97 0.91 0.10 1219 YIL012W  0.99 0.83 0.91 0.10 1220 YEL008W  0.82 1.00 0.91 0.10 1221 YLR225C  0.94 0.87 0.91 0.10 1222 YFL015C  0.80 1.02 0.91 0.09 1223 YER007W PAC2 0.72 1.10 0.91 0.09 1224 YML022W APT1 0.93 0.89 0.91 0.09 1225 YJR079W  1.25 0.58 0.91 0.09 1226 YDR378C LSM6 0.44 1.39 0.91 0.09 1227 YPR022C  0.73 1.09 0.91 0.09 1228 YIL016W SNL1 1.04 0.79 0.91 0.09 1229 YKR036C CAF4 0.91 0.91 0.91 0.09 1230 YHR096C HXT5 0.91  0.91 0.09 1231 YDL214C PRR2 0.98 0.84 0.91 0.09 1232 YLR206W ENT2 1.00 0.82 0.91 0.09 1233 YBR105C VID24 0.94 0.89 0.91 0.09 1234 YDR272W GLO2 0.79 1.03 0.91 0.09 1235 YFR014C CMK1 0.87 0.96 0.91 0.09 1236 YLL021W SPA2 0.64 1.19 0.91 0.09 1237 YHR183W GND1 0.76 1.07 0.91 0.09 1238 YGR129W SYF2 1.06 0.77 0.91 0.09 1239 YBL009W  0.99 0.83 0.91 0.09 1240 YDR371W CTS2 0.87 0.96 0.91 0.09 1241 YDL086W  0.84 0.99 0.91 0.09 1242 YPL207W  0.93 0.90 0.91 0.09 1243 YMR259C  0.83 0.99 0.91 0.09 1244 YDL130W RPP1B 0.95 0.88 0.91 0.09 1245 YML042W CAT2 1.11 0.72 0.91 0.09 1246 YBR078W ECM33 0.95 0.87 0.91 0.09 1247 YDL186W  0.70 1.13 0.91 0.09 1248 YDR007W TRP1 0.98 0.85 0.91 0.09 1249 YHL039W  0.96 0.87 0.91 0.09 1250 YNL289W PCL1 0.86 0.97 0.91 0.09  191 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1251 YNL190W  0.94 0.89 0.91 0.09 1252 YLR437C  1.01 0.82 0.91 0.09 1253 YDR363W -A SEM1 0.90 0.92 0.91 0.09 1254 YBR046C ZTA1 1.01 0.82 0.91 0.09 1255 YMR034C  0.77 1.06 0.91 0.09 1256 YLR299W ECM38 0.75 1.07 0.91 0.09 1257 YDR251W PAM1 0.99 0.84 0.91 0.09 1258 YDR003W RCR2 1.02 0.81 0.91 0.09 1259 YHR086W NAM8 0.93 0.90 0.91 0.09 1260 YPL152W RRD2 0.98 0.85 0.91 0.09 1261 YGL071W RCS1 0.89 0.94 0.91 0.09 1262 YML095C RAD10 0.84 0.99 0.91 0.09 1263 YDL206W   0.91 0.91 0.09 1264 YDR283C GCN2 0.84 0.99 0.91 0.09 1265 YLR213C CRR1 1.03 0.80 0.92 0.09 1266 YJL208C NUC1 0.79 1.04 0.92 0.09 1267 YNL125C ESBP6 0.87 0.96 0.92 0.09 1268 YGR070W ROM1 0.86 0.97 0.92 0.09 1269 YEL040W UTR2 0.89 0.94 0.92 0.09 1270 YDR210W  1.12 0.71 0.92 0.09 1271 YBR169C SSE2 0.80 1.03 0.92 0.09 1272 YPL130W SPO19 0.97 0.86 0.92 0.09 1273 YKL121W  0.79 1.04 0.92 0.09 1274 YGR096W TPC1 0.73 1.10 0.92 0.09 1275 YCL042W  0.97 0.86 0.92 0.09 1276 YLR220W CCC1 0.94 0.89 0.92 0.09 1277 YFR012W  0.70 1.13 0.92 0.09 1278 YDR112W  0.79 1.04 0.92 0.09 1279 YNL015W PBI2 0.75 1.09 0.92 0.09 1280 YDR486C VPS60 0.78 1.05 0.92 0.09 1281 YLR454W  0.94 0.89 0.92 0.09 1282 YFL052W  0.81 1.03 0.92 0.09 1283 YDR271C  0.71 1.12 0.92 0.09 1284 YDR219C  0.97 0.87 0.92 0.09 1285 YJL064W  1.04 0.80 0.92 0.09 1286 YLR335W NUP2 0.80 1.04 0.92 0.09 1287 YNL176C  0.77 1.07 0.92 0.09 1288 YNL028W  1.10 0.74 0.92 0.09 1289 YEL064C AVT2 0.87 0.96 0.92 0.09 1290 YIL173W VTH1 0.89 0.94 0.92 0.09 1291 YNL027W CRZ1 1.06 0.78 0.92 0.09 1292 YLL060C GTT2 1.08 0.75 0.92 0.09 1293 YHR123W EPT1 0.83 1.00 0.92 0.09  192 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1294 YDR152W GIR2 0.97 0.87 0.92 0.09 1295 YJR090C GRR1  0.92 0.92 0.09 1296 YPL162C  1.04 0.79 0.92 0.09 1297 YJL217W  0.75 1.09 0.92 0.09 1298 YDR176W NGG1 0.70 1.14 0.92 0.09 1299 YJL066C MPM1 0.96 0.88 0.92 0.09 1300 YBR054W YRO2 0.93 0.90 0.92 0.09 1301 YPR184W GDB1 0.83 1.01 0.92 0.09 1302 YOR084W  0.99 0.85 0.92 0.09 1303 YLR072W  0.98 0.86 0.92 0.09 1304 YAL059W ECM1 0.95 0.89 0.92 0.09 1305 YPL068C  0.88 0.95 0.92 0.08 1306 YOL107W  0.73 1.11 0.92 0.08 1307 YIR001C SGN1 1.00 0.84 0.92 0.08 1308 YPR174C  0.77 1.07 0.92 0.08 1309 YEL003W GIM4 0.93 0.91 0.92 0.08 1310 YOR108W LEU9 1.03 0.81 0.92 0.08 1311 YBR107C IML3 1.06 0.78 0.92 0.08 1312 YHL040C ARN1 0.92 0.92 0.92 0.08 1313 YDL020C RPN4 0.97 0.87 0.92 0.08 1314 YPR172W  0.77 1.07 0.92 0.08 1315 YKR105C  0.83 1.01 0.92 0.08 1316 YKL190W CNB1 1.06 0.78 0.92 0.08 1317 YBR074W  0.97 0.87 0.92 0.08 1318 YLR372W SUR4 0.84 1.00 0.92 0.08 1319 YML131W  1.04 0.80 0.92 0.08 1320 YDR408C ADE8 0.92 0.92 0.92 0.08 1321 YLL059C  1.02 0.83 0.92 0.08 1322 YCR043C  0.93 0.91 0.92 0.08 1323 YHR033W  1.04 0.80 0.92 0.08 1324 YJR124C  1.04 0.81 0.92 0.08 1325 YOR231W MKK1 0.96 0.88 0.92 0.08 1326 YGL243W TAD1 0.91 0.94 0.92 0.08 1327 YDR185C  1.09 0.75 0.92 0.08 1328 YDR068W DOS2 0.91 0.94 0.92 0.08 1329 YDR231C COX20 0.70 1.14 0.92 0.08 1330 YJL135W  0.99 0.86 0.92 0.08 1331 YDL106C PHO2 0.94 0.90 0.92 0.08 1332 YML047C PRM6 0.95 0.89 0.92 0.08 1333 YJL184W GON7 0.92  0.92 0.08 1334 YJR025C BNA1 0.92 0.93 0.92 0.08 1335 YGR182C  0.91 0.93 0.92 0.08 1336 YMR310C  0.95 0.90 0.92 0.08 1337 YBR263W SHM1 0.98 0.86 0.92 0.08  193 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1338 YGR011W  1.01 0.83 0.92 0.08 1339 YPL115C BEM3 0.93 0.91 0.92 0.08 1340 YDR459C  0.89 0.95 0.92 0.08 1341 YBR225W  0.92 0.92 0.92 0.08 1342 YDR198C  1.05 0.80 0.92 0.08 1343 YMR214W SCJ1 0.82 1.02 0.92 0.08 1344 YDR445C  0.90 0.95 0.92 0.08 1345 YLR118C  0.98 0.87 0.92 0.08 1346 YLL026W HSP104 0.93 0.92 0.92 0.08 1347 YBR162C TOS1 1.02 0.83 0.92 0.08 1348 YML013W SEL1 1.04 0.80 0.92 0.08 1349 YDR370C  0.92 0.92 0.92 0.08 1350 YJL169W  0.93 0.91 0.92 0.08 1351 YHR113W  0.90 0.95 0.92 0.08 1352 YFL047W RGD2 0.93 0.91 0.92 0.08 1353 YOL092W  0.81 1.04 0.92 0.08 1354 YEL011W GLC3 0.83 1.02 0.92 0.08 1355 YER110C KAP123 0.64 1.20 0.92 0.08 1356 YMR247C  0.90 0.94 0.92 0.08 1357 YMR161W HLJ1 0.90 0.94 0.92 0.08 1358 YER044C ERG28 0.92  0.92 0.08 1359 YMR226C  0.88 0.97 0.92 0.08 1360 YJL106W IME2 1.03 0.82 0.92 0.08 1361 YLR111W  0.89 0.96 0.92 0.08 1362 YHR022C  1.06 0.79 0.92 0.08 1363 YPL026C SKS1 0.74 1.11 0.92 0.08 1364 YER088C DOT6 0.91 0.93 0.92 0.08 1365 YLR049C  0.94 0.91 0.92 0.08 1366 YDL095W PMT1 0.72 1.13 0.92 0.08 1367 YMR144W  1.05 0.80 0.92 0.08 1368 YBR035C PDX3 0.92  0.92 0.08 1369 YIL054W  1.05 0.80 0.92 0.08 1370 YBR291C CTP1 0.89 0.96 0.92 0.08 1371 YMR205C PFK2 0.93  0.93 0.08 1372 YOR058C ASE1 0.98 0.87 0.93 0.08 1373 YMR053C STB2 0.88 0.97 0.93 0.08 1374 YJR153W PGU1 0.92 0.93 0.93 0.08 1375 YGL121C GPG1 1.10 0.75 0.93 0.08 1376 YMR127C SAS2 0.91 0.94 0.93 0.08 1377 YDR179C CSN9 0.95 0.90 0.93 0.08 1378 YGR196C FYV8 0.96 0.89 0.93 0.08 1379 YJL200C  0.76 1.09 0.93 0.08 1380 YNL234W  0.93  0.93 0.08 1381 YBR085W AAC3 0.87 0.98 0.93 0.08  194 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1382 YMR175W