Unraveling the physiopathological actions of the newly discovered Aη peptides in the brain Maria Mensch
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Maria Mensch. Unraveling the physiopathological actions of the newly discovered Aη peptides in the brain. Molecular biology. Université Côte d’Azur, 2020. English. NNT : 2020COAZ6001. tel- 03168655
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Étude du rôle pathophysiologique des peptides Aη récemment découverts dans le cerveau
Maria MENSCH Institut de Pharmacologie Moléculaire et Cellulaire
Présentée en vue de l’obtention Devant le jury, composé de : du grade de docteur en Dr Yoon, CHO, MC/HDR, CNRS UMR 5287-Laboratoire INCIA (Bordeaux), Rapportrice Sciences de la Vie et de la Santé Dr Thierry AMÉDÉE, DR, d’Université Côte d’Azur CNRS UMR 5297-Laboratoire IINS (Bordeaux) Rapporteur Dr Corinne, BEURRIER, CR Dirigée par : Dr Hélène MARIE CNRS UMR 7288, IBDM (Marseille), Examinatrice Dr Laurent GIVALOIS, CR CNRS UMR 1198, MMDN (Montpellier), Examinateur Soutenue le : 13 mars 2020 Dr Stéphane MARTIN, DR CNRS UMR 7275, IPMC (Valbonne), Président du jury Dr Hélène MARIE, DR CNRS UMR7275, IPMC (Valbonne), Directrice de thèse
Étude du rôle pathophysiologique des peptides Aη récemment découverts dans le cerveau
Unraveling the physiopathological actions of the newly discovered Aη peptides in the brain
Jury : Président du jury Dr Stéphane MARTIN, DR CNRS UMR 7275, IPMC (Valbonne) Rapporteurs Dr Thierry AMÉDÉE, DR, CNRS UMR 5297-Laboratoire IINS (Bordeaux) Dr Yoon, CHO, MC/HDR, CNRS UMR 5287-Laboratoire INCIA (Bordeaux) Examinateurs Dr Corinne, BEURRIER, CR CNRS UMR 7288, IBDM (Marseille) Dr Laurent GIVALOIS, CR CNRS UMR 1198, MMDN (Montpellier)
Titre : Étude du rôle pathophysiologique des peptides Aη récemment découverts dans le cerveau Résumé : L’implication de la protéine précurseur de l’Amyloïde (APP) est bien établie dans la pathologie Alzheimer, une des maladies neurodégénératives la plus étendue à travers le monde. Ces 30 dernières années de nombreuses études focalisent sur cette pathologie mais le progrès dans la compréhension de son étiologie et les cures possibles restent cependant limitées. Toutes les études concernant la forme familiale et les cibles potentielles, soulignent l’importance d’APP et des fragments issus de son clivage. Déchiffrer le rôle des différents fragments d’APP dans la fonction synaptique et leurs effets comportementaux est crucial dans la compréhension de l’étiologie de cette pathologie. En 2015, Willem et al, ont décrit une nouvelle voie de clivage produisant le peptide Amyloid-η (Aη). Ils ont pu démontrer que le peptide Aη-, dans sa forme la plus longue, produit par le clivage de l’η-secretase et α-secretase, alimente des propriétés bioactives. Appliqué dans l’hippocampe ex vivo, il diminue la potentialisation à long terme (PLT) et in vivo il réduit les ondes calciques. Au-delà de ces observations initiales, ma thèse intitulée « Étude du rôle pathophysiologique des peptides Aη récemment découverts dans le cerveau » focalise sur le rôle d’Aη dans différents paramètres de la plasticité synaptique excitatrice et les comportements associés. Nous avons testé les effets d’une augmentation aigue et chronique d’Aƞ-α, en administrant de l’Aη-α synthétique (M108) de manière aigue sur des tranches d’hippocampe ex vivo et via l’analyse de nouvelles lignées de souris transgéniques MISEPA2 et MISEPA4 sur-exprimant l’Aη-α. Nos résultats montrent l’impact d’Aη-α sur la plasticité synaptique à des concentrations nano-molaires en induisant une dépression à long terme (DLT), tandis que la plasticité présynaptique à court terme et la transmission synaptique basale sont inchangées. Puis, afin d’élucider les effets aigus et chroniques d’un taux élevé d’Aη-α sur la cognition, nous avons mené une série de tests mnésiques. L’analyse des lignées transgéniques révèlent aucun déficit majeur de mémoire, bien que des altérations subtiles soient notables lors d’analyses individuelles. De plus des injections intracérébrales aigues de M108 chez des souris in vivo ne montrent pas de déficit de mémoire. Nous concluons que, bien que la plasticité synaptique excitatrice hippocampique soit clairement impactée par des taux élevés