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Speciﬁc adaptations in the proteostasis network of the social amoebae Dictyostelium discoideum lead to an unusual resilience to protein aggregation

DISSERTATION

zur Erlangung des akademischen Grades Doctor rerum naturalium (Dr. rer. nat.)

vorgelegt der Fakultät Mathematik und Naturwissenschaften der Technische Universität Dresden

von Liliana Malinovska geboren am 5. Mai 1985 in Soﬁa, Bulgarien

Gutachter: Prof. Dr. Elly Tanaka Prof. Dr. Harm H. Kampinga

Eingereicht am 3. Februar 2014 Verteidigt am 29. April 2014

Erklärung entsprechend §5.5 der Promotionsordnung

Hiermit versichere ich, dass ich die vorliegende Arbeit ohne unzulässige Hilfe Dritter und ohne Benutzung anderer als der angegebenen Hilfs- mittel angefertigt habe; die aus fremden Quellen direkt oder indirekt übernommenen Gedanken sind als solche kenntlich gemacht. Die Arbeit wurde bisher weder im Inland noch im Ausland in gleicher oder ähnlicher Form einer anderen Prüfungsbehörde vorgelegt.

Die Dissertation wurde im Zeitraum vom 1. Mai 2010 bis 1. Februar 2014 verfasst und von Dr. Simon Alberti, Max Plank Institut für molekulare Zellbiologie und Genetik betreut.

Meine Person betreﬀend erkläre ich hiermit, dass keine früheren erfolg- losen Promotionsverfahren stattgefunden haben.

Ich erkenne die Promotionsordnung der Fakultät für Mathematik und Naturwissenschaften, Technische Universität Dresden an.

Dresden, den 1. Februar 2014

Na Baba

Acknowledgments

I would like to express my deep gratitude to Dr. Simon Alberti for providing this interesting and exciting project, for his patient guidance, enthu- siastic encouragements and useful critiques on this research work. I would also like to thank the members of my thesis advisory committee, Dr. Karla Neugebauer and Prof. Dr. Elly Tanaka for their valuable and constructive suggestions on this project. I am particularly grateful for the assistance given by the facilities of the MPI-CBG, especially by Britta Schroth-Diez and Jan Peychl (light microscopy facility), Kimberly Gibson and Jean Marc Verbavatz (electron microscopy facility), Holger Brandl and Ian Henry (bioinformatic core), Ina Nüsslein (FACS facility), Barbara Borgonovo (protein puriﬁcation facility) and the team of the media kitchen. I also wish to thank the Dicty community, especially Prof. Dr. Günther Gerisch (MPI München) and Dr. Annette Müller-Taubenberger (LMU), for professional guidance and valuable support; and DictyBase, for providing strains and plasmids used in this study. Furthermore, I would like to extend my thanks to all current and former members of the Alberti lab for creating a pleasant environment to work and a friendly atmosphere in the lab and during the lab adventures in the Sächsische Schweiz and at the Striezelmarkt. Finally, I would like to thank all my friends and particularly my partner Markus. Special thanks goes to my sister Alexandra and my mother for their deep support and encouragement throughout my studies. Last but not least, I would like to acknowledge my grandmother Elena Balabanova- Radonova, who inspired me and laid my way into science. She taught me what I believe are one of the most important things in scientiﬁc research: patience and dedication. Therefore, this work is dedicated to her memory.

Abstract Abstract

A key prerequisite for cellular and organismal health is a functional proteome. A variety of human protein misfolding diseases are associated with the occurrence of amyloid protein aggregates, such as amyotrophic lateral sclerosis (ALS) or Huntington’s disease. The proteins involved in disease manifestation all contain aggregation-prone sequences of low compositional complexity. Such sequences are also known as prion-like, because of their sequence similarity to yeast prions. Yeast prion proteins are a specific subset of amyloid forming proteins with distinct physio chemical and functional features, which give them transmissible properties. The aggregation properties of yeast prions and disease-related prion-like proteins reside in structurally independent, prion-forming domains (PrDs). These domains are highly enriched for uncharged polar amino acids, such as glutamine (Q) and asparagine (N). These compositional features can be used to predict prion-like proteins bioinformatically. To investigate the prevalence of prion-like proteins across different organisms, we analyzed a range of eukaryotic proteomes. Our analysis revealed that the slime mold D. discoideum contains the highest number of prion-like N/Q-rich proteins of all organisms. Based on this finding, we hypothesized that D. discoideum could be a valuable model system to study protein homeostasis (proteostasis) and the molecular basis of protein misfolding diseases. To explore how D. discoideum manages its highly aggregation-prone proteome, we analyzed the behavior of several well-characterized misfolding- prone marker proteins (variants of the disease-causing exon 1 of the huntingtin protein as well as wildtype and variant versions of the Q/N-rich yeast prion Sup35NM). Intriguingly, these proteins did not form cytosolic aggregates in D. discoideum, as they do in other organisms. Aggregates, however, formed as a result of heat stress, which indicates that the tested proteins have the capacity to aggregate, but are kept under tight control under normal conditions. Furthermore, when the stress level was reduced, the stress-induced aggregates dissolved, suggesting that D. discoideum has evolved mechanisms to reverse aggregation after a period of acute stress. Together, these findings reveal an unusual resilience of D. discoideum to aggregation-prone proteins, which very likely results from specific adaptations in its proteostasis network. By studying these specific adaptations,

i Abstract we could get important insight into the strategies that nature employs to control and maintain a highly aggregation-prone proteome. So far, our experimental investigations have revealed evidence for three specific adaptations. First, we identified the disaggregase Hsp101 as a key player in the acute stress response of D. discoideum. A functional analysis of Hsp101 in yeast and D. discoideum revealed that it supports thermotolerance. Second, we found evidence for an important role of the nucleus and nucleolus in proteostasis. We discovered that a small fraction of highly aggregation-prone proteins accumulated in the nucleus or nucleolus of D. discoideum cells. The magnitude of this nuclear accumulation could be increased by proteasome impairment, which suggests that the ubiquitin- proteasome system (UPS) is involved. This finding is consistent with previous studies in other organisms and hints at the possibility that D. discoideum disposes of aggregation-prone proteins by degrading them in the nucleus/nucleolus. Third and finally, we found that cells containing nuclear accumulations are asymmetrically distributed in the multicellular developmental stage (slug), suggesting that D. discoideum employs cell-sorting mechanisms to dispose of cells with accumulated protein damage. Although our current understanding of proteostasis in D. discoideum is preliminary, we have gained important insight into the molecular mechanisms and cellular pathways that D. discoideum uses to counteract protein aggregation. Findings from this work will inform similar comparative studies in other organisms and will impact our molecular understanding of protein misfolding diseases and aging.

protein aggregation, amyloid, molecular chaperones, proteostasis, Dic- tyostelium discoideum

ii Zusammenfassung Zusammenfassung

Eine wesentliche Voraussetzung für die Gesundheit von Zellen und Or- ganismen ist ein funktionales Proteom. Eine Reihe von humanen Protein- Missfaltungs-Erkrankungen, wie Chorea Huntington und Amyotrophe La- teralsklerose (ALS) werden mit dem Auftreten von amyloiden Protein- Aggregaten in Verbindung gebracht. Sämtliche Proteine, die in der Pathoge- nese dieser Krankheiten eine Rolle spielen, enthalten aggregations-anfällige Sequenzen mit geringer Sequenzkomplexität. Solche Sequenzen werden als Prion-ähnlich bezeichnet, da sie in ihrer Zusammensetzung den Prionen aus der Hefe S. cerevisiae gleichen. Die Prion-Proteine der Hefe gehören zu einer Unterart von amyloid-aggregierenden Proteinen, die durch bestimmte physikochemische und funktionelle Eigenschaften einen infektiösen Cha- rakter erhalten. Die Aggregations-Eigenschaften von Hefeprionen und aggregations- anfällige Proteinen, die mit Erkrankungen in Verbindung gebracht werden, basieren auf strukturell unabhängigen, Prion-bildenden Domänen (prion domain, PrD). Diese Domänen sind angereichert mit polaren Aminosäuren wie Glutamin und Asparagin. Diese Zusammensetzung kann dazu verwen- det werden prion-ähnliche Proteine bioinformatisch vorherzusagen. Um die Verbreitung von Prion-ähnlichen Proteinen in verschiedenen Organismen zu untersuchen, analysierten wir eine Reihe von eukaryotischen Proteomen. Unsere Analyse zeigte, dass der Schleimpilz D. discoideum die höchste An- zahl von Prion-ähnlichen N/Q-reichen Proteinen aufzeigt. Aufgrund dieser Erkenntisse erstellten wir die Hypothese, dass D. discoideum ein nützli- cher Modellorganismus sein könnte, um Protein Homöostase (Proteostase) sowie die molekulare Basis von Proteins-Missfaltungs-Erkrankungen zu er- gründen. Um zu analysieren, wie D. discoideum mit seinem höchst aggregations an- fälligen Proteom umgehen kann, untersuchten wir das Verhalten mehrerer bereits charakterisierter aggregations anfälliger Marker-Proteine in D. discoideum. Hierbei verwendeten wir Varianten des krankheits-erzeugenden Exon 1 des humanen Huntingtin Protein sowie den wild-typ und Varianten des N/Q-reichen Hefe Prions Sup35. Interessanterweise bildeten diese Pro- teine, anders als in anderen Organismen, keine zytosolischen Aggregate in D. discoideum aus. Aggregate wurden jedoch unter Hitzestress-Bedingungen

iii Zusammenfassung gebildet. Dies deutet darauf hin, dass die getesteten Proteine durchaus das Vermögen zu aggregieren besitzen, jedoch unter normalen Wachstumsbe- dingungen streng kontrolliert werden. Wenn, darüberhinaus das Stress- Level gesenkt wurde, kam es zur Auflösung der stress-induzierten Aggrega- te. Dies deutet darauf hin, dass D. discoideum Mechanismen entwickelt hat, um Aggregate nach Perioden von akutem Stress wieder aufzulösen. Zusam- mengenommen enthüllen diese Erkenntnisse eine ungewöhnliche Wider- standsfähigkeit gegenüber aggregations anfälligen Proteinen. Diese beruht höchstwahrscheinlich auf spezifischen Modifikationen im Proteostase Netz- werk. Durch die Analyse dieser spezifischen Anpassungen könnten wichtige Einblicke in die Strategien gewährt werden, welche die Natur benutzt, um ein höchst aggregations anfälliges Proteom zu erhalten und zu kontrol- lieren. Bisher erbrachten unsere Experimente Anhaltspunkte für drei spezifi- sche Anpassungen. Erstens zeigten wir, dass die Disaggregase Hsp101 eine Schlüsselrolle in der akuten Stressantwort in D. discoideum einnimmt. Eine funktionale Analyse von Hsp101 in D. discoideum und Hefe zeigte, dass die Disaggregase Thermotoleranz fördert. Zweitens haben wir Anhaltspunkte, dass der Nukleus und der Nukleolus eine wichtige Rolle in der Proteosta- se einnehmen. Eine geringe Fraktion der überaus aggregations anfälligen Proteine akkumuliert im Nukleus oder Nukleolus von D. discoideum. Das Ausmaß der nuklearen Akkumulation konnte erhöht werden, wenn das Proteasom beeinträchtigt wird. Dies deutet darauf hin, dass das Ubiquitin- Proteasom-System involviert sein könnte. Diese Beobachtung ist im Ein- klang mit jüngsten Berichten aus anderen Organismen und daraus folgt, dass D. discoideum möglicherweise aggregations-anfällige Proteine durch Abbau im Nukleus entsorgt. Drittens konnten wir feststellen, dass Zellen, die nukleare Akkumulationen enthalten, asymmetrisch in der multizellulä- ren Entwicklungs-Struktur des Pseudoplasmodiums verteilt sind. Dies deutet darauf hin, dass D. discoideum möglicherweise den Zellsortierungsme- chanismus während der Entwicklung nutzen kann, um Zellen mit angerei- cherten Protein-Schäden zu beseitigen. Auch wenn das gegenwärtige Verständnis der Proteostase in D. discoideum nur vorläufig ist, haben wir wichtige Einblicke in die molekularen Mechanismen und zellulären Prozesse erhalten, die D. discoideum verwen-

iv Zusammenfassung det, um Protein-Aggregation zu verhindern. Die Ergebnisse dieser Arbeit werden ähnliche vergleichende Studien in anderen Organismen beeinﬂus- sen und Auswirkungen auf unser molekulares Verständnis über Protein- Missfaltungs-Erkrankungen und das Altern haben.

Protein Aggregation, Amyloide, Moleculare Chaperone, Proteostase, Dictyostelium discoideum

v Zusammenfassung

vi Contents Contents

List of abbreviations 1

1 Introduction 3 1.1 Protein quality control ...... 3 1.1.1 The ubiquitin-proteasome system (UPS) ...... 3 1.1.2 Molecular chaperones ...... 4 1.1.2.1 The Hsp70/Hsp40 system ...... 5 1.1.2.2 Hsp100 disaggregases ...... 6 1.1.3 Cellular responses to protein aggregation ...... 8 1.2 Amyloid protein aggregation ...... 9 1.2.1 Amyloid aggregates and human diseases ...... 9 1.2.2 Yeast prion proteins ...... 11 1.2.3 Computational prediction of prion and prion-like domains ...... 13 1.3 Disctyostelium discoideum ...... 14 1.4 Aim of this study ...... 16

2 Material and Methods 19 2.1 Cell Biological Methods ...... 19 2.1.1 D. discoideum ...... 19 2.1.1.1 Maintenance ...... 19 2.1.1.2 Storage ...... 19 2.1.1.3 Transformation ...... 19 2.1.1.4 Whole-cell lysates ...... 20 2.1.1.5 Growth curves ...... 20 2.1.1.6 Development ...... 20 2.1.2 S. cerevisiae ...... 20 2.1.2.1 Maintenance ...... 20 2.1.2.2 Transformation ...... 21 2.1.2.3 Whole-cell lysates ...... 21 2.1.2.4 Red-white prion reporter assay ...... 21 2.1.2.5 Plasmid shuﬄe assay ...... 23 2.1.2.6 Mating and Tetrad dissection ...... 23 2.1.3 Mammalian cells ...... 24

vii Contents

2.1.3.1 Maintenance ...... 24 2.1.3.2 Transformation ...... 24 2.1.3.3 Whole-cell lysates ...... 24 2.1.4 E. coli ...... 25 2.2 Molecular biology ...... 25 2.2.1 Cloning ...... 25 2.2.1.1 Amplification from gDNA ...... 26 2.2.1.2 BP and LR reaction ...... 26 2.2.2 E. coli transformation ...... 26 2.2.2.1 Generation of competent cells ...... 26 2.2.2.2 Transformation ...... 27 2.2.3 Purification ...... 27 2.2.3.1 Purification of plasmid DNA ...... 27 2.2.3.2 Purification of genomic DNA from D. discoideum ...... 27 2.2.4 Restriction analysis ...... 28 2.2.5 Gel electrophoresis ...... 28 2.2.6 Site-directed mutagenesis ...... 28 2.3 Protein Chemistry ...... 29 2.3.1 SDS-PAGE ...... 29 2.3.2 SDD-AGE ...... 29 2.3.3 Western Blot ...... 29 2.3.3.1 Transfer ...... 29 2.3.3.2 Immunodetection ...... 29 2.3.4 Filter retardation assay ...... 30 2.3.5 In vitro fibril assembly ...... 30 2.3.5.1 protein expression ...... 30 2.3.5.2 In vitro assembly ...... 31 2.4 Microscopy ...... 31 2.4.1 Wide field microscopy ...... 31 2.4.1.1 Sample preparation ...... 31 2.4.1.2 Imaging ...... 32 2.4.2 Stereo microscopy ...... 32 2.4.3 FRAP ...... 32 2.4.3.1 Sample preparation ...... 32

viii Contents

2.4.3.2 Imaging ...... 32 2.4.4 Confocal microscopy ...... 33 2.4.4.1 Sample preparation ...... 33 2.4.4.2 Imaging ...... 33 2.5 Analysis ...... 33 2.5.1 HMM algorithm ...... 33 2.5.2 Enrichment analysis ...... 34 2.5.3 FRAP ...... 35 2.5.4 MSD ...... 36 2.5.5 Counting cytoslic foci/nuclear accumulates ...... 36

3 Results 37 3.1 Bioinformatic analysis of aggregation-prone proteins in D. discoideum ...... 37 3.2 Behavior of aggregation-prone proteins in D. discoideum . . . 41 3.3 Characterization of phenotypic eﬀects ...... 47 3.4 Eﬀects of heat stress on aggregation-prone proteins ...... 49 3.5 Characterization of Hsp101 function in D. discoideum . . . . 53 3.6 Characterization of Dictyostelium chaperone function in S. cerevisiae ...... 55 3.7 Characterization of nuclear accumulations ...... 58

4 Discussion 63 4.1 Asparagine- and glutamine-rich stretches are conserved and functionally relevant ...... 63 4.2 D. discoideum evolved mechanisms that render it resilient to aggregation-prone proteins ...... 64 4.2.1 Hsp101 is a key player in the acute stress response in D. discoideum ...... 65 4.2.2 The cytoskeleton might be involved in the organiza- tion of stress-inducible aggregates ...... 67 4.2.3 The nucleus is a new compartment for proteostasis . . 68 4.3 Cell sorting mechanisms may be used for proteostasis control during development ...... 69

ix Contents

A Plasmids 72 A.1 Gateway cloning ...... 72 A.2 Expression in D. discoideum ...... 73 A.3 Expression in S. cerevisiae ...... 74 A.4 Expression in HeLa ...... 76 A.5 Expression in E. coli ...... 76