SIP18 0.89 0.96 0.93 0.08 1383 YCL040W GLK1 0.97 0.88 0.93 0.08 1384 YNL326C PFA3 0.91 0.94 0.93 0.08 1385 YLR304C ACO1 1.02 0.84 0.93 0.08 1386 YFR026C  1.09 0.77 0.93 0.08 1387 YDL168W SFA1 1.00 0.85 0.93 0.08 1388 YJR133W XPT1 1.06 0.80 0.93 0.08 1389 YBR015C MNN2 0.75 1.11 0.93 0.08 1390 YBR200W BEM1 0.93 0.93 0.93 0.08 1391 YDR263C DIN7 0.79 1.07 0.93 0.08 1392 YGR122C- A  1.13 0.73 0.93 0.08 1393 YDR326C  1.05 0.81 0.93 0.08 1394 YJL168C SET2 0.89 0.96 0.93 0.08 1395 YMR258C  0.69 1.17 0.93 0.08 1396 YIL138C TPM2 1.17 0.69 0.93 0.08 1397 YDR034C LYS14 0.93  0.93 0.08 1398 YNL300W  0.74 1.12 0.93 0.08 1399 YLR137W  1.11 0.74 0.93 0.08 1400 YML003W  0.86 0.99 0.93 0.08 1401 YMR318C ADH6 0.85 1.01 0.93 0.08 1402 YGR202C PCT1 0.79 1.07 0.93 0.08 1403 YPL080C  0.75 1.11 0.93 0.08 1404 YGR017W  1.03 0.83 0.93 0.08 1405 YMR244W  0.79 1.06 0.93 0.08 1406 YEL016C NPP2 1.03 0.83 0.93 0.08 1407 YGL235W  0.93 0.93 0.93 0.08 1408 YNR004W  1.07 0.79 0.93 0.07 1409 YDR253C MET32 0.97 0.89 0.93 0.07 1410 YMR110C  1.00 0.86 0.93 0.07 1411 YLR228C ECM22 0.93  0.93 0.07 1412 YKR098C UBP11 0.94 0.92 0.93 0.07 1413 YDR333C  0.98 0.88 0.93 0.07 1414 YER075C PTP3 1.14 0.72 0.93 0.07 1415 YER087C- A  1.10 0.76 0.93 0.07 1416 YIL013C PDR11 1.10 0.76 0.93 0.07 1417 YJR024C  0.86 1.00 0.93 0.07 1418 YLR044C PDC1 1.04 0.82 0.93 0.07 1419 YDR535C  0.90 0.96 0.93 0.07 1420 YKR092C SRP40 0.59 1.27 0.93 0.07 1421 YOL061W PRS5 0.95 0.92 0.93 0.07 1422 YLR265C NEJ1 1.06 0.80 0.93 0.07 1423 YBR130C SHE3 1.11 0.75 0.93 0.07  195 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1424 YGL086W MAD1 0.92 0.94 0.93 0.07 1425 YDR096W GIS1 0.87 0.99 0.93 0.07 1426 YKL076C PSY1 1.06 0.80 0.93 0.07 1427 YOR018W ROD1 0.82 1.04 0.93 0.07 1428 YEL017C- A PMP2 1.07 0.79 0.93 0.07 1429 YPL257W  0.85 1.01 0.93 0.07 1430 YLR297W  0.88 0.98 0.93 0.07 1431 YDL022W GPD1 0.91 0.96 0.93 0.07 1432 YBL068W PRS4 0.91 0.95 0.93 0.07 1433 YIR016W  0.96 0.90 0.93 0.07 1434 YNL013C  0.77 1.09 0.93 0.07 1435 YGR268C HUA1 1.09 0.77 0.93 0.07 1436 YAL036C RBG1 0.87 1.00 0.93 0.07 1437 YJR135C MCM22 0.79 1.07 0.93 0.07 1438 YLR224W  0.97 0.90 0.93 0.07 1439 YBR264C YPT10 1.00 0.86 0.93 0.07 1440 YKR040C  0.93 0.93 0.93 0.07 1441 YKL146W AVT3 0.98 0.88 0.93 0.07 1442 YAR029W  0.80 1.06 0.93 0.07 1443 YOR093C  0.79 1.07 0.93 0.07 1444 YDL190C UFD2 0.71 1.16 0.93 0.07 1445 YLR352W  1.07 0.79 0.93 0.07 1446 YNL332W THI12 1.02 0.84 0.93 0.07 1447 YHL035C  0.98 0.89 0.93 0.07 1448 YGR275W RTT102 0.83 1.03 0.93 0.07 1449 YKR093W PTR2 0.75 1.11 0.93 0.07 1450 YAL004W  0.86 1.01 0.93 0.07 1451 YDR380W ARO10 1.00 0.87 0.93 0.07 1452 YLL023C  0.77 1.09 0.93 0.07 1453 YML102W CAC2 0.84 1.02 0.93 0.07 1454 YNL055C POR1 0.62 1.25 0.93 0.07 1455 YNL195C  0.84 1.03 0.93 0.07 1456 YOL075C  0.87 1.00 0.93 0.07 1457 YCR007C  0.96 0.90 0.93 0.07 1458 YNL304W YPT11 0.86 1.01 0.93 0.07 1459 YKL044W  1.02 0.85 0.93 0.07 1460 YJL165C HAL5 0.93 0.94 0.93 0.07 1461 YPR084W  0.69 1.17 0.93 0.07 1462 YLR433C CNA1 0.82 1.05 0.93 0.07 1463 YER040W GLN3 0.84 1.03 0.93 0.07 1464 YMR142C RPL13B 0.73 1.14 0.94 0.07 1465 YOL136C PFK27 0.94 0.93 0.94 0.07 1466 YGR053C  0.99 0.88 0.94 0.07  196 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1467 YLR034C SMF3 0.95 0.92 0.94 0.07 1468 YDL171C GLT1 0.85 1.03 0.94 0.07 1469 YOR296W  0.90 0.97 0.94 0.07 1470 YBR043C QDR3 0.87 1.00 0.94 0.07 1471 YOL003C  1.02 0.85 0.94 0.07 1472 YFR035C  1.02 0.85 0.94 0.07 1473 YNR071C  0.72 1.16 0.94 0.07 1474 YPL033C  0.94 0.94 0.94 0.07 1475 YGR019W UGA1 0.94 0.94 0.94 0.07 1476 YBL094C  0.96 0.92 0.94 0.07 1477 YDL054C MCH1 0.94 0.94 0.94 0.07 1478 YOR059C  0.94 0.93 0.94 0.07 1479 YJL199C MBB1 0.89 0.98 0.94 0.07 1480 YDR540C  0.95 0.92 0.94 0.07 1481 YEL047C  0.95 0.92 0.94 0.07 1482 YLR282C  1.02 0.85 0.94 0.07 1483 YEL037C RAD23 0.98 0.90 0.94 0.07 1484 YLL058W  0.97 0.90 0.94 0.07 1485 YDR297W SUR2 0.95 0.92 0.94 0.07 1486 YPL220W RPL1A 0.89 0.99 0.94 0.07 1487 YMR238W DFG5 0.92 0.95 0.94 0.07 1488 YJL052W TDH1 0.97 0.90 0.94 0.07 1489 YKR091W SRL3 0.80 1.08 0.94 0.07 1490 YHR207C SET5 0.94 0.93 0.94 0.07 1491 YJL171C  1.06 0.82 0.94 0.07 1492 YMR155W  1.09 0.78 0.94 0.07 1493 YPR005C HAL1 1.00 0.88 0.94 0.07 1494 YLL046C RNP1 0.90 0.98 0.94 0.07 1495 YGL094C PAN2 0.91 0.97 0.94 0.07 1496 YKL034W TUL1 0.94 0.94 0.94 0.07 1497 YIL001W  1.01 0.87 0.94 0.07 1498 YDR467C  0.83 1.05 0.94 0.07 1499 YDR422C SIP1 0.92 0.96 0.94 0.07 1500 YML002W  0.89 0.98 0.94 0.07 1501 YIL015W BAR1 1.06 0.81 0.94 0.07 1502 YLL045C RPL8B 0.79 1.08 0.94 0.07 1503 YDR405W MRP20 0.94  0.94 0.07 1504 YGL199C  0.90 0.98 0.94 0.07 1505 YNR066C  0.97 0.91 0.94 0.07 1506 YBL003C HTA2 0.88 1.00 0.94 0.07 1507 YOL106W  0.67 1.21 0.94 0.07 1508 YBR299W MAL32 0.81 1.07 0.94 0.07 1509 YOL091W SPO21 0.80 1.08 0.94 0.07 1510 YFR055W  0.98 0.90 0.94 0.07  197 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1511 YPR003C  0.97 0.91 0.94 0.07 1512 YPR141C KAR3 1.03 0.85 0.94 0.06 1513 YLL005C SPO75 0.85 1.03 0.94 0.06 1514 YOL025W LAG2 0.81 1.07 0.94 0.06 1515 YMR294W -A  1.17 0.71 0.94 0.06 1516 YKR018C  0.79 1.09 0.94 0.06 1517 YMR255W GFD1 0.74 1.14 0.94 0.06 1518 YAL051W OAF1 0.92 0.96 0.94 0.06 1519 YNL187W  0.89 0.99 0.94 0.06 1520 YPR044C  0.72 1.16 0.94 0.06 1521 YPL053C KTR6 0.70 1.18 0.94 0.06 1522 YJL206C  0.83 1.05 0.94 0.06 1523 YKL143W LTV1 0.87 1.02 0.94 0.06 1524 YNL231C PDR16 1.07 0.81 0.94 0.06 1525 YMR163C  0.80 1.08 0.94 0.06 1526 YGR057C LST7 1.04 0.84 0.94 0.06 1527 YNL318C HXT14 1.10 0.78 0.94 0.06 1528 YGR161C RTS3 0.91 0.97 0.94 0.06 1529 YJL198W PHO90 0.91 0.97 0.94 0.06 1530 YOR360C PDE2 0.79 1.09 0.94 0.06 1531 YML038C YMD8 0.99 0.89 0.94 0.06 1532 YGL158W RCK1 0.95 0.93 0.94 0.06 1533 YHR016C YSC84 0.99 0.89 0.94 0.06 1534 YNL120C  0.95 0.93 0.94 0.06 1535 YJR080C  0.73 1.15 0.94 0.06 1536 YNL046W  1.02 0.86 0.94 0.06 1537 YAR003W SWD1 0.76 1.13 0.94 0.06 1538 YHR017W YSC83 1.02 0.87 0.94 0.06 1539 YBR115C LYS2 0.82 1.06 0.94 0.06 1540 YIL073C SPO22 0.91 0.97 0.94 0.06 1541 YDR122W KIN1 1.03 0.85 0.94 0.06 1542 YMR120C ADE17 0.89 0.99 0.94 0.06 1543 YOL151W GRE2 0.94 0.94 0.94 0.06 1544 YBR209W  0.81 1.07 0.94 0.06 1545 YDR031W  1.07 0.82 0.94 0.06 1546 YDR252W