d’Aη-α, aucun phénotype comportemental majeur ne semble apparent. En parallèle, nous avons étudié la plasticité synaptique et le comportement dans un nouveau modèle de souris Knock-out APPΔEta, dans lequel le clivage d’APP par la η-secretase est absent. Dans cette lignée la DLT ne peut pas être induite, mais l’application aigue de M108 rétablit la DLT. Ces données révèlent donc un rôle crucial de l’Aη-α dans ce mécanisme de plasticité synaptique. De plus, les souris APPΔEta montrent un déficit en mémoire spatiale dans le test de la piscine de Morris et une baisse de l’anxiété dans le test d’openfield et les boites claires obscures, indiquant que le clivage d’APP par η-secretase est nécessaire dans les fonctions cognitives. En conclusion, nos résultats contribuent à la compréhension du rôle d’Aη-α dans la physiopathologie, mettant en avant son rôle essentiel dans la plasticité synaptique et la cognition.
Mots clés : APP, amyloid-η, plasticité synaptique, cognition, hippocampe
Title : Unraveling the physiopathological actions of the newly discovered Aη peptides in the brain Abstract : The amyloid precursor protein (APP) is well known by its association with Alzheimer's disease (AD), the most common neurodegenerative disease worldwide. Despite intense research focusing on AD over the last 30 years, the progress in understanding its etiology and finding a cure has been limited. Thus far, all data gathered regarding the genetic causes of familiar AD, the progression of the disease, and potential therapeutic targets for AD, highlight the importance of APP and its cleavage products. Deciphering the role of the different APP fragments in synaptic function and behavior is crucial to understand AD etiology fully. In 2015, Willem et al., described a new APP processing pathway producing amyloid-η (Aη) peptides. They could demonstrate that the Aη-α peptide, the longest form of Aη produced by η-secretase and α-secretase cleavage, harbors bioactive properties. Applied on the hippocampus ex vivo it lowers long-term potentiation (LTP) and in vivo it lowers calcium wave activity. Going beyond these initial observations, my thesis, "Unraveling the physiopathological role of the newly discovered Aη peptides in the brain" focused on further identifying Aƞ-α actions on different parameters of excitatory synaptic plasticity and associated behavioral outputs. We tested the effects of acute and chronic elevations of Aƞ-α, employing acute application of synthetic Aƞ-α (M108) on hippocampal slices ex vivo or via the analysis of new transgenic mouse lines MISEPA2 and MISEPA4 overexpressing Aƞ-α, respectively. Our results show that Aη-α impacts synaptic plasticity at low nanomolar concentrations and shifts plasticity towards long-term depression (LTD), while it does not perturb pre-synaptic short-term plasticity or basal synaptic transmission. Next, to unravel the effects of both acute and chronic elevated Aƞ-α levels on cognition, we performed a series of memory-dependent behavioral tests. Analysis of the transgenic mouse lines indicated no major memory impairments, although subtle alterations were noticeable upon individual testing and analysis paradigms. Also, an acute injection of M108 in the brain in vivo did not correlate with significant memory loss. We conclude that, while hippocampal excitatory synaptic plasticity is clearly impacted by elevated Aη-α levels, this cellular phenotype failed to robustly translate into alterations of behavioral output thus far. In parallel, we went on to investigate the effects on synaptic plasticity and behavior caused by the absence of APP processed by ƞ-secretase in a novel knock-out APPΔEta mice line. In this mouse line LTD could not be induced, but acute M108 application rescued this phenotype. These data reveal a crucial role of Aη-α in this synaptic plasticity mechanism. Additionally, APPΔEta mice exhibited impaired spatial memory in MWM task and reduced anxiety in the Open field and Light-Dark box tests, indicating that this APP cleavage is necessary for cognitive functions. In conclusion, our results advanced the understanding of the physio-pathological role of Aƞ in the brain, highlighting an essential function in excitatory synaptic plasticity and cognition.