B Primer 77

C Cell lines 78 C.1 D. discoideum ...... 78 C.2 S. cerevisiae ...... 80

x List of Tables List of Figures

1.1 The molecular chaperone system ...... 4 1.2 Prion propagation in S. cerevisiae...... 12 1.3 The life cycle of D. discoideum...... 15

2.1 Red-white prion reporter assay ...... 22 2.2 Plasmid shuﬄe assay ...... 23

3.1 Bioinformatic analysis of the D. discoideum proteome . . . . . 38 3.3 Aggregation behavior of Q103 and N47 in D. discoideum . . . 42 3.4 Aggregation behavior of Q103 and N47 in S. cerevisiae and HeLa...... 43 3.5 Aggregation behavior of NM ...... 45 3.6 Eﬀects of expression of aggregation-prone proteins on cellular biology ...... 47 3.7 Inﬂuence of NM* expression on cell fate decision during development ...... 49 3.8 Heat stress leads to reversible aggregation within the cytosol 50 3.9 Mobility of cytosolic aggregates requires the cytoskeleton . . 52 3.10 Function of Hsp101 during acute stress ...... 54 3.11 Hsp101 can functionally replace Hsp104 in S. cerevisiae . . . 56 3.12 Screen for Hsp40 proteins ...... 58 3.13 Nuclear accumulations are dynamic structures ...... 59 3.14 Nuclear accumulations result from proteasomal impairment 61

List of Tables

1.1 Human misfolding diseases associated with accumulation of amyloid aggregates ...... 10

xi List of Tables

xii List of abbreviations List of abbreviations

5-FOA 5-fluoroorotic acid ALS amyotrophic lateral sclerosis ATF6 activating transcription factor 6 cAMP cyclic adenosine monophosphate CLEM correlative light and electron microscopy cPrD candidate prion domain DAPI 4’,6-diamidino-2-phenylindole DMSO dimethyl sulfoxide DNA desoxyribonucleic acid EDTA ethylenediaminetetraacetic acid eIFα eukaryotic translation-initiation factor 2 subunit α ER endoplasmatic reticulum ERAD ER-associated degradation FACS fluorescence assisted cell sorting FOV field of view FRAP fluorescence recovery after photobleaching gDNA genomic DNA GdnHCl guanidinium hydrochloride GFP green fluorescent protein GO gene ontology HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid HMM hidden Markov model Hsp heat shock protein IPOD insoluble protein deposit IPTG isopropyl β-D-1-thiogalactopyranoside IREα inositol-requiring transmembrane kinase and endonuclease JUNQ juxtanuclear quality control compartment LB Luria Bertani LatA latrunculin A MTOC microtubule organizing center mRFPmars monomer red fluorescent protein mars N asparagine NA numerical aperture

1 List of abbreviations

NEF nucleotide exchange factor NEM N-Ethylmaleimide NBD nucleotide binding domain NM prion domain of Sup35p nPQCS nuclear protein quality control system OD optical density PERK double stranded RNA activated protein kinase-like ER kinase PIPES piperazine-1,4-bis(2-ethanesulfonic acid) PMSF phenylmethanesulfonyl fluoride PkC-like proteinase K-like domains PrD prion domain PSF prestarvation factor Q glutamine RNA ribonucleic acid RNP ribonucleoprotein RRM RNA-binding domains RT room temperature SBD substrate binding domain SD standard deviation SDD-AGE semi-denaturing detergent agarose gel-electrophoresis SDS sodium dodecyl sulfate SDS-PAGE SDS polyacrylamide gel electrophoresis SD-medium synthetic drop-out medium TAE Tris-acetate-EDTA TCEP tris(2-carboxyethyl)phosphine ThT thioflavin-T TB Terrific Broth UPS ubiquitin-proteasome system UPR unfolded protein response XBP1 X-box binding protein 1

2 Introduction 1. Introduction

1.1 Protein quality control Cellular functionality depends on an intact proteome. The proteome is subject to a delicate balance between synthesis, folding and degradation (proteostasis). However, even subtle changes can cause imbalances in proteostasis. Therefore, the cells have evolved an extensive protein quality control system to keep protein structure and function under tight surveillance. Several pathways of quality control exist inside the cells: the unfolded protein response (UPR) in the endoplasmatic reticulum (ER), the ubiquitin- proteasome system (UPS) and autophagy in the cytosol. All these pathways are assisted by molecular chaperones. Molecular chaperones monitor the folding state of the proteome and can direct inactive proteins either to refolding or to degradation.

1.1.1 The ubiquitin-proteasome system (UPS) The ubiquitin-proteasome system (UPS) is the predominant cytoplasmic clearance mechanism for short-lived, damaged or abnormal proteins. Pro- teins are targeted for proteasomal degradation by covalent attachment of multiple ubiquitin molecules. The conjugation of ubiquitin requires the coordinated action of three enzymes. Ubiquitin-activating enzyme (E1) activates the monomer through adenylation at the C-terminal glycine residue. There are several ubiquitin-conjugation enzymes (or ubiquitin carrier proteins, E2), which can transfer the activated ubiquitin to the ubiquitin lig- ase enzyme (E3). E3 catalyzes the covalent attachment of ubiquitin to a lysin residue in the target protein. Successive reactions transfer additional ubiquitin-molecules to lysines of the previously conjugated ubiquitin molecule and produce a polyubiquitin chain. This polyubiquitin chain serves as recognition signal for the proteasome and must contain at least four ubiquitin monomers. E3 enzymes provide the speciﬁcity for identifying the target proteins; however, some targets require auxiliary molecules such as molecular chaperones.[1–4] Polyubiquitin-conjugated proteins are recognized and degraded by the 26S proteasome. The 26S proteasome consists of the 20S core catalytic complex and 19S regulatory complexes on each end. The catalytic core is orga-

3 Introduction

Figure 1.1: The molecular chaperone system. Schematics of molecular chaperone system. Co-chaperones of the Hsp40 protein family can recognize misfolded proteins in the cytosol and recruits Hsp70 chaperones. Binding of the Hsp40/Hsp70 chaperone system stabilizes the misfolded proteins and prevents aggregation. The proteins are targeted for refolding or degradation. Aggregated proteins can be disassembled by the disaggregases of the Hsp100 protein family in co-operation with the Hsp40/Hsp70. nized as a stack of four rings (αββα) with seven subunits each. The catalytic sites (trypsin-, chymotrypsin- and post-glutamyl peptidyl hydrolytic-like sites) are located within the β-subunits, in the core tunnel of the proteasome. The 19S regulatory complexes recognize the ubiquitinated substrates and gate them into the proteolytic chamber.[1–4]

1.1.2 Molecular chaperones Molecular chaperones are a group of structurally unrelated proteins that interact with unfolded proteins. They are abundant and can be found in most cellular compartments. The specificity of chaperones is low, they generally can recognize denatured and unfolded proteins, but in this function they show a high flexibility[5–7]. The main role of molecular chaperones is the co-translational folding of newly synthesized proteins and translocation of proteins across membranes. However, under stress conditions, such as environmental stress (heat, oxidation, toxins) or pathological conditions (disease and aging), protein misfolding occurs more frequently. In these cases cells respond with an increased expression of molecular chaperones. Therefore, they are also referred to as heat shock proteins (Hsps) and and, for historical reasons, are classified by their molecular weight[4]. We can distinguish ATP-dependent from ATP-independent chaperones:

4 Introduction

Proteins from the family of the Hsp60s (also called chaperonins), Hsp70s, Hsp90s and Hsp100s use cycles of ATP binding and hydrolysis to act on their substrates, while Hsp40s and the small heat shock proteins (sHsps) are ATP-independent. Hsp60, Hsp70 and Hsp90 proteins are involved in protein folding and refolding of misfolded proteins. They can interact with ATP-dependent proteases to facilitate degradation. Together with the Hsp40s and the sHsps, Hsp70s and Hsp90s can also bind to denatured proteins and slow misfolding and aggregation[5,8–10]. However, if the quality control network is overwhelmed, misfolded proteins can coalesce into aggregates, which in most cases cause cytotoxic effects[6,8,11]. To counteract such effects, cells have evolved different mechanisms to overcome aggregation. Bacteria, plants and yeast posses specialized disaggregases, a specific subset of the Hsp100 protein family, which can resolve protein aggregates and subject proteins to a cycle of refolding, degradation or aggregation. Higher eukaryotes are devoid of Hsp100 proteins, but recent finding showed that non-canonical members of the Hsp70 protein family can partly act as disaggregases[6].

1.1.2.1 The Hsp70/Hsp40 system The members of the Hsp70 proteins are an essential class of ATP- dependent chaperones. Under normal conditions they are involved in nascent protein folding and protein translocation through membranes. During the latter process, they act on both sides of the membranes by either delivering substrates or pulling on them[12]. By binding to its substrates transiently, Hsp70s stabilize the unfolded state either until the substrate can fold in the right cellular destination, or to promote translocation[5]. Simi- larly, during heat stress, they protect proteins from misfolding and assist in refolding[8,9]. Hsp70s are composed of an N-terminal nucleotide binding domain (NBD) and a C-terminal substrate binding domain (SBD). The SBD consists of a β-sheet subdomain with the substrate binding pocket and the α- helical lid subdomain. Hsp70s can switch from an open, ATP-bound state to a closed, ADP-bound state. ATP-hydrolysis is stimulated by the Hsp40 co- chaperones, while the exchange of the nulceotide is facilitated by nucleotide exchange factors (NEF). The nucleotid-binding state inﬂuences substrate binding: in the ADP-bound state, the protein has a higher aﬃnity for its

5 Introduction substrates. In addition, the Hsp40 co-chaperones facilitate substrate binding. Upon hydrolysis, the aﬃnity drops and substrate release is promoted by the NEF.

1.1.2.2 Hsp100 disaggregases In contrast to the Hsp70 proteins, Hsp100 disaggregases are not required for growth under normal conditions. Recent findings even suggest that they might impair growth[13]. However, disaggregases are essential for cell survival after transient exposure to heat (thermotolerance) or other extreme conditions. This has been demonstrated for Hsp100s from S. cerevisiae (Hsp104[14]), E. coli (ClpB[15]) and A. thaliana (Hsp101[16]). Interest- ingly, the mere removal of thermally aggregated proteins is not sufficient for survival; and the recovery of active protein by refolding is required in both S. cerevisiae and E. coli[6]. The disaggregases belong to the extensive family of AAA+ (ATPases associated with various cellular activities) proteins. They are characterized by two conserved AAA+ domains which contain specific motifs: Walker A and Walker B motif, sensor 1, sensor 2 and the arginine finger motif[17,18]. The functional form of AAA+ ATPases is a hexameric ring with a central pore[19]. The disaggregases are composed of an N-terminal domain and an middle (M) domain flanked by two NBDs. This M-domain is unique to the disaggregases; it comprises four α-helices that form a coiled-coil structure[20]. Whether the M-domain is localized at the interior or the exterior of the hexameric ring is currently highly debated[6]. The conformation of the NBD on the other hand is characteristic for AAA+ proteins: the Walker A and Walker B of one protomer interact with the catalytic arginine finger motif of the adjacent protomer. This allows cooperativity of subdomains throughout the reaction cycle[17,19]. AAA+ proteins are generally referred to as ’unfoldases’ that can thread polypeptides or polynucleotides through their central pore to unfold or unwind them in an ATP-dependent manner[21]. Unlike the other Hsp100 proteins, which interact with proteolysis components and target substrates for degradation, the disaggregases are not involved in protein degradation but function in protein remodeling[6]. Although disaggregases possess an innate protein remodeling activity under certain in vitro conditions[22–24], they need the Hsp70/Hsp40 system to function in vivo[25,26].

6 Introduction

The Hsp70/Hsp40 system interacts with the M-domain and activates the disaggregase activity by stimulating ATPase activity[27–29]. It can also target substrate proteins to the disaggregase: First, the J-domain of the Hsp40 interacts with the aggregate, leading to binding of Hsp70 to the surface of the aggregate and partial loosening of exposed structures[30]. Then, the disaggregase is recruited through interaction with the M-domain[31,32]. As a next step, the Hsp70/Hsp40 complex transfers the unstructured region to the disaggregase, which binds it with conserved tyrosine-residues in the loop that extend into the central channel of the hexamer[22,24,33,34]. Finally, the polypeptide is extracted from the aggregate and translocated through the central pore. The extraction and threading movement is powered by ATP- hydrolysis[33,35]. The mechanism with which the disaggregases coordinate ATP-binding can vary depending on the substrate and the presence of the Hsp70/Hsp40 system. In the absence of Hsp70/Hsp40, the disaggregation of small aggregates uses a random or probabilistic mechanism of ATP hydrolysis. In the presence of Hsp70/Hsp40, large and insoluble aggregates are dissolved using sequential or semi-sequential ATP hydrolysis[36–38]. Interestingly, in S. cerevisiae, the disaggregase Hsp104 is also essential for prion propagation (Prions are self-replicating, infectious forms of amyloids aggregates, see 1.2.2). However, it was shown that the E. coli disaggregase ClpB can complement this function in the yeast system when co-expressed with its bacterial co-chaperone system[32,39].

Higher eukaryotes lack Hsp100 disaggregases. However, a disaggregat- ing function was linked to a group of non-canonical Hsp70 proteins, referred to as Hsp110 proteins. They can bind and hydrolyze ATP and they can also bind to substrates. Like the Hsp100 disaggregases, they interact with the Hsp70/Hsp40 system. The disaggregation occurs via entropic pulling by alternating between the open and closed conformation of the nucleotide binding domain: while one chaperone is in the ADP- and substrate- bound state, the other chaperone is in the ATP-bound state. Upon hydrolysis, the second chaperone interacts with the substrate while the ﬁrst binds ATP[40–42].

7 Introduction

1.1.3 Cellular responses to protein aggregation To counteract the cytotoxicity resulting from aggregated proteins during stress and under conditions where the protein quality control system is overwhelmed, cells can sequester aggregated proteins into specialized, membrane-free compartments. In mammalian cells, these are called aggresomes[43]. Aggresomes form juxtanuclearly at the microtubule organizing centers (MTOCs) by active transport along microtubules[43,44] and are enriched in molecular chaperones (Hsp70, Hsp40 and Hsp60) and proteasomes. It has been hypothesized that the aggresome serves as ’cytoplasmic recruitment centers’[45] or ’hold- ing stations’[46] which are formed to facilitate degradation. Proteins that accumulate at the aggresomes have higher turnover rates, and their degradation is reduced when aggresome formation is inhibited[45]. Furthermore, aggresome formation may also activate the autophagy pathway and aggresomes may be degraded via the lysosomal pathway[46]. While aggresome formation can be seen as a system for long-term sequestration of aggregated material, cells also posses short-term dynamic storage centers: recent studies identiﬁed compartments which are distinct from aggresomes and form transiently in response to stress, but faster than aggresomes[47]. Such aggresome-like structures (ALIS) do not localize to the MTOC, can form independently of microtubules and do not accumulate proteasomes. It has been suggested that ALIS are involved in the regulation of protein synthesis during stress by sequestering proteins in the cytosol[47]. In the yeast S. cerevisiae, increasing the load of misfolded proteins triggers formation of two distinct compartments, the juxtanuclear quality control compartment (JUNQ) and the insoluble protein deposit (IPOD)[48]. The JUNQ contains ubiquitinated proteins targeted for degradation. In contrast, terminally misfolded proteins, including amyloid aggregates, accumulate at the IPOD. While proteins in the JUNQ retain relative high mobility, the IPOD is a rigid, immobile structure. The formation of these compartments is probably actin-dependent[48] and sorting factors such as Hsp42[49], Btn2 and Cur1[50] act in cooperation with the Hsp40 co-chaperone Sis1 to sort proteins to these cellular compartments. It has been suggested that compartments similar to the JUNQ and IPOD also exist in the mammalian system[48,51].

8 Introduction

1.2 Amyloid protein aggregation Although cells have evolved very sophisticated mechanisms to control and regulate misfolded protein species, stress conditions lead to an increase in protein misfolding. This can overload the protein quality control system and lead to accumulation of aggregated material. In aging and diseased cells, the capacity to manage protein misfolding declines as well, also leading to increased aggregation[52]. Protein aggregates can vary in their structure, depending on the stress conditions and the proteins involved[53,54]. A specific subset of proteins can form highly structured amyloid aggregates. Such aggregates display very distinct structural and physicochemical features[55]. They bind dyes such as thioflavin-T (ThT) or Congo Red with high affinity, they show a characteristic red-green birefringence in polarized light, and a high resistance to denaturants such as sodium dodecyl sulfate (SDS). Amyloids arrange into extended β-sheets and adopt a crystal-like structure. This structural orga- nization also has functional implications and enables the structure to grow by self-replication. Once formed, the fibril can promote further conversions of native monomeric proteins and their subsequent incorporation into existing fibrils. Fibril formation displays many characteristics of nucleated growth mechanisms[55].