BTT1 1.00 0.88 0.94 0.06 1547 YDL241W  1.03 0.85 0.94 0.06 1548 YGR234W YHB1 0.92 0.97 0.94 0.06 1549 YNL140C  1.03 0.85 0.94 0.06 1550 YER070W RNR1 0.53 1.35 0.94 0.06 1551 YPR054W SMK1 0.83 1.06 0.94 0.06 1552 YJL132W  1.00 0.89 0.94 0.06 1553 YDR244W PEX5 0.92 0.97 0.94 0.06  198 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1554 YLR414C  0.95 0.94 0.94 0.06 1555 YNL173C MDG1 0.77 1.11 0.94 0.06 1556 YHR025W THR1 1.00 0.89 0.94 0.06 1557 YOR380W RDR1 0.96 0.92 0.94 0.06 1558 YLR234W TOP3 0.90 0.99 0.94 0.06 1559 YIL037C PRM2 0.91 0.97 0.94 0.06 1560 YNL271C BNI1 0.94  0.94 0.06 1561 YIL030C SSM4 0.97 0.92 0.94 0.06 1562 YBR295W PCA1 0.89 1.00 0.94 0.06 1563 YOR021C  1.12 0.76 0.94 0.06 1564 YAL056W GPB2 1.02 0.87 0.94 0.06 1565 YAL021C CCR4 0.94  0.94 0.06 1566 YOR264W DSE3 0.88 1.01 0.94 0.06 1567 YML053C  0.97 0.91 0.94 0.06 1568 YBR296C PHO89 0.86 1.03 0.94 0.06 1569 YBR137W  1.00 0.89 0.94 0.06 1570 YGR136W LSB1 0.97 0.92 0.94 0.06 1571 YPL253C VIK1 1.00 0.89 0.94 0.06 1572 YOR076C SKI7 0.88 1.01 0.94 0.06 1573 YLL057C JLP1 1.17 0.72 0.94 0.06 1574 YIL060W  1.15 0.73 0.94 0.06 1575 YJR137C ECM17 0.74 1.15 0.94 0.06 1576 YJL029C VPS53 0.94  0.94 0.06 1577 YBR145W ADH5 1.03 0.86 0.94 0.06 1578 YOL013W- A  0.82 1.07 0.94 0.06 1579 YJL192C SOP4 0.90 0.99 0.94 0.06 1580 YPL221W  0.86 1.03 0.94 0.06 1581 YAL066W  0.80 1.09 0.94 0.06 1582 YPL167C REV3 1.06 0.83 0.95 0.06 1583 YDR295C HDA2 0.84 1.05 0.95 0.06 1584 YKL197C PEX1 1.04 0.85 0.95 0.06 1585 YNL279W PRM1 0.77 1.12 0.95 0.06 1586 YML057W CMP2 1.15 0.74 0.95 0.06 1587 YOR381W FRE3 0.92 0.97 0.95 0.06 1588 YOL081W IRA2 1.00 0.89 0.95 0.06 1589 YGL214W  1.13 0.76 0.95 0.06 1590 YEL057C  0.87 1.02 0.95 0.06 1591 YLR443W ECM7 1.05 0.84 0.95 0.06 1592 YLR131C ACE2 0.86 1.03 0.95 0.06 1593 YNL292W PUS4 0.93 0.96 0.95 0.06 1594 YPL267W  0.91 0.98 0.95 0.06 1595 YDL117W CYK3 0.89 1.00 0.95 0.06 1596 YHR189W PTH1 0.73 1.16 0.95 0.06  199 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1597 YLR438W CAR2 1.02 0.87 0.95 0.06 1598 YOR365C  0.92 0.97 0.95 0.06 1599 YER181C  1.08 0.81 0.95 0.06 1600 YNL230C ELA1 0.90 0.99 0.95 0.06 1601 YOR223W  0.96 0.94 0.95 0.06 1602 YER071C  0.92 0.97 0.95 0.06 1603 YKL101W HSL1 0.95 0.94 0.95 0.06 1604 YDL085W NDE2 0.98 0.92 0.95 0.06 1605 YLR187W SKG3 0.97 0.93 0.95 0.06 1606 YLR364W  0.79 1.10 0.95 0.06 1607 YDL144C  0.95 0.94 0.95 0.06 1608 YKL086W SRX1 1.09 0.81 0.95 0.06 1609 YDR392W SPT3 0.63 1.26 0.95 0.06 1610 YOL124C TRM11 0.94 0.96 0.95 0.06 1611 YGR221C TOS2 1.00 0.89 0.95 0.06 1612 YFL053W DAK2 0.93 0.97 0.95 0.06 1613 YOL056W GPM3 1.04 0.86 0.95 0.06 1614 YNL335W  0.92 0.97 0.95 0.06 1615 YMR129W POM152 1.04 0.86 0.95 0.06 1616 YLR108C  0.93 0.97 0.95 0.06 1617 YGR279C SCW4 0.80 1.09 0.95 0.06 1618 YGR194C XKS1 0.95 0.94 0.95 0.06 1619 YPL067C  0.79 1.10 0.95 0.06 1620 YMR105C PGM2 0.94 0.95 0.95 0.06 1621 YCL064C CHA1 0.84 1.05 0.95 0.06 1622 YDR518W EUG1 0.90 1.00 0.95 0.06 1623 YEL017W GTT3 1.04 0.86 0.95 0.06 1624 YJL152W  0.95 0.94 0.95 0.06 1625 YKL030W  0.96 0.94 0.95 0.06 1626 YNL249C MPA43 0.93 0.97 0.95 0.06 1627 YPL149W ATG5 0.74 1.15 0.95 0.06 1628 YDR026C  0.90 0.99 0.95 0.06 1629 YNL011C  1.05 0.85 0.95 0.06 1630 YNL057W  0.85 1.05 0.95 0.06 1631 YNL078W NIS1 0.79 1.10 0.95 0.06 1632 YOR383C FIT3 1.03 0.87 0.95 0.06 1633 YOL082W ATG19 1.03 0.86 0.95 0.06 1634 YGR051C  0.94 0.96 0.95 0.06 1635 YBL065W  1.04 0.86 0.95 0.06 1636 YMR073C  0.93 0.97 0.95 0.06 1637 YKL120W OAC1 0.92 0.97 0.95 0.06 1638 YDL135C RDI1 0.91 0.98 0.95 0.06 1639 YGR003W CUL3 1.01 0.89 0.95 0.06 1640 YGR093W  0.92 0.98 0.95 0.06  200 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1641 YFR006W  0.93 0.97 0.95 0.05 1642 YGL262W  1.07 0.83 0.95 0.05 1643 YMR231W PEP5 0.95  0.95 0.05 1644 YLR181C VTA1 0.96 0.94 0.95 0.05 1645 YJL213W  0.90 1.00 0.95 0.05 1646 YJL149W  0.94 0.96 0.95 0.05 1647 YGL033W HOP2 0.82 1.08 0.95 0.05 1648 YOL122C SMF1 0.78 1.12 0.95 0.05 1649 YFL030W AGX1 0.86 1.04 0.95 0.05 1650 YDR484W VPS52 0.91 0.99 0.95 0.05 1651 YGL175C SAE2 0.84 1.06 0.95 0.05 1652 YHR181W SVP26 0.91 0.99 0.95 0.05 1653 YBR260C RGD1 1.00 0.90 0.95 0.05 1654 YNL237W YTP1 0.99 0.91 0.95 0.05 1655 YPL269W KAR9 0.93 0.97 0.95 0.05 1656 YPL125W KAP120 1.00 0.90 0.95 0.05 1657 YDR439W LRS4 0.94 0.96 0.95 0.05 1658 YAL007C ERP2 0.92 0.98 0.95 0.05 1659 YGR004W PEX31 0.99 0.91 0.95 0.05 1660 YIR039C YPS6 1.02 0.88 0.95 0.05 1661 YPL071C  0.96 0.94 0.95 0.05 1662 YNL122C  1.07 0.83 0.95 0.05 1663 YKR051W  0.89 1.01 0.95 0.05 1664 YGL110C CUE3  0.95 0.95 0.05 1665 YKL147C  0.95  0.95 0.05 1666 YNR013C PHO91 0.92 0.98 0.95 0.05 1667 YCL014W BUD3 1.10 0.81 0.95 0.05 1668 YGR139W  0.68 1.23 0.95 0.05 1669 YDR143C SAN1 0.96 0.94 0.95 0.05 1670 YPL180W TCO89 0.84 1.07 0.95 0.05 1671 YKL124W SSH4 1.03 0.87 0.95 0.05 1672 YPR021C AGC1 0.77 1.13 0.95 0.05 1673 YNL142W MEP2 1.23 0.68 0.95 0.05 1674 YOL153C  0.78 1.12 0.95 0.05 1675 YPL119C DBP1 0.97 0.93 0.95 0.05 1676 YDL114W  0.95  0.95 0.05 1677 YOR283W  0.99 0.92 0.95 0.05 1678 YKR043C  1.05 0.86 0.95 0.05 1679 YKR034W DAL80 0.94 0.97 0.95 0.05 1680 YMR295C  1.15 0.75 0.95 0.05 1681 YNL129W NRK1 1.04 0.86 0.95 0.05 1682 YOR096W RPS7A 0.19 1.71 0.95 0.05 1683 YGR025W  0.95 0.96 0.95 0.05 1684 YKR078W  0.89 1.01 0.95 0.05  201 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1685 YNL157W  1.09 0.82 0.95 0.05 1686 YDR120C TRM1 1.01 0.89 0.95 0.05 1687 YDR399W HPT1 1.04 0.87 0.95 0.05 1688 YPL055C LGE1 0.67 1.24 0.95 0.05 1689 YOR304W ISW2 1.01 0.90 0.95 0.05 1690 YOR083W WHI5 1.01 0.90 0.95 0.05 1691 YDR458C  0.89 1.02 0.95 0.05 1692 YHR028C DAP2 0.96 0.95 0.95 0.05 1693 YAL017W PSK1 0.89 1.02 0.95 0.05 1694 YIL094C LYS12 0.95  0.95 0.05 1695 YHR142W CHS7 0.92 0.98 0.95 0.05 1696 YOR080W DIA2 0.92 0.99 0.95 0.05 1697 YJL103C  1.02 0.89 0.95 0.05 1698 YOR191W RIS1 0.86 1.04 0.95 0.05 1699 YNL168C  0.82 1.09 0.95 0.05 1700 YBR278W DPB3 0.93 0.98 0.95 0.05 1701 YGL028C SCW11 0.86 1.05 0.95 0.05 1702 YPL090C RPS6A 0.63 1.28 0.95 0.05 1703 YNL020C ARK1 0.95 0.96 0.95 0.05 1704 YCR036W RBK1 0.89 1.02 0.95 0.05 1705 YPR167C MET16 0.79 1.12 0.95 0.05 1706 YNL086W  1.05 0.86 0.95 0.05 1707 YDR183W PLP1 1.05 0.86 0.95 0.05 1708 YLR095C