Keywords: APP, amyloid-η, synaptic plasticity, cognition, hippocampus
Université Côte d’Azur, École Doctorale 85 Science de la Vie et de la Santé Institut de Pharmacologie Moléculaire et Cellulaire, UMR 7275, CNRS/UCA
Thèse de doctorat
Présentée en vue de l’obtention du titre de Docteur en Sciences de la Vie Spécialité : Interactions Moléculaires et Cellulaires
Soutenue par : Maria MENSCH
Étude du rôle pathophysiologique des peptides Aη récemment découverts dans le cerveau
“Unraveling the physiopathological actions of the newly discovered
Aη peptides in the brain”
Thèse dirigée par le Dr Hélène MARIE
Soutenue à Sophia-Antipolis le 13 mars 2020 Devant le jury composé de :
Dr Yoon, CHO, MC/HDR, CNRS UMR 5287-Laboratoire INCIA (Bordeaux) Rapporteur Dr Thierry AMÉDÉE, DR, CNRS UMR 5297-Laboratoire IINS (Bordeaux) Rapporteur Dr Corinne, BEURRIER, CR CNRS UMR 7288, IBDM (Marseille) Examinateur Dr Laurent GIVALOIS, CR CNRS UMR 1198, MMDN (Montpellier) Examinateur Dr Stéphane MARTIN, DR CNRS UMR 7275, IPMC (Valbonne) Président du jury Dr Hélène MARIE, DR CNRS UMR7275, IPMC (Valbonne) Directrice de thèse
Université Côte d’Azur, École Doctorale 85 Science de la Vie et de la Santé Institut de Pharmacologie Moléculaire et Cellulaire, UMR 7275, CNRS/UCA
Ph.D. Dissertation
Submitted for the degree of Doctor of Philosophy Specialization: Molecular and Cellular Interactions
Presented by: Maria MENSCH
Unraveling the physiopathological actions of the newly discovered Aη peptides in the brain
Thesis supervised by Dr Hélène MARIE Defended in Sophia-Antipolis 13 March 2020
In front of a committee composed of:
Dr Yoon, CHO, MC/HDR, CNRS UMR 5287-Laboratoire INCIA (Bordeaux) Reviewer Dr Thierry AMÉDÉE, DR, CNRS UMR 5297-Laboratoire IINS (Bordeaux) Reviewer Dr Corinne, BEURRIER, CR CNRS UMR 7288, IBDM (Marseille) Examiner Dr Laurent GIVALOIS, CR CNRS UMR 1198, MMDN (Montpellier) Examiner Dr Stéphane MARTIN, DR CNRS UMR 7275, IPMC (Valbonne) President of committee Dr Hélène MARIE, DR CNRS UMR 7275, IPMC (Valbonne) Thesis supervisor
Dedication
To Elfi,
For her support, her advice and her love. She always knew the best is yet to come.
Für Elfi,
Für ihre Unterstützung, ihren Rat und ihre Liebe. Geduld mein Kind, das ist erst der Anfang.
Acknowledgements I want to thank Hélène Marie for allowing me to work as a PHD student in her laboratory. Furthermore, I thank all former and present members of the Marie & Barik team for their support and encouragement. Thank you, Carine Gandin, for your Western blots and open ear. A special thank goes to Ingrid Bethus and Paula Pousinha, who both helped me advancing in their fields and were always willing to answer any question I came up with.
Thank you to Yishan Ma and Jade Dunot, two students I had the pleasure to work with and train during their stay in the Marie & Barik laboratory and whose helping hands were greatly appreciated.