1.2.1 Amyloid aggregates and human diseases The presence of amyloid protein aggregates has been linked to a variety of human diseases. The largest group of these protein misfolding diseases is associated with the conversion of a specific protein from a soluble state to a fibrillar amyloid state. Amyloid fibrils can occur both inside the cell (intracellular inclusions) or outside the cell (extracellular plaques). In general, three main types of protein misfolding diseases can be dis- tinguished (see also Table 1.1). The best characterized group are the neurodegenerative diseases such as Alzheimer’s, Huntington’s and Parkinson’s disease[55,56]. Alzheimer’s disease is characterized by the accumulation of extracellular senile plaques, composed of β-amyloid, the cleavage product of the amyloid precursor protein. The formation of α-synuclein containing intracellular inclusions, so-called Lewy Bodies, is the hallmark lesion of Parkinson’s disease and several dementing disorders. Polyglutamine repeat

9 Introduction

Table 1.1: Human misfolding diseases associated with accumulation of amyloid aggregates. Adopted from Chiti et al. [55]

Neurodegenerative diseases Disease Aggregating protein or peptide Alzheimer’s disease Amyloid β-peptide Spongiform encephalopathy Prion protein (PrP) Parkinson’s disease α-synuclein Dementia with Lewy Bodies α-synuclein Frontotemporal dementia Tau with Parkinsonism Amyotrophic lateral sclerosis Superoxide dismutase 1 (SOD) Huntington’s disease Huntingtin with polyQ expansion Spinocerebellar ataxias Ataxins with polyQ expansion Spinocerebellar ataxia 17 TATA box-binding protein with polyQ expansion Spinal and bulbar muscular atrophy Androgen receptor with polyQ expansion Hereditary dentatorubral-pallidoluysian Atrophin-1 with polyQ expansion atrophy

(polyQ) diseases, a group of at least nine inherited diseases that include Huntington’s disease, are characterized by intranuclear accumulations of polyQ-containing peptides in distinct, but overlapping brain regions[57]. The second group are non-neuropathic localized amyloidoses, where a single type of tissue is affected by protein aggregation. The last group are non-neuropathic systemic amyloidoses, where aggregation occurs in multiple tissues[55]. The presence of amyloid aggregates in organs of patients led to the initial postulate that these aggregates are the causative agents. However, recent findings suggest that the precursors of amyloid fibrils, low-molecular weight prefibrillar oligomers, are the true pathogenic entities in neurodegenerative diseases. Unfolded structures can be toxic to the cell, because they can cause aberrant events through interaction with membranes, small molecules, proteins or other macromolecules. Prefibrillar oligomers display a higher proportion of interactive residues on their surface than larger aggregates and therefore have a higher relative toxicity[55].

10 Introduction

What causes these proteins to aggregate? Proteins involved in polyglutamine repeat (polyQ) diseases gain the ability to form amyloid aggregates through the expansion of glutamine-rich sequence stretches[58]. When the length of the polyQ-stretch reaches a certain threshold, the proteins form insoluble, high molecular weight inclusions[59]. Proteins linked to neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS), often carry mutations, which lead to the formation of pathological inclusions. Interest- ingly, recent studies showed that the mutations often reside within speciﬁc regions, which turned out be be responsible for aggregation. These regions strongly resemble prion domains (PrDs), which are found in yeast prion proteins (see 1.2.2)[60–62]. However, these prion-like domains lack the ability to confer a heritable phenotype, the criterion of a bona-ﬁde PrD[60].

1.2.2 Yeast prion proteins Prion proteins are a specific subset of amyloidogenic proteins and their properties have been extensively studied in the yeast S. cerevisiae. Prion states are characterized by protein fibrils, which consist of multiple beta sheet-rich monomers. Conversion of a protein from its native state into the prion state can occur when monomers change their conformation spontaneously. In S. cerevisiae, however, specific proteins of the heat shock family can promote this conversion[63,64]. The disaggregase Hsp104 (see 1.1.2.2) is essential for the formation and the propagation of prion fibrils. Inhibition of Hsp104 function by deletion or specific inhibitors, such as guanidinium hydrochloride (GdnHCl), causes a loss of the prion state, also referred to as ’curing’. Once formed, the fibril can propagate further conversions of native monomeric proteins and their subsequent incorporation into existing fibrils. During cell division, the prion fibrils are passed on to the daughter cell, where the self-propagating nature of the prion promotes further incorporation of unconverted proteins into the fibril. Prions can thus be considered as epigenetic elements that pass information on a protein-only basis - causing a loss-of-function or a gain-of-function phenotype[65]. The aggregation properties of yeast prion proteins reside in structurally independent prion domains (PrDs). These domains are enriched in uncharged amino acids (such as glutamine, asparagine, glycine, proline, serine and tyrosine) and are at least 60 amino acids long[66,67]. In the native conformation, the PrDs are intrinsically disordered[68,69], but they can sponta-

11 Introduction

Figure 1.2: Prion propagation in S. cerevisiae. Proteins can switch spontaneously from the native state to a cross-β structure (1). After the nucleation event, converted monomers associate to form a fiber that is a single extended β-sheet (2). Fibrils grow and can be broken into smaller fragments. The fragments are passed to the daughter cell upon division (3), where they promote further conversion and fibril growth. neously assemble into amyloid-nucleating species[69,70]. Interestingly, not all amyloidogenic proteins are associated with deleterious phenotypes. In contrast to the mammalian system, the yeast S. cerevisiae can use amyloid formation for a variety of cellular processes. It has been suggested that prions are used as so-called bet-hedging devices: under environmental stress, the formation of prions generates selectable phenotypic diversity which facilitates survival under these stress conditions[65,71–73]. Although critical voices argue that prion formation leads to degenerative disease conditions in S. cerevisiae[74,75], the finding that prions also occur in wild yeast strains strongly supports the hypothesis of prions acting as facilitators for survival[76]. Another example for biologically functional prions is the yeast transfer RNA isopentenyltransferase, Mod5. Prion conversion of Mod5 influences the sterol biosynthetic pathway which is important for cellular resistance against antifungal drugs[77]. Together, these findings show that

12 Introduction

S. cerevisiae can use amyloid and prion formation to regulate speciﬁc biological processes.

1.2.3 Computational prediction of prion and prion-like domains The presence of distinct domains, which confer the ability to switch into the amyloid prion state, stimulated the development of bioinformatic algorithms to detect prion-like domains in a proteome-wide scale. An initial algorithm, developed by Michelitsch et al., screened for enrichment of asparagines and glutamines in a stretch of a defined size[78]. This study showed that such stretches are common in eukaryotic, but rare in prokaryotic proteomes. They provided an extensive list of potential candidates, but only a low number proved to be prions in the experimental verification. A second study used binomial probabilities to identify regions with a bias for a high asparagine/glutamine content[79]. Both studies showed that such N/Q-rich domains are widespread within the eukaryotic proteomes. The observation that prion properties are not dependent on the precise primary sequence, but rather on the amino acid composition[80], paved the way for more sophisticated approaches. A refined algorithm used a hidden Markov model to identify domains based on compositional similarities to known yeast prions[67]. The subsequent analysis of the top 100 candidates identified some proteins with prion properties and a large number of aggregation-prone domains. The discrepancy between prion-forming domains and domains which do not form prions can be attributed to the composition of the domains: domains with a propensity to form prions or amyloids were enriched in asparagines and depleted for glutamines, pro- lines and charged residues[67]. This is unexpected, since both asparagines and glutamines were considered to be equally potent in promoting prion formation[78,79]. However, this observation was confirmed by an extensive mutational study that showed opposing effects for the two amino acids: glutamines promote the formation of proteotoxic, non-amyloid aggregates, whereas asparagines enhance formation of prions and reduced toxicity[81]. Further attempts to better predict which candidate prion domains en- code prion behavior uses experimentally derived prion probabilities to rank candidate domains[66,82,83]. This method was able to separate prion-

13 Introduction forming candidates with a high accuracy from those that to do not form prions. All these methods can have important implications in the identiﬁ- cation and prediction of functional prions and aggregation-prone proteins involved in human diseases.

1.3 Disctyostelium discoideum In their study, Michelitsch et al. showed that the greatest content of N/Q- rich regions are found in the proteome of D. discoideum[78]. Dictyostelium discoideum, often called the ’social amoeba’, is a solitary, soil-living amoebae. It belongs to the subclass of Dictyosteliidae, a monophyletic group that diverged from the animal-fungal lineage after the plant-animal split[84]. Since the late 1930s, this organism has been used to study cytokinesis, cell motility, phagocytosis, chemotaxis, signal transduction, and cell differentiation during development[85]. The most fascinating feature of D. discoideum is its life cycle. The organism can switch from a single-cell stage during the vegetative cycle to a multi-cellular stage during development. Interestingly, in D. discoideum, cell division and multicellularity are uncou- pled[86]. During the vegetative cycle, individual D. discoideum cells feed on bacteria or yeast in the soil and divide by mitosis. The cells can sense the amount of food source using secreted folic acid as chemoattractant. They also monitor their own cell density by secreting the glycoprotein PSF (prestarvation factor). If the ratio of PSF to bacterial food source exceeds a certain threshold, the cells stop proliferating and induce expression of genes involved in development. Together with CMF (conditioned medium factor), PSF po- tentiates cAMP signaling: a few of the starving cells start emitting pulses of cAMP. Surrounding cells respond by moving towards the pulse and re- laying the cAMP pulse to more distant cells. Up to 100,000 cells stream together to form a multicellular mound, the tip of which continues to emit cAMP pulses. The tip is pushed upwards by the movement of cells under- neath it to form the so-called ’ﬁnger’ structure. This structure tips over to form a slug-like pseudoplasmodium, which moves towards light (positive phototaxis) and warmth to reach the top layer of the soil. During slug movement, degradation of proteins produces ammonia, which inhibits a premature slug-to-fruiting body transition. When the top layer of the soil is

14 Introduction

Figure 1.3: The life cycle of D. discoideum. During normal growth conditions, cells feed on bacterial and divide mitotically. When the food supply decreases, D. discoideum initiates the developmental cycle. After progression through several phenotypical structures (streams, mound, finger, slug), cells are either encapsulated in spores or produce the stalk, which lifts the fruiting body above. The dormant cell within the spore can hatch and resume vegetative growth. reached, ammonia levels decrease and the slug transforms into the fruiting structure. Prestalk cells form a central cellulose tube, characterized by vac- uolization of the cells and production of a cell wall. Prespore cells climb up the stalk and form several spore walls. D. discoideum cells can hatch from the spores under warm and moist conditions. The fact that stalk-producing cells die and self-sacrifice themselves for the survival of the population, is the origin of the name ’social amoeba’[85–88]. The differentiation process starts already during mound-stage, with a ratio of approximately 80:20 (prespore:prestalk) regardless of the absolute number of cells. Prestalk cells can be divided into four groups, depending

15 Introduction on the expression of the two developmental genes ecmA and ecmB. The different cell types occupy distinct positions within the slug and form specific structures in the fruiting body. The question how this cell proportioning is established and maintained has not been answered completely yet. How- ever, a series of studies suggest that several factors, such as cAMP, the secreted polyketide DIF-1 (differentiation inducing factor 1), as well as the proliferative and nutritional histories of the cells play important roles in fate decision[86,89–91]. The genome of D. discoideum is extraordinarily A/T-rich (77.57 %) and has a high ratio of simple sequence repeats. This is reflected in the amino acid composition of the proteins, where specific amino acids (Asn, Lys, Ile, Tyr, Phe) are more common in D. discoideum than in human. Furthermore, tandem repeats of trinucleotides are unusually abundant in exons of proteins, which translates into a high occurrence of polyglutamines and polyas- paragines repeats and simple-sequence tracts of amino acids (in 34 % of the proteins)[84].

1.4 Aim of this study Computational studies suggested that N/Q-rich, prion-like domains are widespread in eukaryotic proteomes, but comparably rare in prokary- otes[78,79]. This suggests that unusual genome features may burden these organisms with a complex protein-folding problem. On the one hand, these domains might act as conformational switches that regulate the functional state of proteins and thus enable the proteome to better adapt to changing environmental conditions by allowing controlled aggregation of proteins in response to stress. Experimental studies are now required to determine how diﬀerent organisms take advantage of the versatility of prion-like domains. On the other hand, the presence of such domains can be a liability to cells: prion-like domains are found in proteins associated with human protein misfolding diseases and disease-related mutations are predominantly found in those regions[61,62]. Thus, by studying organisms with a high amount of prion-like proteins, we may get valuable insight into the strategies that nature employs to control and maintain a highly aggregation- prone proteome.

16 Introduction

The highest N/Q content and the longest glutamine- and asparagine- repeats were identified in D. discoideum[78]. Curiously, the amino acid composition of this organism seems to be influenced by the compositional bias of the genome, which is very A/T-rich and thus contains low complexity sequence stretches with a high content of aggregation-promoting residues[78,84,92]. Because of its remarkably N/Q-rich proteome, D. discoideum is an ideal candidate for the above mentioned studies. In this study, we will apply the same algorithm that was successfully used to identify prion domains in S. cerevisiae[67] and prion-like domains in disease-related proteins[61] to assess prion-like domains in D. discoideum. By studying the behavior of aggregation-prone proteins in D. discoideum, we aim to identify pathways, which are involved in the regulation of amyloid aggregating proteins. We will use fluorescence microscopy and biochemical methods to characterize the aggregation state of marker proteins in D. discoideum during normal growth, development and stress conditions.

17 Introduction

18 Material and Methods 2. Material and Methods

2.1 Cell Biological Methods 2.1.1 D. discoideum 2.1.1.1 Maintenance Strains used in this study: see C.1 Media: AX medium (ForMedium) Cells were grown on 100 mm cell culture dishes (Corning) at 23℃ under light (Conrad Electronic, Osram dulux S/E, 11 watt warm white light) until reaching conﬂuency.

2.1.1.2 Storage Soerensen buﬀer:

14 mM KH2PO4

2 mM Na2HPO4 x 2 H2O PA-plates: Soerensen buﬀer with 1.2 % agar

Cells were stored at -80℃ as spores in Soerensen buﬀer.

2.1.1.3 Transformation Cells from 4 confluent dishes were harvested in Soerensen buffer. They were washed three times with Soerensen buffer and diluted to 3-5x107 cells/mL in Soerensen buffer. 15 µg - 30 µg of DNA were transferred into an ice cold cuvette (Gene Pulser Cuvette, 0.4 cm, Bio Rad), 800 µL cell suspension was added, mixed and incubated on ice for 5 min. The cell/DNA mixture was electroporated at 1 V (MicroPulser Electroporator, BioRad) with two consecutive pulses and incubated on ice for 5 min. The cells were transferred to a 24 well plate (Corning) and incubated at RT for 15 min. 8 µL of 0.1 M Ca/MgCl2 was added and incubated for 15 min at RT. Cells were resuspended and 200 µL were transferred to 10 mL AX medium in 100 mm dishes. Selection markers were added after 24 hrs recovery time. Posi- tive transformants were selected by FACS after two weeks and sorted into 24 well plates (Corning) with 1 cell per well.

19 Material and Methods

Selection marker: Blasticidin 1000x stock solution 10 mg/mL (Roth) Geneticin (G418) 1000x stock solution 20 mg/mL (Sigma) Hygromycin B 1000x stock solution 33 mg/mL (Merk)

2.1.1.4 Whole-cell lysates Cells were harvested from plates in Soerensen buﬀer and washed three times. The cell pellet was resuspended in 400 µL NP-40 buﬀer (0.05 M

HEPES, 0.05 M Mg(C2H3O2)2, 10 % Saccharose, 2 % Nonidet P40). The cells were lysed by soniﬁcation (3 x 10 sec) and residual unlysed material was removed by centrifugation (8000 rpm, 5 min, 4℃ , Eppendorf tabletop centrifuge) in spinX-columns (0.2 µm pore, Corning).

2.1.1.5 Growth curves Cells were grown in 4 mL cultures in 24 well plates (Qiagen) at 23 ℃ under constant shaking (150rpm) and light. The cell numbers were assessed manually by counting cells in disposable hemocytometer counting cham- bers (Fast Read 102 chamber) according to the manufacturer’s protocol.

2.1.1.6 Development Development was induced by plating cells on PA-plates and incubation in a humidiﬁed chamber at 23℃ for 24 hrs.

2.1.2 S. cerevisiae 2.1.2.1 Maintenance Strains used in this study: see C.2 Media and plates: YPD medium: 1 % yeast extract 2 % peptone 2 % glucose

YPD plates: YPD medium with 2 % agar

20 Material and Methods

Synthetic drop-out medium (SD-medium): 0.74 g CSM-trp/ 0.78 g CSM-ade/ 0.77 g CSM-ura/ 0.69 g CSM-leu/ 0.77 g CSM-his (Formedium) 6.7 g YNB 2 % glucose/galactose/raﬃnose

Synthetic drop-out plates: SD-medium with 2 % agar

2.1.2.2 Transformation Cells were cultured overnight in 250 mL ﬂasks to an OD not higher than 0.5. They were collected by centrifugation (3000 rpm, 3 min, 4 ℃) and washed with H2O. The pellet was resuspended in 0.1 M LiAcetate solution to an equivalent of an OD of 50 and incubated at 30 ℃ for 15 min. 50 µL of cell suspension was added to a tube containing a DNA mix (5:1, salmon sperm DNA (Sigma) : plasmid DNA) and incubated for 30 min at 30 ℃. If eﬃciency needed to be increased, 10% DMSO was added. Then cells were incubated for 15 min at 42 ℃ and collected by centrifugation (2000 rpm,

1 min, RT). The pellet was resuspended in 200 µL H2O and plated onto selective media. If transformants were selected for drug resistance, the cells were grown in YPD medium for 5 hrs at 25 ℃ before plating onto the appropriate selective medium.