IOC2 0.98 0.93 0.96 0.05 1709 YIR019C MUC1 1.07 0.84 0.96 0.05 1710 YOR008C- A  0.84 1.07 0.96 0.05 1711 YBL019W APN2 0.94 0.97 0.96 0.05 1712 YGL036W  0.97 0.94 0.96 0.05 1713 YGL196W  0.88 1.03 0.96 0.05 1714 YDR312W SSF2 1.03 0.88 0.96 0.05 1715 YGL090W LIF1 1.09 0.82 0.96 0.05 1716 YLR400W  0.94 0.97 0.96 0.05 1717 YBR108W  0.85 1.06 0.96 0.05 1718 YKL164C PIR1 0.95 0.96 0.96 0.05 1719 YGL248W PDE1 0.94 0.97 0.96 0.05 1720 YFL010C WWM1 1.08 0.83 0.96 0.05 1721 YOR131C  0.90 1.01 0.96 0.05 1722 YKL171W  0.98 0.94 0.96 0.05 1723 YOL131W  0.94 0.97 0.96 0.05 1724 YNL025C SSN8 0.96  0.96 0.05 1725 YDL130W -A STF1 0.94 0.97 0.96 0.05 1726 YLR134W PDC5 0.70 1.21 0.96 0.05  202 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1727 YDR340W  1.00 0.92 0.96 0.05 1728 YDR014W RAD61 1.25 0.66 0.96 0.05 1729 YLR449W FPR4 0.77 1.14 0.96 0.05 1730 YMR185W   0.96 0.96 0.05 1731 YLR179C  1.16 0.75 0.96 0.05 1732 YGR217W CCH1 0.98 0.93 0.96 0.05 1733 YNL183C NPR1 0.93 0.99 0.96 0.05 1734 YKL115C  1.07 0.85 0.96 0.05 1735 YPL247C  1.05 0.87 0.96 0.05 1736 YJL048C UBX6 1.20 0.72 0.96 0.05 1737 YIL007C NAS2 1.02 0.89 0.96 0.05 1738 YLR368W MDM30 0.69 1.22 0.96 0.05 1739 YMR010W  0.62 1.29 0.96 0.05 1740 YOL150C  0.81 1.11 0.96 0.05 1741 YIL006W YIA6 0.87 1.05 0.96 0.05 1742 YDR453C TSA2 0.94 0.98 0.96 0.05 1743 YOR042W CUE5 1.00 0.91 0.96 0.05 1744 YOR348C PUT4 1.06 0.85 0.96 0.05 1745 YBR157C ICS2 0.92 1.00 0.96 0.05 1746 YFL044C  0.94 0.97 0.96 0.05 1747 YKL140W TGL1 0.95 0.96 0.96 0.05 1748 YOR101W RAS1 0.93 0.98 0.96 0.05 1749 YCL048W SPS22 0.95 0.96 0.96 0.05 1750 YHR031C RRM3 0.95 0.97 0.96 0.05 1751 YJL157C FAR1 1.05 0.87 0.96 0.05 1752 YDR435C PPM1 0.87 1.04 0.96 0.05 1753 YKR104W  0.91 1.01 0.96 0.05 1754 YGR219W  0.89 1.02 0.96 0.05 1755 YDR537C  1.13 0.78 0.96 0.05 1756 YOR356W  1.11 0.81 0.96 0.05 1757 YMR294W JNM1 1.16 0.76 0.96 0.05 1758 YMR305C SCW10 0.86 1.06 0.96 0.05 1759 YKL218C SRY1 0.90 1.01 0.96 0.05 1760 YDR321W ASP1 0.89 1.03 0.96 0.05 1761 YGR039W  0.92 1.00 0.96 0.05 1762 YGR052W  1.00 0.92 0.96 0.05 1763 YFR036W CDC26 1.10 0.82 0.96 0.05 1764 YGL007W   0.96 0.96 0.05 1765 YBL061C SKT5 1.05 0.87 0.96 0.05 1766 YKL129C MYO3 0.97 0.95 0.96 0.05 1767 YBR047W  0.99 0.93 0.96 0.05 1768 YOR173W DCS2 0.94 0.98 0.96 0.05 1769 YER185W  0.89 1.03 0.96 0.05 1770 YPL225W  0.86 1.06 0.96 0.04  203 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1771 YLR401C DUS3 0.94 0.98 0.96 0.04 1772 YJL078C PRY3 0.90 1.02 0.96 0.04 1773 YMR173W DDR48 1.00 0.92 0.96 0.04 1774 YMR114C  0.99 0.93 0.96 0.04 1775 YBL064C PRX1 1.03 0.89 0.96 0.04 1776 YBR241C  0.98 0.94 0.96 0.04 1777 YBL096C  1.04 0.88 0.96 0.04 1778 YGR067C  0.97 0.95 0.96 0.04 1779 YDR480W DIG2 0.93 0.99 0.96 0.04 1780 YNR061C  0.94 0.98 0.96 0.04 1781 YPL206C  0.94 0.98 0.96 0.04 1782 YNL145W MFA2 1.09 0.83 0.96 0.04 1783 YKR009C FOX2 0.96 0.96 0.96 0.04 1784 YEL059W  0.93 1.00 0.96 0.04 1785 YOL014W  0.91 1.01 0.96 0.04 1786 YOR175C  0.90 1.02 0.96 0.04 1787 YPL186C UIP4 0.91 1.02 0.96 0.04 1788 YNL030W HHF2 1.09 0.83 0.96 0.04 1789 YDL210W UGA4 1.02 0.91 0.96 0.04 1790 YNL319W  0.95 0.98 0.96 0.04 1791 YOR308C SNU66 0.97 0.96 0.96 0.04 1792 YGR199W PMT6 0.99 0.93 0.96 0.04 1793 YER011W TIR1 0.78 1.14 0.96 0.04 1794 YER044C- A MEI4 1.09 0.84 0.96 0.04 1795 YMR119W ASI1 0.97 0.96 0.96 0.04 1796 YCR083W TRX3 0.96 0.97 0.96 0.04 1797 YBR071W  1.03 0.89 0.96 0.04 1798 YDR310C SUM1 1.01 0.91 0.96 0.04 1799 YNL276C  0.71 1.22 0.96 0.04 1800 YOR010C TIR2 0.96 0.97 0.96 0.04 1801 YJL126W NIT2 0.97 0.95 0.96 0.04 1802 YBL046W  0.97 0.96 0.96 0.04 1803 YIR025W MND2 1.07 0.86 0.96 0.04 1804 YPL166W  0.94 0.98 0.96 0.04 1805 YLR390W ECM19 0.95 0.98 0.96 0.04 1806 YBR261C  0.96 0.96 0.96 0.04 1807 YPL171C OYE3 1.06 0.87 0.96 0.04 1808 YDR035W ARO3 1.00 0.92 0.96 0.04 1809 YLR024C UBR2 0.85 1.07 0.96 0.04 1810 YML096W  1.00 0.93 0.96 0.04 1811 YNL253W TEX1 0.94 0.99 0.96 0.04 1812 YLR042C  0.95 0.97 0.96 0.04 1813 YMR215W GAS3 1.07 0.85 0.96 0.04  204 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1814 YMR264W CUE1 0.93 1.00 0.96 0.04 1815 YGL263W COS12 0.99 0.94 0.96 0.04 1816 YNL305C  0.81 1.11 0.96 0.04 1817 YFL063W  0.88 1.05 0.96 0.04 1818 YDL232W OST4 0.96  0.96 0.04 1819 YOR328W PDR10 0.95 0.98 0.96 0.04 1820 YJR049C UTR1 1.02 0.91 0.96 0.04 1821 YPR062W FCY1 0.92 1.01 0.96 0.04 1822 YKR039W GAP1 0.98 0.95 0.96 0.04 1823 YNR062C  0.93 1.00 0.96 0.04 1824 YJR152W DAL5 1.01 0.91 0.96 0.04 1825 YLR097C HRT3 1.02 0.91 0.96 0.04 1826 YDR469W SDC1 0.90 1.03 0.96 0.04 1827 YDL131W LYS21 1.05 0.88 0.96 0.04 1828 YNL191W  0.95 0.98 0.96 0.04 1829 YLR331C  0.96 0.97 0.96 0.04 1830 YMR153C- A  1.11 0.82 0.96 0.04 1831 YKL175W ZRT3 0.98 0.95 0.96 0.04 1832 YOR197W MCA1 1.06 0.87 0.96 0.04 1833 YCR079W  0.97 0.96 0.96 0.04 1834 YKR033C  0.97 0.96 0.97 0.04 1835 YDR307W  0.96 0.98 0.97 0.04 1836 YOR166C  1.04 0.89 0.97 0.04 1837 YGL096W TOS8 0.90 1.03 0.97 0.04 1838 YML021C UNG1 0.86 1.07 0.97 0.04 1839 YOR147W MDM32  0.97 0.97 0.04 1840 YER032W FIR1 1.06 0.87 0.97 0.04 1841 YNL032W SIW14 0.97 0.96 0.97 0.04 1842 YPL019C VTC3 1.05 0.88 0.97 0.04 1843 YOR228C  0.92 1.01 0.97 0.04 1844 YBR018C GAL7 0.87 1.06 0.97 0.04 1845 YGL228W SHE10 0.94 0.99 0.97 0.04 1846 YGR008C STF2 0.89 1.05 0.97 0.04 1847 YJR030C  1.00 0.93 0.97 0.04 1848 YOR302W  0.94 1.00 0.97 0.04 1849 YLR125W  1.10 0.84 0.97 0.04 1850 YKL092C BUD2 1.16 0.77 0.97 0.04 1851 YGL077C HNM1 0.97 0.97 0.97 0.04 1852 YNL180C RHO5 1.08 0.86 0.97 0.04 1853 YNL322C KRE1 0.97  0.97 0.04 1854 YHR014W SPO13 1.18 0.76 0.97 0.04 1855 YER086W ILV1 1.02 0.91 0.97 0.04 1856 YLL025W  0.95 0.98 0.97 0.04  205 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1857 YPL268W PLC1 1.06 0.87 0.97 0.04 1858 YIL158W  0.94 1.00 0.97 0.04 1859 YMR204C INP1 0.97 0.97 0.97 0.04 1860 YER007C- A  0.75 1.19 0.97 0.04 1861 YNR065C  1.04 0.90 0.97 0.04 1862 YDR083W RRP8 0.95 0.98 0.97 0.04 1863 YLR084C RAX2 0.98 0.95 0.97 0.04 1864 YHL047C ARN2 0.84 1.10 0.97 0.04 1865 YGR173W RBG2 1.14 0.80 0.97 0.04 1866 YOR311C HSD1 1.02 0.92 0.97 0.04 1867 YHL033C RPL8A 1.06 0.87 0.97 0.04 1868 YPL113C  0.97 0.96 0.97 0.04 1869 YOL039W RPP2A 0.93 1.01 0.97 0.04 1870 YDR533C HSP31 1.07 0.87 0.97 