The Labex SIGNALIFE program, I want to thank for the opportunity to do a PhD in Nice. In this sense I especially want to thank Dr. Konstanze Beck, for organizing the great seminars, assistance with bureaucracy and most of all for introducing me to my fellow SIGNALIFE PhDs. Christina, Aiden, Torsten, Renan, Gosia, Meng, and Monse, thank you for all the little adventures outside the lab and long nights throughout the last three years.
A special thanks goes out to my lunch crew: Loïc, who was there from the start and willing to discuss some crazy theories over the years. Katharina, who became a good friend and who always had an open ear and a helping hand. Ligia, who always stays calm in the storm and supportive. Paula and Joanna, who joined the group last but have become a vital part of the group and whose company I wouldn’t want to miss anymore.
A special thank goes out to Marta and Gaurav, for everything. You two helped me in so many ways. I will always remember our early morning rides in the bus, the deep conversations, and your advice.
Danke auch an Angi und Kathi, ihr zwei seit schon so lange ein Teil meiner Reise und ich bin dankbar immer auf euch zählen zu können. Auch wenn wir uns nicht oft sehen, ihr versteht mich und schafft es immer das die Sonne nach einem Gespräch mit euch doch hervorschaut. Eure Freundschaft bedeutet mir viel.
Ich bedanke mich auch bei meiner Familie. Papa, dafür das ich dich zu jeder Tages- und Nachtzeit anrufen kann, du mich unterstützt, mir Ratschläge gibst und mich aber auch meinen eigenen Weg gehen lässt. Martin und Frida, ich bin dankbar euch zwei meine Geschwister nennen zu dürfen. Mit euch aufzuwachsen hat mich zu dem Besserwisser gemacht, der ich heute bin. Eure Zuversicht und unsere Gespräche möchte ich nicht missen. Danke auch an Anette, für deine Ratschläge, Hilfe und Lunchpakete. Ein spezieller Dank geht an Charlotte, du bist mein großes Glück und motivierst mich jeden Tag aufs Neue besser zu sein.
Last but not least, I want to shout out a massive thank you to Tom, my partner in crime, you have always been there by my side, supported me throughout the way, had my back and believed in me. Thank you for listening, discussing, your help with the graphics, staying up with me and knowing when to buy me Chocolate.
Summary The amyloid precursor protein (APP) is well known by its association with Alzheimer's disease (AD), the most common neurodegenerative disease worldwide. Despite intense research focusing on AD over the last 30 years, the progress in understanding its etiology and finding a cure has been limited. Thus far, all data gathered regarding the genetic causes of familiar AD, the progression of the disease, and potential therapeutic targets for AD, highlight the importance of APP and its cleavage products. Deciphering the role of the different APP fragments in synaptic function and behavior is crucial to understand AD etiology fully. In 2015, Willem et al., described a new APP processing pathway producing amyloid-η (Aη) peptides. They could demonstrate that the Aη-α peptide, the longest form of Aη produced by η-secretase and α-secretase cleavage, harbors bioactive properties. Applied on the hippocampus ex vivo it lowers long-term potentiation (LTP) and in vivo it lowers calcium wave activity. Going beyond these initial observations, my thesis, "Unraveling the physiopathological role of the newly discovered Aη peptides in the brain" focused on further identifying Aƞ-α actions on different parameters of excitatory synaptic plasticity and associated behavioral outputs. We tested the effects of acute and chronic elevations of Aƞ-α, employing acute application of synthetic Aƞ-α (M108) on hippocampal slices ex vivo or via the analysis of new transgenic mouse lines MISEPA2 and MISEPA4 overexpressing Aƞ-α, respectively. Our results show that Aη-α impacts synaptic plasticity at low nanomolar concentrations and shifts plasticity towards long-term depression (LTD), while it does not perturb pre-synaptic short-term plasticity or basal synaptic transmission. Next, to unravel the effects of both acute and chronic elevated Aƞ-α levels on cognition, we performed a series of memory-dependent behavioral tests. Analysis of the transgenic mouse lines indicated no major memory impairments, although subtle alterations were noticeable upon individual testing and analysis paradigms. Also, an acute injection of M108 in the brain in vivo did not correlate with significant memory loss. We conclude that, while hippocampal excitatory synaptic plasticity is clearly impacted by elevated Aη-α levels, this cellular phenotype failed to robustly translate into alterations of behavioral output thus far. In parallel, we went on to investigate the effects on synaptic plasticity and behavior caused by the absence of APP processed by ƞ-secretase in a novel knock-out APPΔEta mice line. In this mouse line LTD could not be induced, but acute M108 application restored this phenotype. These data reveal a crucial role of Aη-α in this synaptic plasticity mechanism. Additionally, APPΔEta mice exhibited impaired spatial memory in MWM task and reduced anxiety in the Open field and Light-Dark box tests, indicating that this APP cleavage is necessary for cognitive functions. In conclusion, our results advanced the understanding of the physio-pathological role of Aƞ in the brain, highlighting an essential function in excitatory synaptic plasticity and cognition.