2.1.2.3 Whole-cell lysates Cell pellets from 5 mL cultures were resuspended in 300 µL ice cold lysis buﬀer (50 mM Tris pH 7.5, 150 mM NaCl, 2.5 mM EDTA, 1 % (v/v) Tri- ton X-100, 0.4 µM PMSF, 0.8 mM NEM, 1.25 mM benzamidine 1, 10 µg/ml pepstatin, 10 µg/ml chymostatin, 10 µg/ml aprotinin, 10 µg/ml leupeptin, 10 µg/ml E-64) and added to pre-cooled tubes containing 250 µL glass beads (425-600 µm, Sigma). Cells were lysed using a bead beater (15 min, 25 Hz, TissueLyzer II, Qiagen). Unlysed material and beads were pelleted by centrifugation (800 rpm, 3 min).

2.1.2.4 Red-white prion reporter assay The red-white prion reporter assay was designed to distinguish the [PRION] state of a cell population[93]. The assay was performed in an ade1-14 background (A4713 or A4714), where the ADE1 gene carries a nonsense mu-

21 Material and Methods

ADE1 nonsense mutation ( ade1-14)

Sup35p

nonfunctional Ade1p [psi-]

functional Ade1p [PSI+]

Figure 2.1: Red-white prion reporter assay. Schematic of the red-white prion reporter assay. In the S. cerevisiae ade1-14 nonsense mutation background the prion state of the transcription termination factor Sup35p can be monitored by the colony color: [psi-] red, [PSI+] white. tation. Premature termination of translation results in the accumulation of red pigment in cells deprived of adenine[94]. The translation termination factor Sup35p is the protein determinant of [PSI+][95]. In [psi-], the protein is soluble and can promote translation termination. In the ade1-14 cells, this results in a red colony color (Fig. 2.1). However, in the [PSI+] state, the translation termination factor is predominantly found in cytosolic ﬁbers and cannot act on its designated stop codon. Thus, ade1-14 cells show a white colony color (Fig. 2.1). In order to asses the [PRION] state of other protein determinants other than Sup35p, the prion domain (PrD) of Sup35p can be exchanged with the appropriate PrD to be tested[93].

22 Material and Methods

Figure 2.2: Plasmid shuffle assay. Schematics of the plasmid shuffle assay. Plasmids with different counter- selectable markers were introduced in a cell. Growth on 5-FOA-containing medium results in loss of uracil counter-selectable plasmids

2.1.2.5 Plasmid shuffle assay The plasmid shuffle assay was used to test the ability of Hsp101 to maintain a [PRION] state. [PSI+] cells were depleted of Hsp104 (∆hsp104) but contained an additional copy of HSP104 on a uracil counter-selectable plasmid (Fig. 2.2, blue). A second, leucine counter-selectable plasmid with a copy of HSP101 was introduced (Fig. 2.2, green). Subsequently, the cells were grown on media containing 0.1 % 5-fluoroorotic acid (5-FOA), which resulted in the loss of the uracil counter-selectable plasmid. The presense of the [PRION] state was assessed using the red-white prion reporter assay (see 2.1.2.4).

2.1.2.6 Mating and Tetrad dissection To induce mating, cell lines with opposing mating types were plated on one plate in two parallel strikes. After colony growth was apparent, the colonies were intermixed and allowed to proceed growing over night. Cells were re- plated to receive single colonies To induce sporulation, diploid cells were inoculated in 5 mL sporulation medium (1 % KC2H3O2, 0.1 % Bacto-yeast extract, 0.05 % Glucose) at 30 ℃. The tetrads were collected by mild centrifugation and incubated in tetrad dissecting buﬀer (1 M Sorbitol, 10 mg/mL lyticase (Sigma), 1:10 tetrads) for 10 min at room temperature and subsequently stored on ice until tetrad dissection.

23 Material and Methods

2.1.3 Mammalian cells 2.1.3.1 Maintenance Strains: name source HeLa Kyoto kindly provied by Neugebauer lab, MPI-CBG Dresden Neuro-2a SUP35NM-GFP kindly provided by I. Vorberg[96], DZNE Bonn

Media: DMEM/Glutamax (4.5 g glucose/500 mL, Invitrogen) 10 % FCS (PAN), 100 units/mL Penicillin, 100 µg/mL Streptomycin (Gibco).

2.1.3.2 Transformation Transformation reactions were performed using Lipofectamine (Life Techologies) according to the manufacturer’s protocol. Cells were plated in 6-well plates (Corning) in medium without antibi- otics prior to transformation. 4 µg DNA was diluted in 125 µL serum-free medium. In parallel, 10 µL lipofectamine was diluted in 125 µL serum-free medium and incubated for 5 min at RT. The diluted DNA was combined with the diluted lipofectamine solution and incubated for 20 min at RT. The mix was added to the cells. After 2 days, cells were harvested for lysis (see 2.1.3.3).

2.1.3.3 Whole-cell lysates Cells were harvested form plates in PBS (137 mM NaCl, 2.7 mM KCl, 12 mM phosphate buffer) and washed three times. The cell pellet was resuspended in 400 µL NP-40 buffer (0.05 M HEPES, 0.05 M Mg(C2H3O2)2, 10 % Saccha- rose, 2 % Nonidet P40). The cells were lysed by sonification (3x 10 sec) and residual unlysed material was removed by centrifugation (8000 rpm, 5 min, 4℃ , Eppendorf tabletop centrifuge) in spinX-columns (0.2 µm pore, Corn- ing).

24 Material and Methods

2.1.4 E. coli Strains: name genetic background source XL1-Blue recA1 endA1 gyrA96 thi-1 hsdR17 supE44 Stratagene relA1 lac [F- proAB lacIqZ∆M15 Tn10 (Tetr)] DH5α recA1 endA1 gyrA96 thi- hsdR17 supE44 Invitrogen relA1 F- 80lacZ∆M15 Λ(lacZYA-argF) U169 (rK-, mK+) phoA λ-1

Media and plates: Luria bertani (LB) medium: 1% peptone 0.5% yeast extract 1% NaCl

Terriﬁc broth (TB) medium: 1.2% peptone 2.4% yeast extract

72 mM K2HPO4

17 mM KH2PO4 0.4% glycerol

2.2 Molecular biology 2.2.1 Cloning All cloning procedures were performed using the Gateway cloning strategy from Invitrogen[97].

25 Material and Methods

2.2.1.1 Amplification from gDNA Genes were amplified from gDNA using gene-specific primers (see B):

PCR reaction 1 2 ng DNA template 0.2 µM primer mix 0.3 mM dNTP

1 mM MgSO4 1x Platinum Pfx buﬀer (life technologies) 0.02 U Platinum Pfx polymerase (life technologies)

Subsequently, the AttB sites were added using universal primers (AttB_univ_F, AttB_univ_R) in a second reaction:

PCR reaction 2 20 µL PCR reaction 1 0.5 µM universal primer mix 0.3 mM dNTP 1x Platinum Pfx buﬀer (life technologies) 0.02 U Platinum Pfx polymerase (life technologies)

PCR reaction was performed following the manufacturer’s instructions. Primer annealing temperature was calculated in accordance to the primer sequence. The elongation was performed at 60 ℃. Reaction 1 was repeated for 20 cycles, reaction 2 for 18 cycles in total.

2.2.1.2 BP and LR reaction BP and LR reactions were performed according to the manufacturer’s protocol. After incubation at 25℃ over night, the reaction was transformed into DH5α cells. Plasmids used to generate entry clones: pDONR221 (see A.1) Plasmids used to generate expression clones: see A.2, A.3, A.4

2.2.2 E. coli transformation 2.2.2.1 Generation of competent cells E. coli cells were grown in pre-culture (100 mL LB) at 37 ℃ over night. The next day, cells were diluted in TB medium (see 2.1.4) to an OD of 0.2 and

26 Material and Methods grown at 37 ℃ until they reached an OD of 1.0. The culture was diluted 1:20 in 500 mL TB and incubated again at 37 ℃ until an OD of 0.5 was reached. Cells were harvested by centrifugation (4.000 g, 10 min, 4 ℃) and the pellets were resuspended with 35 mL transformation mix (5 % (w/v)

PEG 3350, 3,5 % DMSO (Sigma) 7 mM MgCl2, 7 mM MgSO4, 2.8 % glycerol in LB pH 6.1) on ice. The slurry was aliqoted into pre-chilled tubes (1 mL/tube) and quick-frozen on dry ice. Competent cells were stored at -80 ℃.

2.2.2.2 Transformation 5x KCM solution 0.5 M KCl 0.15 M CaCl2 0.25 M MgCl2

DNA/KCM mix was prepared in 50µL on ice. Competent cells were added in a 1:1 ratio and incubated on ice for 20 min. The transformation mix was heat shocked at 42 ℃ for 30 sec and then placed on ice. 900 µL LB medium was added to the cells and incubated at 37 ℃ for 45 min. Cells were plated on appropriate selective media.

2.2.3 Purification 2.2.3.1 Purification of plasmid DNA Plasmid DNA was purified from E. coli cultures using Miniprep Plasmid purification Kit (Qiagen) according to the manufacturer’s protocol. DNA was eluted in 50µL H2O. If high concentration of DNA was needed (see 2.1.1.3), plasmid DNA was purified using NucleoBond Xtra Kit (Macherey Nagel) according to the manufacturer’s protocol. DNA was resuspended in H2O and concentration was adjusted to 1 µg/µL.

2.2.3.2 Purification of genomic DNA from D. discoideum For purification of genomic DNA from D. discoideum, cells were grown to confluency in a 100 mm dish. The cells were harvested in Soerensen buffer and washed with ice-cold 0.2% NaCl. The pellet was resuspended in 1 mL ice-cold NP-40 buffer (see 2.1.1.4) and lysed by sonification (3x

27 Material and Methods

10 sec). Unlysed cell debris was removed by centrifugation (8,000 rpm, 10 min, 4 ℃). 2 mL TE-SDS (10 mM Tris, 1 mM EDTA, 1 % SDS) were added to the supernatant and incubated at 65 ℃ for 15 min. Then, 2mL TE and Proteinase K (to a ﬁnal concentration of 200µg/mL) was added and incubated at 50 ℃ for 2 hrs. The DNA was extracted with one volume of phenol:choloroform:isoamyl alcohol (24:24:1), then with chloroform (3x).

To precipitate the DNA, 0.1 volume of 3 M NaC2H3O2 pH 5.2 and 2 volumes of abs. EtOH was added and pelleted by centrifugation (10,000 rpm,

20 min, 4 ℃). The DNA was resuspended in H2O.

2.2.4 Restriction analysis Correct insertion of PCR fragments during cloning (see 2.2.1) was veriﬁed using restriction enzyme digest. Entry clones resulting from BP reactions were digested with BsrGI (NEB) (see A.1). Expression clones for expression in D. discoideum are digested with BglII (NEB) (see A.2). Expression clones for expression in S. cere- visiaewere digested with EcoRI/BamHI (NEB) (see A.3). Expression clones for expression in HeLa cells were digested HindIII/ApaI (NEB) (see A.4) Restriction digests were performed according to the manufacturer’s protocol. Restriction products were veriﬁed using gel electrophoresis (see 2.2.5).

2.2.5 Gel electrophoresis Restriction digests and PCR products were analyzed on 1% agarose gels in TAE buﬀer (40 mM Tris, 20 mM acetic acid, 1 mM EDTA). Gels were run at 90 V and DNA was visualized with ethidium bromide in a UV chamber.

2.2.6 Site-directed mutagenesis Site-directed mutagenesis was performed using QuickChange II Site- Directed Mutagenesis Kit (Stratagene) with the primers indicated in ap- pendix B according to the manufacturer’s protocol. Correct clones were identiﬁed using sequencing (in-house facility, MPI-CBG).

28 Material and Methods

2.3 Protein Chemistry 2.3.1 SDS-PAGE Whole cell lysates were separated by SDS polyacrylamide gel electrophoresis (SDS-PAGE) using discontinous gels[98,99] comprising a sepearation gel (10% polyacrylamide) and stacking gel (4.8% polyacrylamide) in SDS running buﬀer (25 mM Tris, 190 mM glycine, 0.1 % SDS). Protein samples were mixed with 3x SDS loading buﬀer (0.2 M Tris-HCl, pH 6.8, 6 % SDS, 30 % glycerol, 0.003 % bromophenol blue, 15 % 2-mercaptoethanol) and incubated for 5 min at 95 ℃. Gels were run at 25 V. After protein separation, gels were used for Western Blotting (see 2.3.3).

2.3.2 SDD-AGE To visualize SDS-resistant fibrils, whole cell lysates were separated by semi- denaturing detergent agarose gel-electrophoresis (SDD-AGE) using 1.5 % agarose gels[93] in SDD-AGE running buffer (40 mM Tris, 20 mM acetic acid, 1 mM EDTA, 0.1 % SDS). Protein samples are mixed with 4x SDD-AGE loading buffer (80 mM Tris, 40 mM acetic acid, 2 mM EDTA, 20 % glycerol, 4 % SDS, 0.003 % bromophenol blue) and incubated at RT. Gels were run at 90 V. After protein separation, gels were used for Western Blotting (see 2.3.3).

2.3.3 Western Blot 2.3.3.1 Transfer Proteins separated by SDS-PAGE were transferred onto nitrocellulose membranes (Protran B 85, Whatman) in transfer buﬀer (20 mM Tris-Base, 144 mM Glycine, 20 % Methanol, 0.01 % SDS) using wet transfer elec- troblotting (Mini Tank Transfer Unit, GE Healthcare). Proteins separated by SDD-AGE were transferred onto nitrocellulose membranes (Hybond-C, Amersham) in PBS (137 mM NaCl, 2.7 mM KCl, 12 mM phosphate buﬀer) by capillary transfer over night[93].

2.3.3.2 Immunodetection To test for completeness of the transfer, the membranes were stained with ponceau solution (5 % acetic acid, 0.3 % Ponceau S) and destained in H2O. Unspeciﬁc binding of antibodies was prevented by incubation of the mem-

29 Material and Methods brane in blocking solution (2.5 % milk powder in PBS) for 1 hrs. Next, the membranes were incubated with protein-speciﬁc primary antibody in blocking solution for 1 hrs at RT or over night at 4 ℃. After three consecutive washes with PBS, the membranes were incubated with secondary antibody in blocking solution for 1 hrs at RT or over night at 4 ℃. Antibodies used in this study:

name dilution organism source αGFP 1:2000 mouse Roche αSup35C 1:1000 rabbit Gift αHsp104 1:1000 rabbit Gift αHsp100 1:1000 rabbit Gift α-mouse IgG 1:5000 goat Sigma α-rabbit IgG 1:5000 goat Sigma

The signal was visualized by chemiluminescence (substrate or Supersignal West Dura, Pierce) of x-ray ﬁlms (Film Kodak Biomax Light).

2.3.4 Filter retardation assay The ﬁlter retardation assay was performed as described previously[100]. Whole cell lysates were applied onto a cellulose acetate ﬁlter (0.2 um, GE Healthcare) using a vacuum and a slot blot device (Whatman). For visual- ization of protein signal, the membrane was processed as described in 2.3.3.

2.3.5 In vitro ﬁbril assembly 2.3.5.1 protein expression E. coli BL21 cells were transformed with pRH1-NM (see A.5) using the standard transformation protocol (see 2.2.2). The cells of a fully grown plate were rinsed with 5 mL TB and diluted in 1 L TB to an OD of 0.1. The culture was incubated at 37℃ until an OD of 0.8 was reached. Then, expression was induced with 0.2% L-arabinose ans 1 mM IPTG for 4 hrs. Cells were collected by centrifugation (6,000 g, 15 min, 4℃). The cell pellet was resuspended in lysis buﬀer (6 m GdnHCl, 100 mM potassium phosphate pH 8.5, 5 mM imidazole, 300 mM NaCl, 5 mM 2- mercaptoethanol) and mixed for 60 min. Unlysed material was removed by centrifugation (10,000 g, 20 min). The supernatant was mixed with pre- equilibrated Ni-NTA agarose beads (Qiagen, 2 mL slurry for 1 L of culture)

30 Material and Methods and incubated for 30 min at RT with constant rotation. The mix was transferred to a 10 mL batch purification column (PD-10 Columns, GE Health- care). The beads were washed 5 times with wash buffer (8 M urea, 100 mM potassium phosphate pH 7, 10 mM imidazole, 300 mM NaCl, 5 mM 2- mercaptoethanol). The protein was eluted with 700 µL elution buffer (8 M urea, 100 mM NaC2H3O2 pH 4, 5 mM 2-mercaptoethanol, 200 mM imidazole). 5 volumes methanol were added to the eluate and stored at -80℃.