0.04 1871 YIR007W  1.01 0.93 0.97 0.04 1872 YGR092W DBF2 1.08 0.86 0.97 0.04 1873 YCR020C PET18 0.91 1.03 0.97 0.04 1874 YHL032C GUT1 0.98 0.95 0.97 0.04 1875 YML100W -A  0.94 0.99 0.97 0.04 1876 YPL047W SGF11 0.97 0.97 0.97 0.04 1877 YNL128W TEP1 1.02 0.92 0.97 0.04 1878 YNL227C JJJ1 0.99 0.94 0.97 0.04 1879 YPL163C SVS1 1.12 0.82 0.97 0.04 1880 YBR244W GPX2 0.97 0.97 0.97 0.04 1881 YOL128C YGK3 0.92 1.01 0.97 0.04 1882 YLR294C  0.98 0.96 0.97 0.04 1883 YOL045W PSK2 0.94 1.00 0.97 0.03 1884 YMR069W NAT4 0.93 1.01 0.97 0.03 1885 YMR234W RNH1 1.08 0.86 0.97 0.03 1886 YMR193W MRPL24 1.02 0.92 0.97 0.03 1887 YHR136C SPL2 0.99 0.95 0.97 0.03 1888 YBR203W COS111 0.91 1.03 0.97 0.03 1889 YHR156C LIN1 1.16 0.78 0.97 0.03 1890 YOR301W RAX1 0.92 1.02 0.97 0.03 1891 YGR181W TIM13 1.02 0.92 0.97 0.03 1892 YML072C TCB3 0.86 1.08 0.97 0.03 1893 YOL158C ENB1 0.90 1.04 0.97 0.03 1894 YOR190W SPR1 0.94 1.00 0.97 0.03 1895 YNL072W RNH201 1.03 0.91 0.97 0.03 1896 YKL105C  0.89 1.05 0.97 0.03 1897 YDR490C PKH1 1.02 0.92 0.97 0.03 1898 YNL323W LEM3 0.97 0.97 0.97 0.03  206 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1899 YOR183W FYV12 0.84 1.10 0.97 0.03 1900 YOL132W GAS4 0.95 0.99 0.97 0.03 1901 YER079W  1.00 0.95 0.97 0.03 1902 YDR084C TVP23 0.99 0.95 0.97 0.03 1903 YPR128C ANT1 0.95 0.99 0.97 0.03 1904 YFR015C GSY1 0.96 0.98 0.97 0.03 1905 YNL211C  0.94 1.01 0.97 0.03 1906 YOR247W SRL1 1.08 0.87 0.97 0.03 1907 YHR001W -A QCR10 0.92 1.02 0.97 0.03 1908 YCL055W KAR4 1.03 0.91 0.97 0.03 1909 YDL021W GPM2 0.79 1.15 0.97 0.03 1910 YGL089C MF(ALPH A)2 1.06 0.88 0.97 0.03 1911 YPL181W CTI6 1.01 0.94 0.97 0.03 1912 YDL083C RPS16B 0.93 1.02 0.97 0.03 1913 YBR052C  0.99 0.95 0.97 0.03 1914 YBR024W SCO2 0.81 1.14 0.97 0.03 1915 YFR056C  1.02 0.92 0.97 0.03 1916 YPL096W PNG1 0.90 1.05 0.97 0.03 1917 YML056C IMD4 0.92 1.02 0.97 0.03 1918 YBR280C  0.98 0.97 0.97 0.03 1919 YLR246W ERF2 1.04 0.90 0.97 0.03 1920 YMR194C- A  0.93 1.01 0.97 0.03 1921 YIL055C  1.07 0.87 0.97 0.03 1922 YIL009W FAA3 0.98 0.97 0.97 0.03 1923 YKR069W MET1 0.89 1.06 0.97 0.03 1924 YKL037W  0.93 1.02 0.97 0.03 1925 YCL034W LSB5 0.94 1.00 0.97 0.03 1926 YAL028W FRT2 1.04 0.90 0.97 0.03 1927 YIL096C  0.98 0.97 0.97 0.03 1928 YHL006C SHU1 0.99 0.95 0.97 0.03 1929 YIL167W SDL1 0.96 0.98 0.97 0.03 1930 YDR406W PDR15 1.02 0.93 0.97 0.03 1931 YIL166C  0.93 1.02 0.97 0.03 1932 YKL202W  1.10 0.85 0.97 0.03 1933 YDR509W  0.95 1.00 0.97 0.03 1934 YNR067C DSE4 1.01 0.94 0.97 0.03 1935 YBL051C PIN4 0.95 1.00 0.97 0.03 1936 YOL147C PEX11 0.96 0.99 0.97 0.03 1937 YIL014W MNT3 0.97  0.97 0.03 1938 YIL102C  0.98  0.98 0.03 1939 YDR151C CTH1 0.97 0.98 0.98 0.03  207 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1940 YMR178W  1.01 0.94 0.98 0.03 1941 YBR077C SLM4 1.10 0.86 0.98 0.03 1942 YOR031W CRS5 0.95 1.00 0.98 0.03 1943 YBR039W ATP3 0.98  0.98 0.03 1944 YNL134C  0.99 0.97 0.98 0.03 1945 YLR065C  0.92 1.03 0.98 0.03 1946 YKR058W GLG1 1.01 0.94 0.98 0.03 1947 YMR174C PAI3 0.98 0.97 0.98 0.03 1948 YBR300C  0.86 1.09 0.98 0.03 1949 YHR209W  1.05 0.90 0.98 0.03 1950 YML101C CUE4 1.06 0.89 0.98 0.03 1951 YMR246W FAA4 0.90 1.05 0.98 0.03 1952 YLR311C  1.02 0.94 0.98 0.03 1953 YPR002W PDH1 0.95 1.01 0.98 0.03 1954 YGR207C  1.02 0.93 0.98 0.03 1955 YPL188W POS5 0.98  0.98 0.03 1956 YGR189C CRH1 1.01 0.94 0.98 0.03 1957 YGR105W VMA21 0.98  0.98 0.03 1958 YBR250W  0.98 0.97 0.98 0.03 1959 YFL056C AAD6 0.98 0.97 0.98 0.03 1960 YER047C SAP1 0.96 1.00 0.98 0.03 1961 YAL023C PMT2 0.98 0.97 0.98 0.03 1962 YGL165C  0.94 1.02 0.98 0.03 1963 YOL163W  0.98 0.97 0.98 0.03 1964 YNL254C  1.00 0.95 0.98 0.03 1965 YNL301C RPL18B 0.99 0.96 0.98 0.03 1966 YLR068W FYV7 0.93 1.03 0.98 0.03 1967 YPL095C  0.93 1.03 0.98 0.03 1968 YPL014W  1.01 0.95 0.98 0.03 1969 YAL018C  1.10 0.85 0.98 0.03 1970 YDL088C ASM4 0.94 1.02 0.98 0.03 1971 YPR160W GPH1 1.01 0.95 0.98 0.03 1972 YDR374C  0.95 1.01 0.98 0.03 1973 YGR097W ASK10 0.99 0.97 0.98 0.03 1974 YJR011C  0.83 1.12 0.98 0.03 1975 YLL051C FRE6 0.97 0.99 0.98 0.03 1976 YLR385C SWC7 1.02 0.93 0.98 0.03 1977 YMR017W SPO20 0.99 0.97 0.98 0.03 1978 YDL066W IDP1 1.06 0.90 0.98 0.03 1979 YBL060W  1.12 0.83 0.98 0.03 1980 YKL183W LOT5 1.02 0.93 0.98 0.03 1981 YER164W CHD1 1.14 0.82 0.98 0.03 1982 YDL188C PPH22 0.99 0.97 0.98 0.03 1983 YNL074C MLF3 0.92 1.03 0.98 0.03  208 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  1984 YBL054W  1.03 0.93 0.98 0.03 1985 YKR026C GCN3 1.12 0.84 0.98 0.03 1986 YBR073W RDH54 1.00 0.96 0.98 0.03 1987 YDR206W EBS1 1.10 0.86 0.98 0.03 1988 YJL079C PRY1 0.98 0.97 0.98 0.03 1989 YOR342C  1.07 0.89 0.98 0.03 1990 YOR202W HIS3 0.95 1.01 0.98 0.03 1991 YDR475C  0.99 0.97 0.98 0.03 1992 YDR536W STL1 0.98  0.98 0.03 1993 YDR248C  0.94 1.01 0.98 0.03 1994 YDR538W PAD1 1.01 0.94 0.98 0.03 1995 YGR213C RTA1 0.80 1.16 0.98 0.03 1996 YMR086C- A  0.90 1.06 0.98 0.03 1997 YPL009C  0.99 0.97 0.98 0.03 1998 YPL008W CHL1 1.09 0.86 0.98 0.03 1999 YDR483W KRE2 0.99 0.96 0.98 0.03 2000 YOR051C  0.95 1.00 0.98 0.03 2001 YOR019W  1.21 0.75 0.98 0.03 2002 YOR359W VTS1 1.13 0.83 0.98 0.03 2003 YJL163C  1.05 0.91 0.98 0.03 2004 YIR013C GAT4 0.96 1.00 0.98 0.03 2005 YCR025C  0.91 1.05 0.98 0.03 2006 YLR227C ADY4 0.91 1.05 0.98 0.03 2007 YER046W -A  0.90 1.06 0.98 0.03 2008 YDR500C RPL37B  0.98 0.98 0.03 2009 YBR188C NTC20 0.98 0.97 0.98 0.03 2010 YDL057W  1.01 0.95 0.98 0.03 2011 YBR298C MAL31 1.05 0.91 0.98 0.03 2012 YGL258W  0.95 1.01 0.98 0.03 2013 YBR076W ECM8 0.94 1.02 0.98 0.03 2014 YDR033W MRH1 0.99 0.97 0.98 0.03 2015 YHR076W PTC7 0.97 0.99 0.98 0.03 2016 YNL321W  1.04 0.92 0.98 0.03 2017 YDR142C PEX7 1.04 0.92 0.98 0.02 2018 YKL211C TRP3 1.05 0.91 0.98 0.02 2019 YML059C NTE1 0.99 0.97 0.98 0.02 2020 YMR169C ALD3 1.00 0.96 0.98 0.02 2021 YCL016C DCC1 0.90 1.06 0.98 0.02 2022 YJR148W BAT2 0.98 0.98 0.98 0.02 2023 YDR102C  1.03 0.93 0.98 0.02 2024 YLR313C SPH1 0.98 0.98 0.98 0.02 2025 YLR357W RSC2  0.98 0.98 0.02  209 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2026 YJL181W  1.03 0.93 0.98 0.02 2027 YNL295W  1.01 0.95 0.98 0.02 2028 YER170W ADK2 1.19 0.77 0.98 0.02 2029 YDR336W  1.12 0.84 0.98 0.02 2030 YCL050C APA1 0.97 0.99 0.98 0.02 2031 YMR300C ADE4 1.29 0.67 0.98 0.02 2032 