I
II Résume L’implication de la protéine précurseur de l’Amyloïde (APP) est bien établie dans la pathologie Alzheimer, une des maladies neurodégénératives la plus étendue à travers le monde. Ces 30 dernières années de nombreuses études focalisent sur cette pathologie mais le progrès dans la compréhension de son étiologie et les cures possibles restent cependant limitées. Toutes les études concernant la forme familiale et les cibles potentielles, soulignent l’importance d’APP et des fragments issus de son clivage. Déchiffrer le rôle des différents fragments d’APP dans la fonction synaptique et leurs effets comportementaux est crucial dans la compréhension de l’étiologie de cette pathologie. En 2015, Willem et al, ont décrit une nouvelle voie de clivage produisant le peptide Amyloid-η (Aη). Ils ont pu démontrer que le peptide Aη−α, dans sa forme la plus longue, produit par le clivage de l’η-secretase et α-secretase, alimente des propriétés bioactives. Appliqué dans l’hippocampe ex vivo, il diminue la potentialisation à long terme (PLT) et in vivo il réduit les ondes calciques. Au-delà de ces observations initiales, ma thèse intitulée « Étude du rôle pathophysiologique des peptides Aη récemment découverts dans le cerveau » focalise sur le rôle d’Aη dans différents paramètres de la plasticité synaptique excitatrice et les comportements associés. Nous avons testé les effets d’une augmentation aigue et chronique d’Aƞ-α, en administrant de l’Aη-α synthétique (M108) de manière aigue sur des tranches d’hippocampe ex vivo et via l’analyse de nouvelles lignées de souris transgéniques MISEPA2 et MISEPA4 sur-exprimant l’Aη-α. Nos résultats montrent l’impact d’Aη-α sur la plasticité synaptique à des concentrations nano-molaires en induisant une dépression à long terme (DLT), tandis que la plasticité présynaptique à court terme et la transmission synaptique basale sont inchangées. Puis, afin d’élucider les effets aigus et chroniques d’un taux élevé d’Aη-α sur la cognition, nous avons mené une série de tests mnésiques. L’analyse des lignées transgéniques révèlent aucun déficit majeur de mémoire, bien que des altérations subtiles soient notables lors d’analyses individuelles. De plus des injections intracérébrales aigues de M108 chez des souris in vivo ne montrent pas de déficit de mémoire. Nous concluons que, bien que la plasticité synaptique excitatrice hippocampique soit clairement impactée par des taux élevés d’Aη-α, aucun phénotype comportemental majeur ne semble apparent. En parallèle, nous avons étudié la plasticité synaptique et le comportement dans un nouveau modèle de souris Knock-out APPΔEta, dans lequel le clivage d’APP par la η-secretase est absent. Dans cette lignée la DLT ne peut pas être induite, mais l’application aigue de M108 rétablit la DLT. Ces données révèlent donc un rôle crucial de l’Aη-α dans ce mécanisme de plasticité synaptique. De plus, les souris APPΔEta montrent un déficit en mémoire spatiale dans le test de la piscine de Morris et une baisse de l’anxiété dans le test d’openfield et les boites claires obscures, indiquant que le clivage d’APP par η-secretase est nécessaire dans les fonctions cognitives. En conclusion, nos résultats contribuent à la compréhension du rôle d’Aη-α dans la physiopathologie, mettant en avant son rôle essentiel dans la plasticité synaptique et la cognition.