2.3.5.2 In vitro assembly The protein methanol slurry was pelleted (13,000 rpm, 30 min) and the protein was resuspended in denaturation buffer (6 M GdnHCl, 100 mM potassium phosphate pH 7, 2 mM TCEP). Protein concentration was determined at 280 nm. The protein was diluted to 10 µM in assembly buffer (5 mM K2HPO4 pH 6.6, 150 mM NaCl, 5 mM EDTA, 2 mM TCEP, 5 µM ThT). The assembly reaction was performed in nonbinding plates (Sigma) and fibril assembly was measured by exciting ThT at 450 nm and its 482 nm emission.

2.4 Microscopy 2.4.1 Wide field microscopy 2.4.1.1 Sample preparation For live cell microscopy of D. discoideum, cells were grown over night in LoFlo medium (Formedium) to reduce background fluorescence. Before imaging, cells were transferred to glass bottom dishes (MaTek) and allowed to settle for 20 min. During imaging, cells were kept at 22℃ using a cooling chamber (Warner), unless otherwise indicated. Constant cooling reduced phototoxic effects significantly. S. cerevisiae cells were prepared as described previously[50]. Cells were im- mobilized on 1 % agar pads before imaging.

If required, D. discoideum and HeLa cells were fixed using the picric acid- paraformaldehyde fixation protocol[101]. Cells were grown on glass cover slips (0.17 mm ±0.01) and washed three times with PBS (137 mM NaCl, 2.7 mM KCl, 12 mM phosphate buffer). The cover slips were inverted onto a drop of fixative solution (20 mM PIPES, 4 % paraformaldehyde, 35 % pi-

31 Material and Methods cric acid) and incubated for 30 min at RT. Residual fixative was removed by washing with quenching buffer (100 mM glycine in PBS) and 20 mM PIPES buffer. The cells were post-fixed with 70 % ethanol for 15 min at RT. Af- ter three washes with PBS, cells were either stained with DAPI (1:10,000 in PBS) or directly mounted in gelvatol mounting solution (15 % (v/w) Gel- vatol (Sigma) in 0.01 M KH2PO4, 0.01 M Na2HPO4, 0.14 M NaCl, 30 % Glycerol, pH 7).

2.4.1.2 Imaging Images and time-lapse movies were acquired using a Deltavision microscope system with softWoRx 4.1.2 software (Applied Precision, Issaquah, WA). The system is based on an Olympus IX71 microscope, which we used with a 100x/1.4 numerical aperture (NA) or 60x/1.42 NA objective (for single cell microscopy and time-lapse of heat stress) or 20x/0.75 NA objective (for time-lapse of mitosis). The images were collected with a Cool SnapHQ camera (Photometrics, Tucson, AZ) as 1024 x 1024 pixel ﬁles using 1 x 1 binning. All images were deconvolved using standard softWoRx deconvo- lution algorithms (enhanced ratio, high-to-medium noise ﬁltering). Images acquired with the Deltavision setup were maximum-intensity projections of at least 20 individual images.

2.4.2 Stereo microscopy For imaging developmental stages of D. discoideum, development was induced as described in 2.1.1.6. Structures were imaged on a Olympus SZX12 upright stereo microscope.

2.4.3 FRAP 2.4.3.1 Sample preparation D. discoideum cells were grown over night in LoFlo medium (Formedium) to reduce background ﬂuorescence. Before imaging, cells were transferred to glass bottom dishes (MaTek) and allowed to settle for 20 min. During imaging, cells were kept at 22℃ using a cooling chamber (Warner).

2.4.3.2 Imaging Images were acquired on a spinning-disk Olympus IX81 inverted stand microscope using a Olympus UPlanSApo 60x 1.20 W objective and iQ 1.10.5

32 Material and Methods software. The microscope is equipped with an Yokogawa CSU-X1 spinning disc scan head ((5000 rpm) pinhole radius: 25 µm, pinhole spacing: 250 µm). The images were collected with an Andor iXon EM with DU-897 BV back illuminated EMCCD. Pre-bleaching images were acquired as z-stacks (0.5 µm sections) with a time interval of 5 min. The cells were bleached in a 30x30 nm region in three pulses with 60 % laser power (488 nm laser) for 30 msec. Post- bleaching images were acquired as z-stacks (0.5 µm sections) with time intervals of 1 sec for the ﬁrst 100 frames and 1 min intervals for the following 30 frames.

2.4.4 Confocal microscopy 2.4.4.1 Sample preparation D. discoideum slugs were formed on 1-2 mm thin agarose pads (see 2.1.1.6) in a humidiﬁed chamber. 1x1 cm wide squares were cut out and inverted (slug-ﬁrst) onto glass bottom dishes (Matek).

2.4.4.2 Imaging Slugs were imaged on an inverted stand Zeiss-Axio Observer with a Zeiss LD C-Apochromat 40x 1.1 W objective and AxioVision software from Zeiss The spinning disk microscope is equipped with an Yokogawa CSU-X1 spinning disc scan head ((5000 rpm) pinhole radius: 25 µm, pinhole spacing: 250 µm). The images were collected with a Roper evolve 515 EMCCD camera. Slugs were imaged as z-stacks (2 µm sections). Images acquired with the setup were maximum-intensity projections of at least 50 individual images.

2.5 Analysis 2.5.1 HMM algorithm For predicting the occurrence of a prion domain in a given set of proteins, we used the hidden Markov model (HMM) based on the HMM described previously by the Lindquist lab[67]. The following output probabilities for the prion state were obtained:

33 Material and Methods

Amino acid output probability prion state A 4.2501322 C 0.8495353 D 2.0713379 E 1.7073955 F 3.3644566 G 10.8440664 H 1.0713270 I 1.5822792 K 2.7584645 L 3.4096907 M 2.0704712 N 19.3603931 P 3.5267232 Q 16.2506059 R 2.3562638 S 10.5433046 T 3.2207167 V 2.1705145 W 0.8495353 Y 7.7427865 To account for amino acids occurring in the other analyzed species (e.g. Selenocysteine U, Pyrrolysine O or placeholder symbols J, X, B, Z) an output frequency for the prion state of p = 0.000001 was assigned. Additionally, the obtained predicted PrDs were screened for a foldIndex <0 to exclude folded domains[102].

2.5.2 Enrichment analysis The gene list resulting from was analyzed using DAVID[103,104]. For the functional analysis, an initial clustering was obtained using the functional annotation clustering tool of DAVID with an EASE score of ≤ 0.1 for each GO-term. The resulting clusters were then manually curated and the GO- terms clustered by localization or molecular function. The enrichment analysis for protein domains found in the candidate protein list was also performed with DAVID. Only those SMART domains were

34 Material and Methods used, which showed more than 4 counts per term. The proteomes of S. cerevisiae, D. melanogaster and H. sapiens were obtained from the ENSEMBL genome server. The genomes of D. discoideum and D. purpureum were obtained from dictyBase.

2.5.3 FRAP For FRAP analysis, we obtained three values for each acquired image: background fluorescence at each time point (BG(t)), total fluorescence at each time point (T ot(t)) and the fluorescence of the bleached area (ROI(t)). For analysis of nuclear structures, T ot(t) corresponded to the fluorescent singal of the whole cell; for Analysis of nucleolar structures, T ot(t) corresponded to the fluorescent signal of the nucleus, assessed by H2B-mRFPmars signal. All values were obtained from maximum-intensity projections of pre- bleached and post-bleached images. Images were processed using Fiji image analysis software. Image analysis comprised three steps: background subtraction (i), data correction (ii) and normalization (iii).

ROI(t) − BG(t) (i) T ot(t) − BG(t)

ROI(t) − BG(t) (ii) T ot(t) − BG(t)

ROI(t) − BG(t) T ot(0) − BG(0) × (iii) T ot(t) − BG(t) ROI(0) − BG(0)

For each FRAP analysis, 4 experiments were analyzed independently. The mean fluorescence intensity (Intm) was used to calculate the half-time (t1/2) and the mobile fraction (Mr). To calculate t1/2, the data points were fitted to equation (iv), where −t is the time constant and A represents the intensity of fluorescence in the image.

× − t time Intm = A (1 e− × ) (iv)

log(0.5) t = (v) 1/2 −t

35 Material and Methods

The mobile fraction (Mr) was be calculated using the ﬂuorescence intensity before bleaching (Fpre), after bleaching (Fpost at time = 0) and A:

− A Fpost Mr = − (vi) Fpre Fpost 2.5.4 MSD To model the diﬀusion of stress foci, we measured the mean square dis- [105] placement (µ) for the particles as described in (vii), where Ml was the length of the trajectory measurement, ∆n was the time shift, x(n) and y(n) the x- and y-position at time point n.

M ∆n 1 1 lX− − µ(∆n) = (x(n + ∆n) − x(n))2 + (y(n + ∆n) − y(n))2 (vii) M − ∆n l n=0

For both, Q103-GFP and NM*-GFP, we measured at least 6 traces under normal conditions and in the presence of latrunculin A (LatA). The mean square displacement was determined for each trace independently and a mean value (MSD) was calculated for each condition. To determine the diffusion mode, we plotted MSD against the time shift (∆n or time) and fitted to equation (viii), thereby determining the diffusion coefficient (D) an α.

MSD = 4 × D × timeα (viii)

The value of α can be used to assess the mode of diffusion[106]. If 0 < α < 1, then the movement was characterized by subdiffusion, while 1 < α < 2 indicated superdiffusion, thus active transport.

2.5.5 Counting cytoslic foci/nuclear accumulates The number of nuclear accumulations and cytosolic foci occurring during stress was counted manually in minimum 9 field of views (FOVs) in the GFP channel. The number of total cells was determined by counting in the bright field channel. The size and number of cytosolic foci during prolonged heat stress was determined using Fiji image analysis software and the analyze particle plugin (size-0-Infinity, circularity-0.00-1.00).

36 Results 3. Results

3.1 Bioinformatic analysis of aggregation-prone proteins in D. discoideum Bioinformatic analysis reveals a highly aggregation-prone proteome in D. discoideum Poly-aspagarine (N) and poly-glutamine (Q)-rich regions are key determinants for protein aggregation[67]. Analyses of proteomes from diverse species identified a subset of organisms with an increased incidence of N/Q- rich stretches[78]. These studies showed that the greatest total N/Q content in regions of low complexity is found in the social amoeba D. discoideum. In order to assess the prevalence of aggregation-prone proteins in the proteome of D. discoideum, we made use of a HMM-based approach. A similar algorithm was previously used by Alberti et al.[67] to identify potential prion domains (PrDs) in the proteome of S. cerevisiae, based on characterized prion proteins. We adapted the algorithm to make it applicable to other organisms[107]. Our analysis revealed approximately 1700 prion-like candidate proteins in the proteome of D. discoideum. This number exceeds the number of predicted prion proteins in yeast by a factor of ten. In addition, not only the number of proteins containing N/Q-rich stretches was increased, but also the length of the stretches was elevated, with some polyglutamine stretches above the aggregation threshold of 36-40[59] (Fig. 3.1A). To analyze the distribution of the candidate proteins within protein families, we clustered the candidates according to their associated domains. We used DAVID[104] to perform an enrichment analysis of associated protein super-domain families. We observed that the N/Q-rich sequence stretches were specifically associated with proteinase K-like domains (PkC-like) or RNA-binding domains (RRM) (Fig. 3.1B). The association of aggregation- prone domains with RRMs seems to be a general feature, as a similar observation has been made for other organisms[61,107]. In addition, we found significant associations of the candidate proteins with specific GO-terms (Fig. 3.1C). We noticed that aggregation-prone domains are significantly enriched (p<0.01) in proteins associated with the cytoskeleton and the nucleus. Interestingly, we found that these proteins are associated (p<0.005)

37 Results

Figure 3.1: Bioinformatic analysis reveals a highly aggregation-prone proteome in D. discoideum (A) Length distribution of N/Q-rich stretches in D. discoideum and S. cerevisiae. N/Q-rich proteins in the proteomes were predicted based on their compositional similarity with known prion proteins [67]. (B) Protein domains frequently associated with N/Q-rich proteins in D. discoideum and S. cerevisiae. N/Q-rich proteins were analyzed for their association with SMART domains using DAVID [103]. The pie chart shows the total number of N/Q-rich proteins in the proteome of the species. (C) Clustering of N/Q-rich proteins in D. discoideum according to gene ontology (GO)-terms. The analysis was performed with DAVID. All proteins with an EASE score 0.1 were taken into ≤ account. Clusters were generated manually based on initially proposed clusters by the functional annotation tool DAVID.

38 Results with DNA/RNA interaction (DNA binding, RNA binding, DNA modification), protein modification and signaling processes. These findings indicate that prion-like stretches are not randomly occurring features in protein sequences. Next, we compared the occurrence of prion-like stretches within the Dic- tyostelid family. Apart from D. discoideum, D. purpureum is the only Dic- tyostelid that has been sequenced. We found approximately 900 candidate proteins in the proteome of D. purpureum. To test whether the prion-like stretches reside in the same proteins in both species, we performed an ortholog analysis. We found 505 orthologous proteins in both candidate lists (Fig. 3.2A). In addition, we compared the associated protein super-domain families and found a comparable overlap between both species (Fig. 3.2B). This suggests that the occurrence of N/Q-rich sequence stretches and their association with certain protein families is partially conserved within the Dictyostelid family. Using our modified algorithm, we extended the analysis to additional species. We analyzed the proteome of the fruit fly D. melanogaster and H. sapiens. We found 656 proteins in fruit flies that contained a N/Q-rich stretch and 219 such proteins in humans . We combined these results with the hits obtained from S. cerevisiae and performed an enrichment analysis of associated GO-terms. Clustering according to the cellular components revealed four groups that were conserved across all three species: cytoskeleton, nucleus, RNP complexes and chromatin (Fig. 3.2C). A similar functional association was observed in D. discoideum (Fig. 3.1C). Clustering according to molecular function revealed three conserved groups: transcription, DNA binding, and RNA binding. Additional clusters were specific to only one or two species. A comparison showed that two groups (DNA binding and RNA binding) are conserved throughout all four species. Taken together, these findings suggest that prion-like domains are biologically relevant and not randomly occurring stretches of low compositional complexity. Nevertheless, the questions how the extreme aggregation propensity of these proteins is regulated seems to be of even higher importance.

39 Results

Figure 3.2: Comparison of N/Q-rich proteins in different species (A,B) Comparison of N/Q-rich proteins in D. discoideum and D. purpureum. The Venn diagrams show protein orthologs and protein superfamily domains represented in N/Q-rich proteins. N/Q-rich proteins were identified based on compositional similarity with known prion proteins [67].The identified proteins were analyzed for their association with SMART domains using DAVID [103]. Protein ortholog information was obtained from DictyBase [108].(C) Clustering N/Q-rich proteins in S.cerevisiae, D. melanogaster and H. sapiens according to GO-terms. The analysis was performed with DAVID. All proteins with an EASE score 0.1 were taken into account. Clusters were curated based on initially proposed ≤ clusters by the functional annotation tool DAVID.

40 Results

3.2 Behavior of aggregation-prone proteins in D. discoideum Aggregation-prone proteins do not aggregate in the cytosol of D. discoideum To determine mechanisms controlling protein aggregation, we first studied the behavior of several well-characterized aggregation-prone marker proteins. These proteins have been characterized extensively in other organisms and have been shown to form cytosolic aggregates in S. cerevisiae, C. elegans and mammalian cells[109–111]. In the present study, we used the poly-glutamine-rich exon1 of human Huntingtin with 103 consecutive glutamines (Q103). To account for the N-richness of Dictyostelium, we also used a synthetic poly-asparagine protein (N47), in which the glutamines of Htt1 were replaced by 47 asparagines. In yeast, this protein exhibits the same aggregation propensities as the poly-glutamine marker Q103[81]. We expressed the marker proteins and non-aggregating control proteins as GFP fusions in Dictyostelium cells. Surprisingly, Q103 and N47 did not form aggregates in the cytosol but were diffusely distributed throughout the cytoplasm in the majority of the cells (Fig. 3.3A). In contrast, expression of each marker proteins in S. cerevisiae and mammalian cells resulted in formation of cytosolic foci (Fig. 3.4A). However, the uniform cytoplasmic distribution observed in D. discoideum cells does not necessarily reflect the absence of protein aggregation. To probe for the presence of amyloid aggregation, we subjected whole-cell lysates of Q103- or N47-expressing cells to SDD-AGE[93]. This method allows to distinguish soluble monomers from SDS-resistant high molecular weight species. We detected SDS-resistant material in both cell lines. However, the amount of SDS-resistant material was very low. In addition, the fractions of Q103 and N47 differed in size; structures formed by N47 were of higher molecular weight than those formed by Q103 (Fig. 3.3B). However, this might just be a consequence of aberrant running behavior of the Q103 monomer in the SDD-AGE. To clarify this, we performed filter retardation assays with whole cell lysates. This assay specifically detects SDS-resistant aggregates of large size. We observed retention of N47 in the presence of increasing SDS concentrations (Fig. 3.3C). On the contrary, we could not detect insoluble material in

41 Results

Figure 3.3: Q103 and N47 do not aggregate in the cytosol of D. discoideum. (A) Fluorescence microscopy of D. discoideum cells expressing GFP-tagged aggregation-prone proteins (Q103, N47) and control peptides (Q25, N25). The numbers give the percentage of cells showing the observed distribution pattern. The majority of cells showed diffuse cytosolic fluorescent signal. The location of the nucleus is visualized by DAPI staining. (B) Biochemical analysis of whole cell extracts of D. discoideum using semi-denaturing detergent agarose gel- electrophoresis (SDD-AGE) [67]. SDS-insoluble material is distinguishable by its retarded migration behavior. Both Q103 and N47 show low amounts of SDS-resistant material, although with differing size. (D) Filter retardation assay of whole cell extracts of D. discoideum cells supplemented with increasing amount of SDS. Large aggregates are retained on the filter. N47-GFP forms large SDS-resistant aggregates that are retained on the filter whereas Q103-GFP is soluble in SDS and thus passes through the filter.