YDR061W  0.91 1.05 0.98 0.02 2033 YNL068C FKH2 1.04 0.92 0.98 0.02 2034 YER073W ALD5 0.96 1.00 0.98 0.02 2035 YMR219W ESC1 1.00 0.96 0.98 0.02 2036 YBR270C  0.94 1.03 0.98 0.02 2037 YMR152W YIM1 0.98 0.98 0.98 0.02 2038 YLL013C PUF3 0.90 1.07 0.98 0.02 2039 YER046W SPO73 1.00 0.96 0.98 0.02 2040 YMR273C ZDS1 0.99 0.97 0.98 0.02 2041 YBR242W  0.92 1.05 0.98 0.02 2042 YPR038W  0.98 0.99 0.98 0.02 2043 YHR182W  0.88 1.09 0.98 0.02 2044 YER188W  1.09 0.88 0.98 0.02 2045 YER096W SHC1 0.96 1.01 0.98 0.02 2046 YNR007C ATG3 1.23 0.73 0.98 0.02 2047 YLR286C CTS1 0.98 0.98 0.98 0.02 2048 YDR218C SPR28 1.01 0.95 0.98 0.02 2049 YDR191W HST4 1.13 0.83 0.98 0.02 2050 YMR002W  0.93 1.03 0.98 0.02 2051 YLR396C VPS33 0.86 1.10 0.98 0.02 2052 YER169W RPH1 1.17 0.80 0.98 0.02 2053 YNL143C  0.95 1.02 0.98 0.02 2054 YPL050C MNN9 1.01 0.95 0.98 0.02 2055 YHR103W SBE22 1.04 0.93 0.98 0.02 2056 YHR150W PEX28 0.91 1.06 0.98 0.02 2057 YHR112C  0.96 1.01 0.98 0.02 2058 YKL017C HCS1 0.98 0.99 0.98 0.02 2059 YBR030W  0.91 1.05 0.98 0.02 2060 YIR038C GTT1 0.99 0.98 0.98 0.02 2061 YDR436W PPZ2 0.96 1.01 0.98 0.02 2062 YDR134C  1.12 0.85 0.98 0.02 2063 YER141W COX15 0.88 1.09 0.98 0.02 2064 YNL286W CUS2 1.07 0.90 0.98 0.02 2065 YMR087W  0.91 1.06 0.98 0.02 2066 YOR185C GSP2 1.00 0.97 0.98 0.02 2067 YLR016C PML1 0.96 1.01 0.98 0.02 2068 YJL049W  1.01 0.95 0.98 0.02 2069 YJL141C YAK1 1.01 0.96 0.98 0.02  210 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2070 YPR043W RPL43A 0.78 1.19 0.98 0.02 2071 YER002W NOP16 0.88 1.08 0.98 0.02 2072 YLR079W SIC1 0.91 1.06 0.98 0.02 2073 YER051W  0.92 1.05 0.98 0.02 2074 YAL046C  0.90 1.06 0.98 0.02 2075 YJL075C  1.07 0.90 0.98 0.02 2076 YOL027C MDM38 0.65 1.32 0.98 0.02 2077 YPR115W  1.06 0.91 0.99 0.02 2078 YBR173C UMP1 0.98 0.99 0.99 0.02 2079 YJL201W ECM25 1.00 0.97 0.99 0.02 2080 YKR029C SET3 0.99 0.98 0.99 0.02 2081 YML123C PHO84 0.96 1.01 0.99 0.02 2082 YBR068C BAP2 0.96 1.01 0.99 0.02 2083 YIL135C VHS2 1.13 0.84 0.99 0.02 2084 YDL052C SLC1 0.97 1.00 0.99 0.02 2085 YKL201C MNN4 1.10 0.87 0.99 0.02 2086 YJL191W RPS14B 0.91 1.06 0.99 0.02 2087 YPR138C MEP3 1.05 0.92 0.99 0.02 2088 YBR134W  1.06 0.91 0.99 0.02 2089 YDR345C HXT3 1.06 0.91 0.99 0.02 2090 YOR324C FRT1 0.95 1.02 0.99 0.02 2091 YCR090C  0.91 1.06 0.99 0.02 2092 YMR156C TPP1 1.09 0.88 0.99 0.02 2093 YOR307C SLY41 0.92 1.06 0.99 0.02 2094 YIL028W  0.95 1.02 0.99 0.02 2095 YLR330W CHS5 1.03 0.94 0.99 0.02 2096 YNR063W  1.05 0.92 0.99 0.02 2097 YNL093W YPT53 1.07 0.91 0.99 0.02 2098 YIL153W RRD1 0.78 1.19 0.99 0.02 2099 YEL065W SIT1 0.83 1.14 0.99 0.02 2100 YMR306W FKS3 1.17 0.80 0.99 0.02 2101 YPL147W PXA1 0.96 1.02 0.99 0.02 2102 YHL026C  0.99 0.99 0.99 0.02 2103 YIL170W HXT12 1.06 0.92 0.99 0.02 2104 YPL199C  1.03 0.95 0.99 0.02 2105 YMR040W  1.03 0.95 0.99 0.02 2106 YIL064W  1.01 0.96 0.99 0.02 2107 YGR209C TRX2 0.96 1.02 0.99 0.02 2108 YGR007W MUQ1 1.05 0.92 0.99 0.02 2109 YOR049C RSB1 0.98 0.99 0.99 0.02 2110 YLR036C  1.06 0.92 0.99 0.02 2111 YLR014C PPR1 0.90 1.08 0.99 0.02 2112 YDR320C SWA2 0.87 1.10 0.99 0.02 2113 YAL034C FUN19 0.95 1.03 0.99 0.02  211 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2114 YCR085W  1.01 0.97 0.99 0.02 2115 YFR030W MET10 0.95 1.03 0.99 0.02 2116 YDL133C- A RPL41B 0.91 1.06 0.99 0.02 2117 YOL088C MPD2 0.93 1.05 0.99 0.02 2118 YOR213C SAS5 1.05 0.93 0.99 0.02 2119 YOR112W  0.93 1.05 0.99 0.02 2120 YBL075C SSA3 1.02 0.96 0.99 0.02 2121 YNR068C   0.99 0.99 0.02 2122 YJL151C SNA3 0.96 1.02 0.99 0.02 2123 YDR056C  0.99 0.99 0.99 0.02 2124 YDL123W SNA4 0.99 0.99 0.99 0.02 2125 YLR431C ATG23 0.79 1.19 0.99 0.01 2126 YLR287C- A RPS30A  0.99 0.99 0.01 2127 YPL176C  1.09 0.89 0.99 0.01 2128 YHL041W  1.07 0.91 0.99 0.01 2129 YMR135C GID8 1.16 0.82 0.99 0.01 2130 YPL182C  1.08 0.90 0.99 0.01 2131 YPL272C  0.99 0.99 0.99 0.01 2132 YPL052W OAZ1 0.82 1.16 0.99 0.01 2133 YPL116W HOS3 0.93 1.06 0.99 0.01 2134 YNL330C RPD3 0.99  0.99 0.01 2135 YOL032W  0.90 1.08 0.99 0.01 2136 YER183C FAU1 1.06 0.92 0.99 0.01 2137 YER089C PTC2 1.04 0.94 0.99 0.01 2138 YGL114W  0.94 1.04 0.99 0.01 2139 YDR258C HSP78 1.03 0.95 0.99 0.01 2140 YBR177C EHT1 1.07 0.91 0.99 0.01 2141 YDR077W SED1 1.00 0.98 0.99 0.01 2142 YJL051W  1.06 0.92 0.99 0.01 2143 YNL141W AAH1 0.89 1.09 0.99 0.01 2144 YDL203C  0.92 1.06 0.99 0.01 2145 YOR225W  0.91 1.07 0.99 0.01 2146 YJL013C MAD3 1.09 0.89 0.99 0.01 2147 YGL085W  0.98 1.00 0.99 0.01 2148 YLL042C ATG10 0.86 1.12 0.99 0.01 2149 YPR071W  0.85 1.13 0.99 0.01 2150 YER045C ACA1 0.96 1.02 0.99 0.01 2151 YGR021W  1.05 0.94 0.99 0.01 2152 YLL032C  0.98 1.00 0.99 0.01 2153 YOL084W PHM7 0.98 1.00 0.99 0.01 2154 YOL042W NGL1 0.97 1.02 0.99 0.01 2155 YHR125W  0.89 1.09 0.99 0.01  212 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2156 YIL121W QDR2 0.82 1.17 0.99 0.01 2157 YER057C HMF1 0.94 1.04 0.99 0.01 2158 YOR069W VPS5 0.91 1.07 0.99 0.01 2159 YGR086C PIL1 1.02 0.96 0.99 0.01 2160 YBR165W UBS1 0.96 1.03 0.99 0.01 2161 YGR018C  1.17 0.82 0.99 0.01 2162 YPL105C  0.97 1.02 0.99 0.01 2163 YBR269C  1.02 0.96 0.99 0.01 2164 YCL069W VBA3 0.90 1.09 0.99 0.01 2165 YOR079C ATX2 0.93 1.06 0.99 0.01 2166 YBR239C  1.00 0.99 0.99 0.01 2167 YDR078C SHU2 0.97 1.01 0.99 0.01 2168 YGL004C RPN14 1.12 0.87 0.99 0.01 2169 YNL303W  0.91 1.08 0.99 0.01 2170 YPR125W  0.95 1.03 0.99 0.01 2171 YNR073C  1.03 0.96 0.99 0.01 2172 YEL046C GLY1 0.88 1.11 0.99 0.01 2173 YHR127W  0.99 1.00 0.99 0.01 2174 YMR153W NUP53 1.11 0.88 0.99 0.01 2175 YGR001C  0.99 1.00 0.99 0.01 2176 YCR098C GIT1 0.87 1.12 0.99 0.01 2177 YDL079C MRK1 1.02 0.97 0.99 0.01 2178 YBR133C HSL7  0.99 0.99 0.01 2179 YER063W THO1 0.96 1.03 0.99 0.01 2180 YNL193W  1.05 0.94 0.99 0.01 2181 YML108W  0.91 1.08 0.99 0.01 2182 YDR420W HKR1 0.97 1.02 0.99 0.01 2183 YOR097C  0.94 1.05 0.99 0.01 2184 YLR406C RPL31B 1.02 0.97 0.99 0.01 2185 YIL058W  1.05 0.94 0.99 0.01 2186 YIL040W APQ12 0.94 1.04 0.99 0.01 2187 YMR201C RAD14 1.00 0.99 0.99 0.01 2188 YHL007C STE20  0.99 0.99 0.01 2189 YKR080W MTD1 0.97 1.02 0.99 0.01 2190 YNL334C SNO2 1.00 0.99 0.99 0.01 2191 YGR134W CAF130 0.96 1.03 0.99 0.01 2192 YKR005C  1.05 0.94 0.99 0.01 2193 YGR193C PDX1 1.12 0.87 0.99 0.01 2194 YDL049C KNH1 1.01 0.98 0.99 0.01 2195 YDL065C