III
IV Table of Contents
Summary ...... I
Index of Figures ...... XI
Index of Tables...... XV
Abbreviations ...... XVII
1. Introduction ...... 3
Alzheimer’s Disease and Amyloid Precursor Protein processing ...... 3 1.1.1 The Amyloid Precursor Protein (APP) ...... 6 1.1.2 Amyloidogenic Pathway ...... 8 1.1.2.1 ß-Secretase ...... 8 1.1.2.2 Amyloid ß ...... 9 1.1.3 Non-Amyloidogenic Pathway ...... 12 1.1.3.1 α -Secretase ...... 12 1.1.3.2 P3 ...... 13 1.1.4 γ-Secretase ...... 13 1.1.5 η-Secretase Pathway ...... 15 1.1.5.1 η -Secretase ...... 16 1.1.5.2 Amyloid η-α and Aη-β ...... 18 1.1.6 Soluble APP ...... 18 1.1.6.1 sAPP-α ...... 19 1.1.6.2 sAPPβ ...... 19 1.1.6.3 sAPP-η ...... 19 1.1.7 Carboxyl-Terminal Fragment ...... 20 1.1.7.1 AICD ...... 20 1.1.8 Other APP Processing Pathways ...... 21
The Hippocampus ...... 23 1.2.1 Anatomy of the Hippocampus ...... 23 1.2.2 Functional Role of the Hippocampus ...... 26 1.2.3 Hippocampus and Memory ...... 27 1.2.3.1 Definition of Memory ...... 27 1.2.3.2 Memory formation ...... 29 1.2.3.3 Working memory ...... 29 1.2.4 Spatial Memory ...... 29 1.2.5 Anxiety ...... 30 1.2.6 An Object to Study in Neurobiology ...... 31
V Methods to Study Physio-Pathological Role of Proteins ...... 33 1.3.1 Electrophysiology ...... 33 1.3.1.1 The Synapse...... 34 1.3.1.1.1 Glutamate ...... 36 1.3.1.1.1.1 mGluRs ...... 37 1.3.1.1.1.2 iGluR ...... 37 1.3.1.1.2 AMPAR ...... 37 1.3.1.1.3 NMDAR...... 41 1.3.1.2 Long-Term Synaptic Plasticity ...... 44 1.3.1.2.1 LTP ...... 45 1.3.1.2.1.1 Mechanism of LTP ...... 45 1.3.1.2.2 LTD ...... 46 1.3.1.2.2.1 Mechanisms of LTD ...... 46 1.3.1.3 Short-Term Synaptic Plasticity...... 47 1.3.1.3.1 Facilitation ...... 47 1.3.1.3.2 Depression ...... 48 1.3.1.4 Synaptic plasticity reflects behavioral outcome ...... 49 1.3.2 Behavioral Studies ...... 51 1.3.2.1 Experimental Design ...... 51 1.3.2.1.1 Husbandry ...... 51 1.3.2.2 Behavior ...... 52 1.3.2.2.1 Spatial Navigation Tasks ...... 52 1.3.2.2.2 Aversive Learning ...... 52 1.3.2.2.3 Recognition Memory ...... 53 1.3.2.2.4 Anxiety ...... 53
2. Objectives ...... 57
3. Material and Methods ...... 61
Animal Model ...... 61 3.1.1 Acute Effects of Aη on Synaptic Plasticity in Electrophysiology Field Recordings ...... 61 3.1.2 Acute Effects of Synthetic Aη-α Injections into the CA1 Hippocampal Region or Lateral Ventricle ...... 61 3.1.3 MISEPA2: A Transgenic Mouse Line Overexpressing Aη-α in the Brain ...... 61 3.1.4 MISEPA4: A Transgenic Mouse Line Overexpressing Aη-α in the Brain with an Elevated Expression Level Compared to MISEPA2 Line ...... 62 3.1.5 APPΔEta: A Mouse Model Without η-Secretase Processing of APP due to Deletion the Enzymatic Recognition Site on APP ...... 62 3.1.1 Immunofluorescence and Western Blot Verify Expression of Aη-α in MISEPA2 Mice and Absence of Aη-α in APPΔEta Mice ...... 64