42 Results

Figure 3.4: Q103 and N47 form amyloid aggregates in the cytosol of S. cerevisiaeand HeLa cells (A) Fluorescent microscopy analysis of HeLa and S. cerevisiae-cells expressing GFP-tagged aggregation-prone proteins (Q103, N47) and control peptides (Q25, N25). Poly-asparagine proteins are not expressed in mammalian cells, thus characterization of N47-GFP is not possible in HeLa. In both organisms, the aggregation-prone marker proteins Q103 and N47 aggregate in the cytosol. The location of the nucleus in HeLa is visualized by DAPI stain (blue). (B) Biochemical analysis of whole cell extracts of D. discoideum using semi-denaturing detergent agarose gel- electrophoresis (SDD-AGE) [67]. SDS-insoluble material is distinguishable by size from SDS-soluble monomers. In both organisms, Q103 and N47 form SDS-resistant amyloid aggregates.

43 Results

Q103-expressing cells, even in the absence of SDS. Therefore, we conclude that N47-GFP does form SDS-insoluble material in D. discoideum whereas Q103-GFP does not. However, the fraction of insoluble N47-GFP in D. discoideum cells is very low in comparison to true amyloid aggregation in S. cerevisiae (N47 and Q103) and mammalian cells (Q103)1, where the majority of the material can be found in the SDS-insoluble fraction (Fig. 3.4B). Thus, we assume that N47-GFP forms amyloid-like aggregates in D. discoideum, but only in low amounts. Because we performed these biochemical experiments with whole cell lysates, it was unclear whether all cells contain SDS-resistant aggregates or only a small fraction of the cells. In agreement with the latter assumption, we detected a small fraction of cells where N47-GFP localized to distinct ﬂuorescent foci. These foci localized to the nucleus as judged by DAPI stain (Fig. 3.3A). Together, these ﬁndings suggest that Q103 and N47 are mainly soluble in D. discoideum cells, but N47 may form aggregates in the nucleus.

To further assess the proteostatic capacity of D. discoideum, we investigated the behavior of the prion domain (NM) of the yeast [PSI+] prion protein Sup35p. This domain switches between an aggregated and a non- aggregated state in S. cerevisiae. In addition, it has been shown to aggregate in the cytosol of mammalian Neuro2a cells[114] and body muscle cells in C. elegans[115]. However, when expressing NMWT-GFP in D. discoideum cells, we observed a diffuse cytosolic distribution and no formation of cytosolic aggregates (Fig. 3.5A). In addition, we could not detect SDS-resistant material when we analyzed the lysates by SDD-AGE (Fig. 3.5B). In Neuro2a cells, NM does not aggregate in the cytosol unless pre-formed fibrils are added to the cells. Therefore, we tried to induce conversion into the prion state by supplementing the media with in vitro assembled fibrils. However, NM remained diffusely distributed in D. discoideum, although assembled fibrils were competent in inducing cytosolic NM aggregation in Neuro2a cells (Fig. 3.5C). This suggests that NM is kept under tight control, thus prevent- ing conversion into a prion form.

1We could not express N47 in mammalian cells, probably because N runs cannot be translated as they are absent form mammalian proteomes [112,113].

44 Results

Figure 3.5: Aggregation of NM is tightly controlled in D. discoideum. (A) Fluorescent microscopy of D. discoideum cells expressing GFP-tagged NM and NM variants. The amino acid sequence of the variants is depicted above, N(turquoise) and Q(purple) are highlighted and their abundance indicated by percentage. The numbers give the percentage of cells showing the observed distribution pattern. (B) SDD-AGE of the cells in A, to assess the SDS-insoluble and SDS-soluble fraction of the proteins. (C) Induction of NM aggregation by in vitro assembled fibrils (upper panel) in D. discoideum (lower panel, left) and Neuro2a-cells (lower panel, right). Fibril assembly was measured by ThT emission. Assembled and non-assembled fibres were added to the tested cells. The position of the nucleus of HeLa is visualizes by DAPI stain (blue). (D) Comparison of aggregation behavior of NM and NM* in different S. cerevisiae backgrounds by SDD-AGE. NM* aggregated in the [rnq-] and ∆hsp104 background where NMWT remained soluble. 45 Results

To further investigate how D. discoideum handles aggregation-prone proteins, we analyzed variants of NM with distinct aggregation properties. First, we used a variant (NM*) which has a very high aggregation propensity in yeast. This behavior is due to modifications in the N-terminal domain, which cause higher nucleation propensity of the protein. Thus, the aggregation of NM* is independent of the co-inducing prion factor [RNQ+] and it only slightly depends on the disaggregase Hsp104 (Fig. 3.5D). Expression of NM* again did not lead to the formation of cytosolic aggregates. Rather, the majority of the cells showed diffuse cytosolic signal and only a small fraction of the cells displayed a nuclear signal (Fig. 3.5A). In agreement with the observations made for N47, the presence of nuclear accumulations coincided with a small fraction of SDS-resistant material (Fig. 3.5B). A previous study showed that the relative amount of Qs and Ns in NM can influence its aggregation behavior[81]. A variant in which all Qs were replaced with Ns (NMN) formed SDS-resistant amyloids, whereas replacing all Ns with Qs (NMQ) resulted in the formation of SDS-soluble amorphous aggregates. Surprisingly, when expressed in D. discoideum, both variants did not form cytosolic aggregates: all protein variants were diffusely distributed in the cytosol with rare accumulations within the nucleus. How- ever, the fraction of nuclear foci differed, with NMQ inducing less nuclear accumulations than NMN. Consistent with this, SDD-AGE analysis revealed a lower amount of SDS-resistant, high molecular weight structures. These findings show that, unlike in yeast, the relative amount of Ns and Qs has only minor effects on the aggregation propensity of N/Q-rich proteins in D. discoideum. In summary, these findings show that proteins, which exhibit a high aggregation propensity in other organisms, are generally kept soluble in D. discoideum cells. However, those proteins with higher aggregation propensities can accumulate in the nucleus, which is accompanied by the formation of a small fraction of SDS-insoluble material. Furthermore, we could show in a related study, that this behavior also applies to endoge- nous aggregation-prone proteins and is not an artifact of exogenous protein expression[116].

46 Results

Figure 3.6: Expression of aggregation-prone proteins does not aﬀect cellular health. (A) Comparing division time of D. discoideum-cells expressing aggregation-prone marker proteins (N47, Q103, NM*) to non-aggregating control proteins (N25, Q25). (B) Developmental states of the cells shown in (A). The expected developmental stages is depicted on the right. No measurable eﬀect on the progression through the cell cycle was detected. (C) Fluorescent microscopy analysis of a chimeric slug (cells expressing Q103-GFP and wild type AX2 cells) showed an even distribution of GFP.

3.3 Characterization of phenotypic effects Expression of aggregation-prone proteins does not affect cellular health Aggregating proteins, and, in particular, polyglutamine can interfere with cellular function[56,117–120]. Therefore, we tested the influence of Q/N- rich proteins on the growth and developmental cycle of D. discoideum. First, we measured the division rates of cells expressing Q103-GFP, N47-GFP or NM*-GFP and compared them to cells expressing non-aggregating Q25, N25 or wild type AX2 cells respectively. We did not detect a significant difference in the division time (Fig. 3.6A).

47 Results

Next, we tested whether expression of aggregation-prone marker proteins can influence the developmental cycle or cell fate decision. D. discoideum has a remarkable developmental cycle, in which the organism tran- sitions from a single cell state to a multicellular state. During the process of development, cells divide into two different populations: the prespore cells, which will eventually end up as spores in the fruiting body, and prestalk cells, which will build the stalk. We wondered whether the presence of aggregation-prone proteins can, first, alter the progression and completion of the developmental cycle in general, and second, whether the presence of such proteins can influence the decision of the cells towards either prespore or prestalk fate. However, we found no differences in the progression through the developmental cycle (Fig. 3.6B) in cells expressing aggregation- prone marker proteins and control cells. Next, we used chimeric slugs to probe whether expression of aggregation-prone marker proteins influences the cell fate decision. We found Q103-GFP expressing cells uniformly distributed throughout the slug (Fig. 3.6C), indicating that soluble Q103 has not measurable effect on differentiation. However, when we analyzed the distribution of NM*-GFP and N25- mRFPmars in chimeric slugs, we noticed that N25-expressing cells were enriched in the middle part of the slug (Fig. 3.7A, 3.7B right panel). In contrast, we detected several GFP-positive foci in the anterior and posterior part (Fig. 3.7A arrow, 3.7B left panel). To test whether these GFP foci corresponded to nuclear accumulations, we analyzed chimeric slugs of wild type AX2 cells and cells co-expressing NM*-GFP and H2B-mRFPmars as nuclear marker. Indeed, we found that the GFP-positive foci localized to the nuclei of the cells. We conclude that soluble NM* does not influence the distribution of cells within the slug, since we detect H2B-mRFPmars positive cells throughout the slug (the fluorescence signal of diffuse NM*-GFP is too low to be detected in an intact slug) (Fig. 3.7C). Taken together, the expression of soluble aggregation-prone proteins does not influence the distribution of the cells in the slug, although cells which express highly aggregation-prone marker proteins seem to preferentially accumulate in the prestalk region of the slug.

48 Results

Figure 3.7: Inﬂuence of NM* expression on cell fate decision during development. (A) Fluorescence microscopy analysis of chimeric slugs (NM*-GFP expressing cells, labeled with CellTrace and N25-mRFPmars expressing cells). Brigth GFP foci in the anterior and posterior regions are indicated by arrows. (B) Distribution of the GFP signal (left panel) and RFP signal (right panel) across the anterior-posterior axes. The GFP signals peaks in regions of the anterior and posterior end, whereas the RFP signal peaks in the middle part of the slug. (C) Chimera slug of cells co-expressing NM*-GFP and H2B-mRFPmars. Bright GFP foci in the anterior and posterior region (indicated by arrows) localize to the nucleus as judged by co-localization with H2B-mRFPmars.

3.4 Eﬀects of heat stress on aggregation-prone proteins Heat stress leads to reversible aggregation within the cytosol The observation that aggregation-prone proteins are kept soluble in the cytoplasm of D. discoideum raised the question which mechanisms might be involved in this process. A plethora of studies has shown that misfolded proteins within the cytosol are controlled by molecular chaperones[7,121,122]. To test whether the chaperone network is involved in the regulation of aggregation-prone marker proteins in D. discoideum, we applied additional stress to growing cells. We hypothesized that, by raising the temperature, we increased the overall amount of misfolded proteins, thereby challenging the chaperone system with a higher load of aggregated material. When we stressed the cells by increasing the temperature from

49 Results

Figure 3.8: Heat stress leads to reversible aggregation within the cytosol. (A) Fluorescence time-lapse microscopy analysis of D. discoideum cells expressing Q103-GFP (upper panel) and NM*-GFP (lower panel) during stress. Time-point indicated below, current temperature indicated above, cytosolic foci indicated by arrows (B) SDD-AGE analysis of the cells described in (A) after 3 hrs of heat stress at 30℃ shows an increase in SDS-insoluble material. (C) Quantiﬁcation of time-lapse microscopy (A) (error bars = SD, n = 9 FOV).

50 Results

23℃ to 30℃ for three hours[123], we observed the formation of cytosolic foci in cells expressing Q103-GFP as well as in cells expressing NM*- GFP (Fig. 3.8A). The number of cytosolic foci increased with the duration of stress. In addition, we observed an increase in the amount of SDS-insoluble aggregates. (Fig. 3.8B). In general, cytosolic protein aggregates are rigid, therodynamically stable structures. However, when we released the stress and grew the cell under normal growth conditions, the foci resolved over time (Fig. 3.8A,C). These findings show that the marker proteins used in this study have the ability to aggregate in D. discoideum. However, under normal growth conditions, aggregation is prevented. In mammalian cells, aggregated material accumulates in cytosolic compartments, the aggresomes[43,124]. To test whether D. discoideum employs a similar mechanism, we applied prolonged heat stress and measured the number of foci and their relative size. We observed an increase in area size over time for NM*-GFP that is accompanied by a decrease in foci numbers (Fig. 3.9A). This suggests that the cytosolic foci merged into larger deposits. However, the number and area size of cytosolic foci formed in Q103-GFP expressing cells did not change significantly over time. (Fig. 3.9A). Aggresome formation is dependent on active, microtubule-based transport[43,44]. In addition, it has been shown that actin also plays an important role in aggregate sorting in S. cerevisiae [125]. Therefore, we measured the mean square displacement of cytosolic stress foci to determine their mode of motion (Fig. 3.9B, right panel). For both, NM* and Q103, the measurement indicated subdiffusion (0 < α < 1)[106]. However, when we treated the cells with drugs that interfere with the cytoskeleton (latrunculin A), we observed a clear decrease in mobility in the trajectories of those aggregates (Fig. 3.9B, left panel). We conclude that the cytosolic foci in D. discoideum are not actively transported, but their movement may involve actin filaments. Whether other cytoskeletal elements such as microtubules are involved has to await the results from further experimental studies. In summary, these findings show that aggregation of Q103 and NM* is tightly controlled under normal conditions. However, when cells encounter stress, the proteins coalesce into mobile cytosolic foci, whose movement is aided by the cytoskeleton. Probably, these proteins are collected into larger deposits during prolonged heat stress.

51 Results

Figure 3.9: Mobility of cytosolic aggregates requires the cytoskeleton. (A) Quantiﬁcation of relative area of cytosolic foci (upper panel) and relative number of cytosolic foci per FOV in cells expressing Q103-GFP and NM*- GFP at 30℃ (error bars = SD, n = 9 FOV). (B) Tracking of Q103-GFP and NM*-GFP cytosolic foci. Trajectories of the foci (left panel) visualize the movement of foci within the cells in the presence (+LatA) or absence of latrunculin A (LatA). Mean square displacement analysis (right panel) is used to asses the mode of diﬀusion of the cells in the presence (black) or absence (red) of LatA (error bar = SD, n = 6 (NM*); 9 (NM*+LatA); 4 (Q103); 4 (Q103+LatA)).

52 Results

3.5 Characterization of Hsp101 function in D. discoideum Hsp101 is a major player in the control of aggregation-prone proteins during acute stress The observation, that aggregation-prone proteins aggregate under stress but are resolved upon stress release, suggests the involvement of members of the chaperone family in aggregation control. In yeast and plants, members of the Hsp100 protein family regulate aggregated proteins by reversing amorphous and amyloid aggregation[126]. At the same time they are essential for thermotolerance in these organisms[16,127,128]. We screened the proteome of D. discoideum for orthologs of Hsp100s proteins and found a potential candidate protein, Hsp101 (Fig. 3.10A). We characterized the expression levels of Hsp101 by Western blotting and immuno-detection and observed an increase in protein levels after heat stress (Fig. 3.10B). Next, we tested the influence of Hsp101 on aggregation-prone marker proteins. Overexpression of Hsp101 did not alter the subcellular localization of Q103 under normal growth conditions (data not shown). However, when we overexpressed Hsps101 in heat stressed cells, formation of cytosolic aggregates was prevented (Fig. 3.10C). Unfortunately, we could not over- express Hsp101 in the presence of NM*, as this resulted in severe impairment of growth. Next, we investigated the functional effects of Hsp101 inactivation. Because a knock-out of Hsp101 was not successful, we generated dominant negative variants of the protein (Walker A point mutation). For- mation of hetero-oligomers between wild type protein and the dominant negative variant has been shown to inactivate the disaggregase, as shown for other Hsp100 proteins[37]. When we expressed the mutant disaggregase in a Q103-GFP or NM*-GFP background, foci formation during heat stress was not altered (data not shown). However, inactivation of Hsp101 prolonged the presence of cytosolic foci after stress release in comparison to control cells (Fig. 3.10D). These findings indicate that Hsp101 is specifically required for the clearance of aggregates after an acute stress event. Next, we tested whether Hsp101 is required for thermotolerance in D. discoideum as in other organisms. We applied prolonged heat stress and measured the relative increase in dead cells (Fig. 3.10E). Overexpression of

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Figure 3.10: Hsp101 is a major player in the control of aggregation-prone proteins during acute stress. (A) Phylogenetic tree of Hsp100 family proteins (A. thaliana At_Hsp101, D. discoideum Dd_Hsp101, E. coli Ec_ClpB, C. albicans Ca_Hsp104, S. cerevisiaeSc_Hsp104, S. pombe Sp_Hsp104). Numbers indicate the relation distance.(B) Analysis of Hsp101 expression in D. discoideum cells during normal growth and heat stress. (C) Formation of cytosolic aggregates was followed by of time-lapse fluorescence microscopy of cells expressing Q103 (black) and cells co-expressing Q103 and Hsp101 (red) during heat stress and recovery. The number of aggregates per cell was quantified (error bars = SD, n = 9 FOV). (D) Same as C except that the cells co-expressing Q103 (upper panel) or NM* (lower panel) and dominant negative Hsp101 variants (black, grey) during recovery from heat stress (error bars = SD, n = 9 FOV). (E) Effects of Hsp101 overexpression and inactivation on thermotolerance in D. discoideum. Cells were stressed at 34℃and 37℃ and the increase of dead cells in comparison to growth at 23℃ was determined (fold increase).