PEX19 1.08 0.91 0.99 0.01 2196 YDR220C  1.09 0.90 0.99 0.01 2197 YGL125W MET13 0.99  0.99 0.01 2198 YDL124W  1.00 0.99 0.99 0.01 2199 YGR032W GSC2 1.02 0.97 0.99 0.01  213 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2200 YPL177C CUP9 1.17 0.82 0.99 0.01 2201 YLR020C YEH2 0.99 1.00 0.99 0.01 2202 YBR099C  1.01 0.98 1.00 0.01 2203 YIR043C  0.93 1.06 1.00 0.01 2204 YOL089C HAL9 1.02 0.97 1.00 0.01 2205 YLR344W RPL26A 1.05 0.94 1.00 0.01 2206 YNL194C  0.97 1.02 1.00 0.01 2207 YLR376C PSY3 0.89 1.10 1.00 0.01 2208 YGL159W  0.96 1.03 1.00 0.01 2209 YLR019W PSR2 1.02 0.97 1.00 0.01 2210 YCR107W AAD3 1.03 0.96 1.00 0.01 2211 YBR288C APM3 0.91 1.09 1.00 0.01 2212 YDL040C NAT1 0.98 1.01 1.00 0.01 2213 YPL098C MGR2 0.93 1.06 1.00 0.01 2214 YDL240W LRG1 1.04 0.95 1.00 0.01 2215 YDR285W ZIP1 0.96 1.03 1.00 0.01 2216 YAL024C LTE1 0.98 1.02 1.00 0.01 2217 YIR035C  0.98 1.01 1.00 0.01 2218 YBL066C SEF1 1.00  1.00 0.01 2219 YOR015W  1.03 0.96 1.00 0.01 2220 YBR199W KTR4 1.05 0.94 1.00 0.01 2221 YER049W  0.99 1.01 1.00 0.01 2222 YML011C  1.02 0.97 1.00 0.01 2223 YBR218C PYC2 1.01 0.99 1.00 0.01 2224 YGL063W PUS2 0.96 1.03 1.00 0.01 2225 YMR190C SGS1 1.00  1.00 0.01 2226 YMR279C  1.07 0.92 1.00 0.01 2227 YDL094C  0.88 1.11 1.00 0.01 2228 YEL020C  1.14 0.86 1.00 0.01 2229 YDL125C HNT1 0.99 1.00 1.00 0.01 2230 YIL052C RPL34B 0.73 1.26 1.00 0.01 2231 YMR237W  1.06 0.93 1.00 0.01 2232 YDR502C SAM2 1.15 0.85 1.00 0.01 2233 YDL019C OSH2 1.01 0.99 1.00 0.01 2234 YOR222W ODC2 0.97 1.02 1.00 0.01 2235 YGL050W  1.06 0.94 1.00 0.01 2236 YBR101C FES1  1.00 1.00 0.01 2237 YGL132W  0.90 1.09 1.00 0.01 2238 YKR003W OSH6 1.02 0.97 1.00 0.01 2239 YJR149W  1.11 0.89 1.00 0.01 2240 YER090W TRP2 0.98 1.01 1.00 0.01 2241 YKL061W  1.01 0.98 1.00 0.01 2242 YDL074C BRE1 1.00 0.99 1.00 0.01 2243 YDL089W  0.93 1.07 1.00 0.01  214 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2244 YOL037C  1.02 0.98 1.00 0.01 2245 YNR064C  0.99 1.00 1.00 0.01 2246 YHL012W  0.93 1.06 1.00 0.01 2247 YNL175C NOP13 0.92 1.08 1.00 0.01 2248 YHR061C GIC1 1.03 0.97 1.00 0.01 2249 YGR059W SPR3 1.11 0.89 1.00 0.01 2250 YJL140W RPB4 1.00  1.00 0.01 2251 YPR118W  0.99 1.01 1.00 0.01 2252 YOL029C  1.07 0.92 1.00 0.01 2253 YKL015W PUT3 1.00 1.00 1.00 0.01 2254 YLR185W RPL37A 0.90 1.10 1.00 0.01 2255 YKR010C TOF2 0.91 1.08 1.00 0.01 2256 YKL161C  1.01 0.99 1.00 0.01 2257 YOR214C  1.09 0.91 1.00 0.01 2258 YDL027C  1.13 0.87 1.00 0.01 2259 YAR015W ADE1 1.04 0.96 1.00 0.01 2260 YKL068W NUP100 0.88 1.12 1.00 0.01 2261 YKR102W FLO10 0.93 1.07 1.00 0.01 2262 YLR271W  1.01 0.98 1.00 0.01 2263 YNL139C RLR1 1.00  1.00 0.01 2264 YBR195C MSI1 1.02 0.97 1.00 0.01 2265 YBR016W  1.01 0.99 1.00 0.01 2266 YJL162C JJJ2 1.00 0.99 1.00 0.01 2267 YLR077W  0.96 1.04 1.00 0.01 2268 YER135C  1.02 0.97 1.00 0.01 2269 YHR106W TRR2 1.08 0.92 1.00 0.01 2270 YJL196C ELO1 0.98 1.02 1.00 0.01 2271 YER035W EDC2 0.99 1.01 1.00 0.01 2272 YJR020W  0.82 1.18 1.00 0.01 2273 YDR403W DIT1 1.05 0.95 1.00 0.01 2274 YOR384W FRE5 1.09 0.91 1.00 0.01 2275 YHR104W GRE3 1.19 0.81 1.00 0.01 2276 YAL014C SYN8 1.06 0.94 1.00 0.00 2277 YPL099C  0.92 1.08 1.00 0.00 2278 YOR248W  1.03 0.97 1.00 0.00 2279 YBR041W FAT1 1.01 0.99 1.00 0.00 2280 YEL030W ECM10 0.96 1.04 1.00 0.00 2281 YGL118C  1.13 0.87 1.00 0.00 2282 YHR057C CPR2 0.96 1.04 1.00 0.00 2283 YLR334C  1.03 0.97 1.00 0.00 2284 YML051W GAL80 0.86 1.14 1.00 0.00 2285 YIL149C MLP2 0.98 1.02 1.00 0.00 2286 YER030W  1.09 0.91 1.00 0.00 2287 YOR133W EFT1 0.90 1.10 1.00 0.00  215 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2288 YNL278W CAF120 1.04 0.96 1.00 0.00 2289 YDR055W PST1 1.10 0.90 1.00 0.00 2290 YER091C- A  1.07 0.93 1.00 0.00 2291 YPL123C RNY1 1.07 0.93 1.00 0.00 2292 YJR130C STR2 0.94 1.06 1.00 0.00 2293 YOR355W GDS1 0.96 1.04 1.00 0.00 2294 YBR021W FUR4 0.88 1.12 1.00 0.00 2295 YKR060W UTP30 1.01 0.99 1.00 0.00 2296 YJL084C  1.06 0.94 1.00 0.00 2297 YJR038C  0.98 1.02 1.00 0.00 2298 YER062C HOR2 0.99 1.02 1.00 0.00 2299 YOR092W ECM3 0.94 1.07 1.00 0.00 2300 YHL028W WSC4 0.97 1.03 1.00 0.00 2301 YPL040C ISM1 1.04 0.96 1.00 0.00 2302 YLR363C NMD4 0.82 1.19 1.00 0.00 2303 YEL010W  1.09 0.92 1.00 0.00 2304 YBR205W KTR3 1.00 1.01 1.00 0.00 2305 YBR178W  1.15 0.86 1.00 0.00 2306 YKR012C  1.01 0.99 1.00 0.00 2307 YBR093C PHO5 1.19 0.81 1.00 0.00 2308 YLR194C  0.94 1.07 1.00 0.00 2309 YBR187W  0.94 1.06 1.00 0.00 2310 YOR053W  1.08 0.93 1.00 0.00 2311 YGR286C BIO2 0.97 1.03 1.00 0.00 2312 YNR060W FRE4 0.93 1.07 1.00 0.00 2313 YDL115C IWR1 1.08 0.92 1.00 0.00 2314 YBR056W  0.99 1.02 1.00 0.00 2315 YPL097W MSY1 1.00  1.00 0.00 2316 YDR428C  1.08 0.92 1.00 0.00 2317 YML005W TRM12 1.13 0.88 1.00 0.00 2318 YBR210W ERV15 1.02 0.98 1.00 0.00 2319 YER132C PMD1 1.02 0.99 1.00 0.00 2320 YOR322C LDB19 1.07 0.94 1.00 0.00 2321 YDR488C PAC11 1.03 0.98 1.00 0.00 2322 YEL028W  1.01 1.00 1.00 0.00 2323 YMR133W REC114 1.13 0.87 1.00 0.00 2324 YNL031C HHT2 1.06 0.95 1.00 0.00 2325 YGR012W  1.03 0.97 1.00 0.00 2326 YOL090W MSH2 1.00  1.00 0.00 2327 YFR046C CNN1 1.02 0.99 1.00 0.00 2328 YPL086C ELP3 1.00  1.00 0.00 2329 YKL142W MRP8 1.09 0.91 1.00 0.00 2330 YDR066C  1.08 0.92 1.00 0.00  216 Rank ORF Gene Normalized densitometry values  SCORE    MATa  MATalpha average  2331 YPR195C  1.02 0.99 1.00 0.00 2332 YDR135C YCF1 1.08 0.93 1.00 0.00 2333 YBR297W MAL33 1.02 0.98 1.00 0.00 2334 YPR076W  0.98 1.03 1.00 0.00 2335 YMR299C DYN3 1.17 0.84 1.00 0.00 2336 YIL050W PCL7 1.02 0.99 1.00 0.00 2337 YML007W YAP1 0.94 1.06 1.00 0.00 2338 YHL030W ECM29 0.95 1.06 1.00 0.00 2339 YMR210W  1.01 1.00 1.00 0.00 2340 YPL144W  1.11 0.90 1.00 0.00 2341 YGL232W TAN1 1.03 0.98 1.00 0.00 2342 YCR027C RHB1 0.94 1.07 1.00 0.00 2343 YGR236C SPG1 1.00 1.01 1.00 0.00 2344 YMR015C ERG5 0.90 1.11 1.00 0.00 2345 YDR046C BAP3 1.02 0.99 1.00 0.00   217    218 Figure A1. Full hierarchical clustering of the genetic interaction data.  Hierarchical clustering of normalized, median-centered invertase activity values of double mutant strains generated by crossing top-scoring mutants from the primary screen (array genes, y axis) to a diverse set of 81 trafficking mutants (query genes, x axis). Although 374 top-scoring mutants were used for the crosses, the heat map shows only the 307 array genes for which reliable double mutant data were obtained. Yellow indicates lower than expected levels of GSS at the cell surface, whereas blue indicates higher than expected levels. Red bars indicate representative query genes with known roles in endocytosis or recycling.                                         219    Figure A2. Characterization of LDB17 mutants and identification of Ldb17-interacting proteins. (A–C) Kymograph representations of Ldb17-GFP relative to markers Sla1-RFP (A), Myo5-RFP (B), and Abp1-RFP (C) at cortical patches over 120 s. (D) Localization of Ldb17-GFP and ldb17ΔPRD in wild-type (WT) and bzz1 cells. Bar, 2 μm. (E) Ldb17 interacts with the syndapin homologue Bzz1 through a C-terminal PRD. Proteins were immunoprecipitated from cells expressing Ldb17-myc, ldb17DPRD-myc, and/or Bzz1-HA with a-HA antibodies and detected by immunoblot analysis with either a-HA or a-myc. (F) Loss of the Ldb17 PRD or Bzz1 increases cell surface levels of the GSS reporter, as measured by liquid assay. Invertase activity is expressed as nanomole glucose  220 released per OD600 (mean of at least three experiments ± SD). (G) Summary of yeast two- hybrid interactions between Ldb17-GAL4AD and the 16 different SH3 domain–GAL4BD fusions. Interactions between Ldb17 and SH3 domains from Bzz1, Sla1, Ysc84/Lsb4, and Yfr024c/Lsb3 resulted in strong activation of the HIS3 reporter (resistant to 50 mM 3-AT). (H) PRD dependence of the yeast two-hybrid interactions. Diploid strains containing GALAD and GALBD plasmids are shown on the left; activation of the HIS3 reporter is shown on the right.                                  221 APPENDIX B: Supplemental material (chapter 3)  Table B.1. Plasmids and yeast strains used in this study  Type Name Description/Genotype Source yeast strain LCY858 can1::SRE2pr-LEU2 lyp1∆ cyh2 his3∆1 leu2∆0 ura3∆0 met15∆0 LYS2+  this study yeast strain LCY1156 LC858 apm1∆::NAT this study yeast strain LCY1154 LC858 apm2∆::NAT this study yeast strain LCY1155 LC858 ap14∆::NAT this study yeast strain LCY1141 LC858 yap1801∆::NAT this study yeast strain BY4741 MATa his3-1 leu2-0 ura3-0 this study yeast strain LC1994 BY4741 Apm2::GFP(HIS) this study yeast strain LCY1979 BY4741 Apm4::GFP(HIS) Clc1::RFP(NAT) this study yeast strain LCY1977 LCY1994 Clc1::RFP(NAT) this study yeast strain HBY155 LC1979 sla2∆ this study yeast strain LCY1978 LC1977 sla2∆ this study yeast strain LCY1997 BY4741 Apm2::GFP(HIS3) Clc1::RFP(NAT) this study yeast strain CTY708 BY4741 Apm1::RFP(KAN) Apm2::GFP(HIS3) this study yeast strain CTY603 BY4741 Apm1::RFP(KAN) Ima1::GFP(HIS3) this study yeast strain LCY2439 BY4741 Ima1::GFP(HIS3) Clc1::RFP(NAT) this study yeast strain LCY1230 BY4741 chs6∆::NAT this study yeast strain LCY3168 1230 apl2∆::KAN this study yeast strain LCY3167 1230 apm1∆::KAN this study yeast strain LCY3170 1230 apm2∆::KAN this study yeast strain LCY3202 1230 apm2∆::KAN apm1∆::URA this study yeast strain LCY3169 1230 ima1∆::KAN this study  222 Type Name Description/Genotype Source yeast strain LCY3203 1230 ima1∆::KAN apm2∆::URA this study yeast strain LCY3204 BY4741 + pNAT this study yeast strain CTY301 Ima1-GFP(HIS3) this study yeast strain CTY564 Ima1-GFP(HIS3) Apl4::3HA(KAN) this study yeast strain CTY574  Ima1::GFP(HIS3) Apl4N::HA(KAN) this study yeast strain CTY265 Ima1::GFP(HIS3) Apm1::3HA(KAN) this study yeast strain CTY661 Ima1::GFP(HIS3) Apm2::3HA(KAN) this study yeast strain pj694a MATa trp1-901 leu2-3,112 ura3-52  his3- 200 gal4∆ gal80∆ LYS::GAL1-HIS3 GAL2- ADE2 met2::GAL7-lacZ James et al., 1996a yeast strain pj694alpha MATalpha trp1-901 leu2-3,112 ura3-52  his3-200 gal4∆ gal80∆ LYS::GAL1-HIS3 GAL2-ADE2 met2::GAL7-lacZ James et al., 1996a yeast strain HBY536 pj694alpha pOBD2-Apm2 this study yeast strain HBY544 pj694alpha pOBD2-Apm2 (246-605) this study yeast strain HBY625 pj694alpha pOBD2-Apm2 (391-605) this study yeast strain NR pj694alpha pOBD2-Apm2 (389-582) this study yeast strain CTY188 pj694a pOAD-Apl4 this study yeast strain HBY539 pj694a pOAD-Ima1 this study yeast strain HBY626 pj694a pOAD-Mut5N (1-262) this study yeast strain HBY463 LCY1994 ima∆::NAT this study yeast strain HBY567 BY4741 Apm2::3HA(KAN) this study yeast strain HBY688 BY4741 Ima1::3HA(KAN) this study yeast strain LCY2210 BY4741 Ima1::GFP(HIS3) erg6∆::NAT this study yeast strain CTY286 BY4741 Apl2::GFP(HIS3) erg6∆::NAT this study  223 Type Name Description/Genotype Source yeast strain HB577 BY4741 +  GFP-Snc1-Suc2::SUC2 The GSS reporter plasmid pCS30 was linearized with XbaI and integrated at the SUC2 locus.  yeast strain SEY6210 MATa leu2-3,112  ura3-52  his3-∆200  trp1-∆901  lys2-801 suc2-∆9  Met- S. Emr yeast strain HBY596 SEY6210 GFP::SNC1(URA) this study plasmid pGST-Ima1  Open Biosystems plasmid pBG1805  Open Biosystems plasmid pNR1 pRS415-IMA1 this study plasmid pNR3 pRS415-IMACM this study plasmid pLC1329 pSec7-DsRed(URA) this study plasmid pOAD Uetz et al., 2000 gift from Stan Fields plasmid pOBD2 Uetz et al., 2000 gift from Stan Fields plasmid pCS7 SNC1-GFP in pRS316 Schluter et al., 2008b plasmid pCS30 GFP-SNC1-SUC2 in pRS306 (GSS; TPI1 promoter) Sequences from pGS (Lewis et al., 2000)c were PCR- amplified to introduce a SmaI site before the Snc1 stop codon, and subcloning this into XhoI/SmaI- digested pRS306. The resulting plasmid was digested with XbaI/SmaI, end- filled, and ligated to SUC2 sequences on a SmaI-HpaI fragment from pSEYC306 (Darsow et al., 2000)d plasmid pPPL92 pGST-SNC1 gift from Anne Spang a James, P., Halladay, J. & Craig, E. A. (1996) Genomic libraries and a host strain designed for highly efficient two- hybrid selection in yeast. Genetics 144: 1425-1436   224 b Schluter et al. Global analysis of yeast endosomal transport identifies the vps55/68 sorting complex. Mol Biol Cell (2008) vol. 19 (4) pp. 1282-94  c Lewis et al. Specific retrieval of the exocytic SNARE Snc1p from early yeast endosomes. Mol.Biol.Cell (2000) vol. 11 (1) pp. 23-38  d Darsow et al. Invertase fusion proteins for analysis of protein trafficking in yeast. Meth Enzymol (2000) vol. 327 pp. 95-106  

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