54 Results

Hsp101 led to a decrease in dead cells compared to control cells, while im- pairing Hsp101 function increased the fraction of dead cells. This suggests that Hsp101 functions in a similar manner as other members of the Hsp100 family in other species. Taken together, these data reveal that Hsp101 is an important player in the regulation of protein aggregation during stress, thus providing protec- tion against high temperatures.

3.6 Characterization of Dictyostelium chaperone function in S. cerevisiae Hsp101 can functionally replace Hsp104 in S. cerevisiae In order to characterize the molecular function of Hsp101 in more detail, we expressed it in the genetically accessible model eukaryote S. cerevisiae. Hsp101 has a high sequence similarity with budding yeast Hsp104 within the two AAA-domains, but less similarity within the N-terminal substrate binding domain (Fig. 3.11A). First, we tested the ability of Hsp101 to complement Hsp104 in conferring thermotolerance. We expressed Hsp101 in a ∆hsp104 background, where it restored the growth phenotype after heat stress and cells recovered in a similar manner as wild type cells (Fig. 3.11B). This finding shows that Hsp101 can confer thermotolerance in both D. discoideum and S. cerevisiae. Hsp104 is also essential for the maintenance of prions in S. cerevisiae[129]. Therefore, we tested the ability of Hsp101 to propagate the [PSI+] prion by using a plasmid-shuffle assay. We monitored the presence of prion proteins by a red-white prion reporter assay[93], where [PSI+] cells exhibit a white colony color, while [psi-] colonies are red (see 2.1.2.4). Upon deletion of Hsp104, [PSI+] cells are converted to [psi-][130]. However, when Hsp101 was expressed in these cells, they retain the white [PSI+] state (Fig. 3.11C upper panel). In addition, we probed for presence of [PSI+] fibrils by SDD- AGE. We confirmed that all white [PSI+] cell lines contained SDS-resistant amyloid fibrils (Fig. 3.11C lower panel). We also noticed that the size of the fibrils was dependent on the expression level of Hsp101, in agreement with observations made for Hsp104[129]. Thus, Hsp101 is the first non-fungal disaggregase that can functionally replace Hsp104 in S. cerevisiae.

55 Results

Figure 3.11: Hsp101 can functionally replace Hsp104 in S. cerevisiae (A) Sequence comparison between Hsp104 and Hsp101. (B) Thermotolerance assay in S. cerevisiae. Expression of Hsp101 rescues the growth phenotype of ∆hsp104 during heat shock (right panel). (C) Hsp101 can functionally replace Hsp104 in the replication cycle of the [PSI+] prion. The prion state of the cells is assessed by the colony color ([PSI+] white, [psi" ] red). Expression levels of Hsp104 and Hsp101 were determined by immunoblotting. SDS-resistant amyloid fibers were identified using semi-denaturing detergent agarose gel-electrophoresis (SDD-AGE). (D) The inheritance of Hsp101- and Hsp104-dependent [PSI+] was investigated by mating with the indicated strain backgrounds. (E) Effect of of 5 mM GdnHCl, a specific inhibitor of Hsp104, on prion curing. Note that [PSI+] is only lost in the Hsp104-expresing strain (left) but not in the Hsp101-expressing strain (right). (F) Two additional yeast prions, [NRP1C+] and [URE2C+], were faithfully replicated by Hsp101. Note that the [NRP1C+] also retains its Hsp100-independent heat sensitivity in the presence of Hsp101.

56 Results

Although the generated prion states were phenotypically very similar, it could still be possible that the prion states in Hsp101 and Hsp104- expressing cells are incompatible. To test this, we performed mating experiments where one parent strain was [PSI+]Hsp101 or [PSI+]Hsp104, and the other [psi-]Hsp104 or [psi-]Hsp101. After tetrad dissection, we found all hap- loid daughter cells to be [PSI+], indicating that fibrils formed by one of the disaggregases can be maintained by the other and vice versa (Fig. 3.11D). Despite these functional commonalities between Hsp101 and Hsp104, additional experiments revealed considerable differences as well. The conversion of [PSI+] cells to [psi-] is generally referred to as "curing". It can be caused by deletion of Hsp104 (see above) or inhibition by millimolar concentrations of the specific inhibitor GdnHCl[131]. Surprisingly, when we treated [PSI+]Hsp101 cells with GdnHCl, we did not observe a curing effect, in contrast to [PSI+]Hsp104 cells (Fig. 3.11E). Together, these findings suggest that, although Hsp101 can functionally replace Hsp104, it might employ a different mechanism. It has been suggested that the [PSI+] prion interacts with Hsp104 in a unique manner[132]. To exclude that our observations are only specific to [PSI+], we tested the ability of Hsp101 to propagate two other well- characterized yeast prions: [URE2C+] and [NRP1C+]. We could induce and maintain the [PRION+] state in cells expressing Hsp101 for both tested proteins (Fig. 3.11F). In agreement with our previous observation, these prions were also not cured by treatment with GdnHCl. Furthermore, the prions kept their specific properties, such as the heat-induced curing of [NRP1C+][50]. This indicates that the ability of Hsp101 to maintain prions in S. cerevisiae applies to all prions and is not specific for [PSI+]. In addition to the functional characterization of Hsp101, we used the yeast system to test potential candidates of the Hsp40 family from D. discoideum for their function. The proteome of D. discoideum contains four candidates that showed high sequence similarity to Ydj1p, the major Hsp40 protein in S. cerevisiae (Fig. 3.12A). We tested the top two candidates, Ddj1 and DnaJa1, for their ability to complement Ydj1 function in a ∆ydj1 background. Both proteins were able to restore the growth phenotype resulting from YDJ1-deletion in the same extent as Ydj1p or Sis1p, another main Hsp40 protein in S. cerevisiae (Fig. 3.12B). This shows that the candidate

57 Results

Figure 3.12: Functional characterization of Hsp40 orthologs in D. discoideum (A) Phylogenetic tree of Hsp40 family proteins, comparing S. cerevisiae Ydj1p and Sis1p with four candidates from D. discoideum DDB_G0278789, DDB_G0280037, DDB_G0291568, DDB_G0282313. (B) Complementation assay. Two candidate Hsp40 proteins (DDj1p and DnaJa) are able to complement the growth phenotype of ∆ydj1 under normal growth conditions and under stress. The rescue of the growth phenotype is comparable to expression of Hsp40 proteins from S. cerevisiae (Ydj1p and Sis1p) proteins can function as Hsp40 homologs. The next step will be the characterization of their function and their eﬀects on aggregation-prone proteins in D. discoideum. Thus, we conclude that D. discoideum chaperones can functionally replace chaperones in S. cerevisiae that have speciﬁc functions in prion replication and thermotolerance.

3.7 Characterization of nuclear accumulations Nuclear accumulations are dynamic structures When analyzing the distribution of aggregation-prone marker proteins in D. discoideum, we noticed an occasional nuclear signal for N47-GFP (Fig. 3.3A) and NM*-GFP (Fig. 3.5A). We also observed the GFP signal ac- cumulating in the nucleus over time (data not shown). A detailed characterization of the nuclear signal using fluorescence microscopy revealed that 75 % of the cells showed diffuse nuclear signal, with occasionally occurring small foci; in the remaining 25 % we observed two distinct fluorescent foci (Fig. 3.13A upper panel). Analysis by correlative light and electron microscopy (CLEM) showed that these foci co-localize with electron dense structures in the vicinity of the nuclear membrane (Fig. 3.9D lower panel). Previous studies identified those structures as the nucleoli of the cells[133]. This suggests that aggregation-prone proteins are transported to the nucleus and can accumulate in the nucleolus. Interestingly, we did not find electron-dense fibrils in the nucleus or the

58 Results

Figure 3.13: Nuclear accumulations are dynamic structures. (A) Light microscopy and correlative light and electron microscopy (CLEM) analysis of nuclear accumulation. Nuclear accumulations appear in two patterns. Numbers indicate the percentage of cells (with nuclear signal) showing the depicted conformation. Electron dense structures within the nucleus correspond to the nucleolus. (N, nucleus; Nu, nucleolus) (B) Fluorescence recovery after photobleaching (FRAP) analysis of nucleolar NM*-GFP signal (upper left panel) and correspondig time- lapse microscopy (lower left panel) in comparison to FRAP of nulcear NM*-GFP signal (right panel). Nucleolar structures display a high mobile fraction (80%) while the nuclear signal does not recover. Time-lapse microscopy images are shown in false coloring, color legend at the left indicates intensities (C) Time-lapse microscopy of cells co-expressing NM*-GFP (green) and H2B-mRFPmars (red) during mitosis. The GFP signal re-locates to the cytosol 10 min before cell division and 5 min before nuclear division.

59 Results nucleolus, which are usually observed for amyloid protein aggregates[134]. This indicates that the nuclear and nucleolar accumulations are not amyloid aggregates. To further investigate this, we measured the mobility of the nucleolar accumulations by fluorescence recovery after photobleaching (FRAP). Interestingly, we obtained relatively quick recovery times and a high mobile fraction of 80 % (Fig. 3.13C, left panel). This suggests that these accumulations are dynamic structures and not rigid aggregates. The recovery of the GFP signal might be accomplished by re-arrangement of material between the nucleoli or from soluble material within the nucleus. We can exclude that the import of cytosolic material into the nucleus is responsible for the observed recovery, since FRAP analysis of the diffuse nuclear signals did not show any signal recovery, which could only be occurring due to nuclear import of material (Fig. 3.13C, right panel). Further evidence supporting the assumption of dynamic nuclear structures came from observations of D. discoideum cells during cell division. When we followed cells with nuclear accumulations through mitosis, we found that the nuclear NM*-signal rapidly disappeared before division of the nucleus (5 min) and division of the cell (10 min) (Fig. 3.13B). Interest- ingly, the daughter cells did not re-accumulate the nuclear signal (data not shown), suggesting that these accumulations were successfully cleared during or shortly after mitosis. The nucleolar accumulations could result from impairment of cellular functions or from the fact that these cells experienced a high level of stress. Therefore, we tested whether heat stress can increase the number of nuclear foci. However, in both NM- and N47-expressing cells, the number of foci remained unchanged during stress (Fig. 3.14A). Next, we tested whether impairment of proteostasis can influence nuclear accumulation. Therefore, we treated NM*-expressing cells with a series of proteasomal inhibitors (Epox- omicin, Lactacystin and MG132). Interestingly, we observed a significant increase in foci numbers (Fig. 3.14B). This finding is in agreement with previous studies that showed that the proteasome of D. discoideum is located in the nucleus[135]. Taken together, this suggests that cells, which suffer proteostatic stress accumulate aggregation-prone proteins in the nucleus.

60 Results

Figure 3.14: Nuclear accumulations result from proteasomal impairment. (A) Time-lapse ﬂuorescence microscopy of D. discoideum cells expressing nuclear N47-GFP (left panel) and NM*-GFP (right panel) during heat stress (error bars = SD, n = 9 FOV). Number of nuclear accumulation remained unchanged. Note that there was no change during stress. (B) Eﬀects of proteasomal inhibition (Epoxomicin, Lactacystin, MG132) on number of nuclear NM*-GFP accumulations. Cell were treated for 14hrs with proteasomal inhibitors. Inhibition of the proteasome increased the number of nuclear accumulations (error bars = SD, n = 25 FOV).

61 Results

Taken together, these data indicate that the nuclear accumulations are caused by an impairment of the ubiquitin-proteasome system (UPS), but do not result in the formation of rigid amyloid aggregates. Instead, aggregation-prone proteins are deposited in the nucleolus and can be resolved during mitosis.

62 Discussion 4. Discussion

4.1 Asparagine- and glutamine-rich stretches are conserved and functionally relevant The propensity of a protein to misfold and aggregate is determined by its specific amino acid sequence. In particular, asparagine- and glutamine- (N/Q)-rich sequences have been shown to have a high aggregation tendency.[67]. A multispecies analysis showed that the occurrence of N/Q-rich sequence stretches varies substantially between organisms[78]. This study revealed that the prevalence of N/Q-rich sequences was particularly high in the social amoebae D. discoideum. We characterized the N/Q-rich proteome of Dictyostelium further by using more sophisticated bioinformatic tools. Using an HMM-based algorithm trained with naturally occurring N/Q- rich sequences, we revealed an exceptionally high number of potentially aggregation-prone proteins in D. discoideum. These aggregation-prone proteins could be associated with specific groups of GO-terms and specific protein superdomain families. These findings suggest a biological function for the N/Q-rich stretches in D. discoideum. Previous studies have investigated the question of functional signifi- cance. The first analysis of poly-amino acid stretches in D. discoideum showed that poly-amino acid stretches occur only in specific protein families[84]. More recent work suggested that poly-amino acid repeats might function as microsatellites[136]. However, Sucgang et al.[137] provided data that contradicts the notion that N/Q-rich sequence stretches are functionally relevant: the study compared poly-amino acid repeats in D. discoideum and the close relative D. purpureum. They found only a low number of protein orthologs with conserved poly-amino acid repeats. Based on this finding they concluded that poly-amino acid stretches are randomly distributed and may occur due to shared physiological properties in DNA replication and repair. In contrast, our approach identified a high number of ortholog proteins in D. discoideum and D. purpureum. In addition, we found a remarkable overlap of protein superdomain families. An ex- planation for this discrepancy may be found in the different methods used. Sucgang et al. used direct sequence alignment. In this method, stretches of differing size might lead to mis-alignments, thus decreasing the num-

63 Discussion ber or hits, as noted by the authors themselves[137]. In contrast, our approach used a sliding window to identify amino-acid stretches with a certain "prion probability" and then annotated the region as candidate prion domain (cPrD). Such a more flexible assignment of protein domains facilitated the subsequent identification of protein orthologs. This suggests that N/Q-rich sequence stretches are not randomly occurring sequence features and may have important biological functions. This assumption is further supported by the observation that the association of RRM-domains with N/Q-rich stretches is conserved in yeast[107] and mammalian proteins[61]. Interestingly, many of these proteins have been linked to the pathology and genetics of protein misfolding diseases, such as amyotrophic lateral sclerosis (ALS), Alzheimer’s and Huntington’s disease[61]. In addition, we find that N/Q-rich proteins are associated with similar GO-clusters in S. cerevisiae, D. melanogaster and H. sapiens[107], although we were able to find the same GO-terms within a cluster only in reare cases. This might be due to the fact that our algorithm relies on yeast prion proteins to assign "prion probabilities" to amino acids within a sequence. Thus, although yeast prion probabilities turned out to be a good predictor for protein aggregation propensities in other organisms, we speculate that the the amino acid composition of these domains may be modified by different functional constraints in other organisms. Nevertheless, these findings suggest that N/Q-rich sequence stretches are biologically relevant and conserved from yeast to man despite the fact that they are prone to misfold and aggregate.

4.2 D. discoideum evolved mechanisms that render it resilient to aggregation-prone proteins The expression of aggregation-prone polyQ-proteins is associated with protein aggregation in the cytosol and causes cytotoxic effects[110,118–120,138]. To test whether N/Q-rich proteins have similar con- sequences in D. discoideum, we expressed a number of aggregation-prone marker proteins in D. discoideum. Surprisingly, we did not observe the formation of cytosolic aggregates for any of the tested proteins. On the contrary, Q103-GFP and NM-GFP remained soluble, as judged by ﬂuorescence microscopy and biochemical analysis. The N-rich variant of Q103, N47, as

64 Discussion well as the highly aggregation-prone variants of NM (NM*, NMN and NMQ) also showed a diffuse cytosolic localization, but exhibited a small amount of aggregated material that was accompanied by nuclear accumulations. This is in stark contrast to observations made in S. cerevisiae, C. elegans, D. melanogaster and mammalian cells, where all tested proteins aggregated in the cytosol[110,118–120,138]. Moreover, the expression of polyQ-proteins in these organisms is detrimental, because of cytotoxic effects[110,118–120,138]. However, in D. discoideum, the expression of aggregation-prone marker proteins did no lead to measurable effects on cellular health in the vegetative cycle or during development. This suggests that D. discoideum has evolved mechanisms which render this organism resilient to aggregation-prone proteins. By further studying the specific adaptations underlying this resilience we expect to get important insight into the ways in which an organism can handle a highly aggregation-prone proteome.

4.2.1 Hsp101 is a key player in the acute stress response in D. discoideum In an attempt to identify factors involved in the regulation of aggregation-prone marker proteins in D. discoideum, we challenged the chaperone system by applying stress. We reasoned that the increase in misfolded proteins occurring during stress would challenge the chaperone system. Indeed, we observed formation of cytosolic aggregates in the cells and these aggregates are dissolved after removal of the stress. These data high- lights a role for the chaperone system in regulating protein aggregation in D. discoideum. The cellular chaperone system consists of different chaperone families, which collectively act on misfolded proteins to ensure either their refolding or degradation. In general, members of the Hsp40 family recognize unfolded protein species and act together with Hsp70 family proteins to prevent aggregation in an ATP-dependent manner. In bacteria, fungi and plants, the Hsp100 family proteins, which belong to the AAA+-ATPases, act as disaggregases in cooperation with the Hsp40/Hsp70 system to unfold protein aggregation[6]. We identified and characterized a disaggregase ortholog in D. discoideum (Hsp101) and analyzed its influence on aggregation-prone pro-

65 Discussion teins. The formation of aggregates in response to heat stress was prevented by overexpression of Hsp101, whereas compromising Hsp101 function impaired the clearance of aggregates, suggesting that the disaggregase plays a key role in the control of aggregation. This is further supported by the finding that Hsp101 can confer thermotolerance in both, D. discoideum and S. cerevisiae. Thermotolerance requires the dissolution of aggregated material in the cell[6]. Although disaggregases from D. discoideumand S. cerevisiae might employ different mechanisms, both function in a similar manner and resolve protein aggregates. These findings are consistent with previous reports which highlight the role of molecular chaperones in regulation of aggregation-prone proteins and their cytotoxic effects: It has been shown that members of the Hsp40 family can prevent the aggregation of polyglutamine proteins in mammalian cells[139,140]. In D. melanogaster, the co-chaperones Hsp40 and the Hsp70-related Hsp110 can act together to suppress polyglutamine- induced cell death[141]. Interestingly, Muralidharan et al.[142] showed that in Plasmodium falciparum, an organism that also has a very asparagine- and glutamine-rich proteome, cytoplasmic Hsp110 is able to prevent aggregation of asparagine-rich proteins in cultured malaria parasites and mammalian cells. However, except for P. falciparum, the organisms used in the mentioned studies do not possess orthologs of disaggregases of the Hsp100 family. Hence, the utilization of disaggregases for controlling aggregation may also be a specific adaptation in D. discoideum, but it remains to be tested. Nevertheless, other components of the chaperone network, particularly the co-chaperones Hsp40 and/or Hsp110, may also be involved in the regulation of protein aggregation in D. discoideum. In particular, they may be involved in proteostasis during normal growth conditions, as Hsp101 seems to preferentially act during an after stress. Their involvement should be assessed by using specific chemical inhibitors of Hsp70 or Hsp90 chaperones, something that we will address in future experiments. Nonetheless, the data presented in this study provide strong evidence that the chaperone machinery has undergone specific changes to coordinate the cellular response to aggregates in D. discoideum.

66 Discussion

4.2.2 The cytoskeleton might be involved in the organiza- tion of stress-inducible aggregates Cells can react to an increase in aggregated material by sequestering aggregates into specialized compartments. In agreement with this, we noticed that the average size of NM* foci increased over time while the relative number of foci decreased when we applied heat stress for a prolonged time period. This suggests that small aggregates merge into larger entities, as has been proposed previously for other organisms[124,125]. Further characterization of aggregate movement revealed no superdiffusive behavior, consistent with the fact that aggregates are not actively transported. Treatment with the actin inhibitor latrunculin, however, reduced the diffusion constant of aggregates. This suggests that actin might be involved in the movement of aggregates but the underlying mechanism remains elusive. These findings are in line with observations made in mammalian cells. During stress or disease conditions, cells accumulate misfolded proteins when the capacity of the proteasome to degrade them is exceeded[43,124]. The protein aggregates are transported along microtubules by dynein to the MTOC[44,143], where they coalesce into aggresomes[43]. Aggresomes are associated with the proteasome and chaperone proteins of the Hsp40/Hsp70 family[44,46,124,144]. It has been suggested that the aggregated proteins within the aggresomes are degraded by the proteasomes present in the structures. Moreover, the formation of aggresome might be used to concen- trate misfolded proteins to increase the capture efficiency into autophagic structures[46,124]. It has also been suggested that in S. cerevisiae, segregation of aggregated proteins during cytokinesis depends on the actin cytoskeleton[125]. How- ever, this hypothesis is controversial[145]. Nevertheless, it might be possible that D. discoideum employs a mechanism that is similar to the mammalian system. However, whether the cytoskeleton plays a role in the organiza- tion of aggregated material in D. discoideum needs to be elucidated in more detail, since our findings represent only preliminary data. For example, it remains to be tested if and to which extent microtubules are involved in the process.

67 Discussion

4.2.3 The nucleus is a new compartment for proteostasis Apart from cytosolic compartments, protein aggregates can also be se- questered to the nucleus. In agreement with this, we noticed that highly aggregation-prone variants are occasionally accumulated in the nucleus of D. discoideum cells. Although the occurrence of nuclear aggregates was accompanied by the formation of low amounts of SDS-resistant aggregates, we could show that the nuclear accumulates are dynamic structures. Inter- estingly, we found that these aggregates accumulated also in the nucleolus of the cells. The accumulation of aggregated proteins in the nucleus and, particularly, in the nucleolus, has been reported previously for mammalian cells. Disease-causing variants of human huntingtin form nuclear aggregates which are found adjacent to the nucleolus[146]. Nuclear aggregates are also found in spinocerebral ataxia, another neurodegenderative disease caused by aggregation of polyQ proteins[146,147]. But not only diesease conditions cause nuclear accumulation of proteins; upon proteasome inhibition, stress-related and non-stress related proteins translocate to the nucleolus and accumulate in so called nuclear aggresomes[148]. It has been suggested that the threshold for nuclear aggresome formation lies in the ability of the UPS to degrade proteins[148]. When UPS function is hampered, ubiquitinated proteins accumulate locally at the sites of proteasome enrichment. Indeed, proteasomes localize to the nucleolus during proteotoxic stress[149,150]. Aggresomes form within the nucleoli[151] and their formation is dependent on intact nucleoli[151,152]. Our ﬁnding that aggregation-prone proteins also accumulate in the nucleolus suggest that Dictyostelium may utilize this compartment for turning over misfolded N/Q-rich proteins.. Interestingly, Park et al.[153] reported recently that mildly misfolded proteins are shuttled to the nucleus for degradation in both S. cerevisiae and mammalian cells. Two pieces of evidence support the assumption that this might also apply to D. discoideum nucleoli. First, it has been shown that proteasomes of D. discoideum are highly enriched in the nucleus[135,154]. Second, in this study, we observed a signiﬁcant increase in the accumulation of misfolding-prone proteins in the nucleus upon proteasome inhibition. However, it remains unclear whether the accumulations are storage depots for misfolded proteins or are actively engaged in degrading misfolded proteins. It also remains to be determined how the proteins are transported

68 Discussion into the nucleus. Thus, we conclude that D. discoideum has evolved a nuclear protein quality control system (nPQCS) that plays an important role in the protein homeostasis of the cell.

In summary, we found molecular pathways that control highly aggregation-prone proteins in D. discoideum during both normal growth and under stress. This suggests that D. discoideum has adopted speciﬁc mechanisms to prevent misfolding. By studying these processes in detail we will learn how a complex protein-folding environment can be managed successfully.

4.3 Cell sorting mechanisms may be used for proteostasis control during development In addition to the molecular mechanisms that cells have evolved to respond to protein aggregation[9,54], asymmetrically dividing cells can use specific mechanisms to generate aggregate-free offspring[155–158]. For in- stance, oxidatively damaged proteins are asymmetrically sorted to the mother cell in S. cerevisiae[155]. However, the exact molecular mechanism underlying this asymmetry is still under debate[125,159,160]. Interestingly, Rujano et al.[157] showed that asymmetric inheritance of aggregated proteins also occurs in higher eukaryotes. They observed asymmetric inheritance of polyQ-proteins in stem cells, where aggresomes were retained in shorter-lived, differentiated daughter cells. Similar observations were made in neuroblasts of D. melanogaster. We tested whether D. discoideum employs similar mechanisms, but found that the nucleolar accumulations were dissolved during mitosis (Fig 3.13C). However, it still remains to be tested whether cells that divide during or after stress segregate cytosolic stress-induced protein damage asymmetrically. Our observations so far seem to suggest that there may not be a strong segregation bias, in agreement with the fact that D. discoideum divides predominantly symmetrically under normal growth conditions[161,162]. How- ever, D. discoideum can generate a different sort of asymmetry during development. When cells encounter starvation conditions, they switch from vegetative growth to the developmental cycle, in which cells differentiate into two distinct cell types: spore cells and stalk cells. Interestingly, we ob-

69 Discussion served that cells with nuclear NM*-GFP accumulations preferentially seg- regated to the anterior and posterior region of chimera slugs. These regions are comprised of cells expressing prestalk gene markers[163]. This suggests that cells harboring nuclear accumulations may be sorted to the prestalk regions during development, most likely to clean the population of cells that have accumulated too much protein damage. This is in agreement with the hypothesis that development can act as a biological filter for gene function[85]. The question what controls fate decision in D. discoideum during the developmental cycle, has been controversially discussed for many years. It has been suggested that the cell-cycle state of cells before starvation plays a role. Consistent with this, cells in S to early G2 phase display a higher prestalk tendency while cells in mid to late phase display an increased prespore tendency[89]. Ca2+ concentrations are also important for fate decision[164] and interlinked to the cell-cycle state[165]. Moreover, the metabolic state can influence development and glucose-starved cells are primarily found in prestalk regions[166,167]. Interestingly, Castillo et al[168] showed that cells stressed by growth in acidic conditions are preferentially sorted to the stalk. Therefore, we speculate that stress in general might induce a specific fate decision towards stalk development. Interestingly, it has been suggested, that the cAMP signaling pathway, which triggers development in Dictyostelia, has evolved from an intercellular signaling pathway that transduces the perception of environmental stress to the cell[87]. Thus, our data represents preliminary but exciting observations, suggesting that Dic- tyostelia use their developmental program to purge the population of cells that have been impaired by protein damage and stress. Our future effort will aim to verify the influence of protein aggregates and protein damage on the fate decision of the cells. If our hypothesis proves to be right, this will give very important insights into the question what drives the fate decision of D. discoideum cells. However, even if protein damage is not involved in cell fate descision, the question remains why D. discoideum employs the developmental cycle to remove damaged cells. On the one hand, this provides a means to generate aggregation-free offspring, as previously proposed for stem cells[157]. On the other hand, entry into the developmental cycle stops the progression

70 Discussion through the cell cycle[86] and we have evidence that successful clearing of aggregates under normal growth conditions can occur during mitosis. Fur- thermore, the protein quality control system requires energy for the control of protein aggregates, a condition which might not be given in starving cells. Therefore, co-option of the of the developmental sorting mechanism might be an adaptation born out of necessity.

71 Plasmids A. Plasmids

A.1 Gateway cloning

72 Plasmids

A.2 Expression in D. discoideum For details see Veltman et al.[169].

73 Plasmids

A.3 Expression in S. cerevisiae For details see Alberti et al.[170].

74 Plasmids

75 Plasmids

A.4 Expression in HeLa

A.5 Expression in E. coli For details see Alberti et al.[67].

76 Primer B. Primer

Name Sequence GFP_as GTA ATC CCA GCA GCT GTT AC GFP_s CAC TGG AGT TGT CCC AAT TC GFP_R CCA TCT AAT TCA ACA AGA ATT GGG ACA AC M13_rev GGA AAC AGC TAT GAC CAT G Sequencing M13_univ TGT AAA ACG ACG GCC AGT D1_WalkerB_F TTA TTC ATT GAT GCA ATC CAT TTG GTA TTG D1_WalkerB_R CAA TAC CAA ATG GAT TGC ATC AAT GAA TAA D2_WalkerB_F GTA TTG TTT GAT GCA GTT GAA AAA GCT CAT utagenesis

M D2_WalkerB_R ATG AGC TTT TTC AAC TGC ATC AAA CAA TAC AttB_univ_F GGG GAC AAG TTT GTA CAA AAA AGC AGG CTT CGA AGG AGA TAA CAA AAT G AttB_univ_R GGG GAC CAC TTT GTA CAA GAA AGC TGG GTC ddHsp101_A ATG TCA TTT AAT CCA GAA GAA TTT AC ddHsp101_B CAA CGA CTC TAT TAT GAA GAT GAT CAG CC ddHsp101_C GGC TGA TCA TCT TCA TAA TAG AGT CGT TG ddHsp101_D TTA TTT AAT AGT TTT TTG TTT TTT GGT TGG AGA AGC TGG AC ateway cloning

G Dnaja_F AGG AGA TAA CAA AAT GGT AAA AGA AAA AGA ATA TTA TGA AAG ATT AG Daja1_R CAA GAA AGC TGG GTC TTA TTG TTG TTG ACA CTG TTG TGC TTG TT Daja1_R_stopless CAA GAA AGC TGG GTC TTG TTG TTG ACA CTG TTG TGC TTG TT Ddj1_F AGG AGA TAA CAA AAT GCC CGA TAA TAA ATT TTA TGA TAT TTT AG Ddj1_R CAA GAA AGC TGG GTC TTA TTG TTG AGC ACA AGA AAC Ddj1_R_stopless CAA GAA AGC TGG GTC TTG TTG AGC ACA AGA AAC

77 Cell lines C. Cell lines

C.1 D. discoideum

name genetic background source

AX2-214 axeA2, axeB2, axeC2 G. Gerisch, DictyBase

AX2 Hsp101-GFP AX2 pDM353-Hsp101-GFP this study

AX2 Hsp101K213A-GFP AX2 pDM353-Hsp101K213A-GFP this study

AX2 Hsp101K613A-GFP AX2 pDM353-Hsp101K613A-GFP this study

AX2 Hsp101K213A K613A- AX2 pDM353-Hsp101K213A K613A- this study GFP GFP

AX2 NM*-GFP AX2 pDM353-Sup35NM*-GFP this study Hsp101K613A-mRFPmars pDM451-Hsp101K613A-mRFPmars

AX2 NMWT-GFP AX2 pDM353-Sup35NMWT-GFP this study

AX2 NM*-GFP AX2 pDM353-Sup35NM*-GFP this study

AX2 NMN-GFP AX2 pDM353-Sup35NMN-GFP this study

AX2 NMQ-GFP AX2 pDM353-Sup35NMQ-GFP this study

AX2 mRFPmars-H2B AX2 #639-14 A. Mueller- Taubenberger

AX2 NM*-GFP AX2 #639-14 this study mRFPmars-H2B pDM353-Sup35NMWT-GFP

AX2 NM*-GFP AX2 pDM353-Sup35NM*-GFP this study Hsp101K213A-mRFPmars pDM451-Hsp101K213A-mRFPmars

78 Cell lines

name genetic background source

AX2 NM*-GFP AX2 pDM353-Sup35NM*-GFP this study Hsp101K613A-mRFPmars pDM451-Hsp101K613A-mRFPmars

AX2 N25-GFP AX2 pDM353-N25-GFP this study

AX2 N25-mRFPmars AX2 pDM354-N25-mRFPmars this study

AX2 N47-GFP AX2 pDM353-N47-GFP this study

AX2 Q25-GFP AX2 pDM353-Q25-GFP this study

AX2 Q103-GFP AX2 pDM353-103-GFP this study

AX2 Q103-GFP AX2 pDM353-Q103-GFP this study Hsp101-mRFPmars pDM451-Hsp101-mRFPmars

AX2 Q103-GFP AX2 pDM353-Q103-GFP this study Hsp101K213A-mRFPmars pDM451-Hsp101K213A-mRFPmars

AX2 Q103-GFP AX2 pDM353-Q103-GFP this study Hsp101K613A-mRFPmars pDM451-Hsp101K613A-mRFPmars

79 Cell lines

C.2 S. cerevisiae

name genetic background source

A4713 Mata, leu2-3,-112; his3-11,-15; trp1- YJW584,[171] 1; ura3-1; ade1-14; can1-100

A4712 Matalpha, leu2-3,-112; his3-11,-15; YJW509,[171] trp1-1; ura3-1; ade1-14; can1-100

∆hsp104 A4713, Hsp104::KanMX Alberti lab, MPI- CBG

∆hsp104 Hsp101 A4713, Hsp104::KanMX, this study pAG304GPD-Hsp101

∆hsp104 ADH-Hsp101 A4713, Hsp104::KanMX, this study pAG415ADH-Hsp101

∆hsp104 GAL-Hsp101 A4713, Hsp104::KanMX, this study pAG415GAL-Hsp101

∆hsp104 GPD-Hsp101 A4713, Hsp104::KanMX, this study pAG415GPD-Hsp101

∆hsp104 SUP35-Hsp101 A4713, Hsp104::KanMX, this study pAG415SUP35-Hsp101

∆ydj1 Mata, his3-0, leu2-0, met15-0, ura3- Giaever et 1, [RNQ+], ydj1::KanMX4 al.,[172]

∆ydj1 Ddj1 Mata, his3-0, leu2-0, met15-0, this study ura3-1, [RNQ+], ydj1::KanMX4 pAG415GPD-Ddj1

∆ydj1 DnaJa Mata, his3-0, leu2-0, met15-0, this study ura3-1, [RNQ+], ydj1::KanMX4 pAG415GPD-DnaJa

80 Cell lines

name genetic background source

∆ydj1 Ydj1 Mata, his3-0, leu2-0, met15-0, this study ura3-1, [RNQ+], ydj1::KanMX4 pAG415ADH-Ydj1

∆ydj1 Sis1 Mata, his3-0, leu2-0, met15-0, this study ura3-1, [RNQ+], ydj1::KanMX4 pAG415ADH-Sis1

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