VI 3.1.2 Housing Conditions ...... 65 3.1.3 Genotyping ...... 65 3.1.3.1 Lysis ...... 65 3.1.4 Polymerase-Chain Reaction Protocol for MISEPA2 and MISEPA4 Mouse Line ...... 66 3.1.5 Polymerase-Chain Reaction Protocol for APPΔEta Mouse Line ...... 67 3.1.6 Gel Electrophoresis ...... 68
Electrophysiology ...... 70 3.2.1 Peptides ...... 70 3.2.2 Solutions ...... 71 3.2.3 Harvesting and Slicing of Mice Hippocampi ...... 72 3.2.4 Rig Set-Up ...... 73 3.2.5 Field Recordings ...... 73 3.2.5.1 Long-Term Synaptic Plasticity Recordings ...... 73 3.2.5.2 Short-Term Synaptic Plasticity Recordings ...... 74 3.2.5.2.1 Paired-Pulse Ratio ...... 74 3.2.5.2.2 Synaptic Fatigue ...... 74 3.2.5.2.3 Input/ Output...... 74
Acute M108 Injection ...... 75 3.3.1 Surgery ...... 75 3.3.2 Injection Volume and Concentration ...... 76 3.3.3 Verification of Injection Site and Distribution of M108 ...... 77 3.3.3.1 Microscopy imaging for injection side in bilateral hippocampal injections...... 77 3.3.3.2 Blue Evans Staining to Verify Correct Placement of Canula Guides and Distribution after Injection ...... 77 3.3.3.2.1 Perfusion Surgery ...... 77 3.3.3.2.2 Perfusion ...... 78 3.3.3.3 Western Blot ...... 79 3.3.3.3.1 Brain Harvesting and Storage ...... 79 3.3.3.3.2 RIPA Extraction Protocol...... 79 3.3.3.3.3 Immunoblotting ...... 80
Behavioral Testing ...... 83 3.4.1 Experimental Design for MISEPA2 and MISEPA4 Lines ...... 83 3.4.2 Experimental Design of M108 Injected Mice Submitted to Behavioral Tasks ...... 84 3.4.3 Experimental Design for APPΔEta Mice ...... 85 3.4.4 Morris Water Maze ...... 85 3.4.5 Novel Object Recognition ...... 87 3.4.6 Contextual Fear Conditioning ...... 88 3.4.6.1 CFC Protocol for the M108 Mice ...... 89 3.4.6.2 CFC Protocol for APPΔEta Mice ...... 90 VII 3.4.7 T-Maze ...... 91 3.4.7.1 Injection of M108 During T-Maze Testing ...... 92 3.4.7.2 Familiar versus New Arm ...... 92 3.4.7.2.1 Alterations of the T-Maze Task for Testing APPΔEta Mice ...... 93 3.4.7.3 Forced Alternation ...... 93 3.4.8 Open Field ...... 94 3.4.9 Light-Dark Box ...... 95 3.4.10 3-Chambers Social Interaction Task ...... 96 3.4.11 Actimeter ...... 97
Statistical Analysis ...... 98 3.5.1 Electrophysiology ...... 98 3.5.2 Behavioral Testing ...... 98
4. Results ...... 99
Consequences of Elevated Aƞ Levels on Synaptic Plasticity and Behavior ...... 103 4.1.1 Effect of Acute Increase of Aη-α Levels on Synaptic Function and Behavior ...... 103 4.1.1.1 Impact of Acutely Elevated Aƞ-α Levels on Synaptic Plasticity ...... 103 4.1.1.1.1 Aƞ-α, the secreted APP fragment processed by ƞ- and α-secretases, acutely modulates post- synaptic plasticity mechanisms shifting the balance towards depression of synaptic strength...... 105 4.1.1.2 Impact of Acute in vivo Injection of M108 into the Brain ...... 125 4.1.1.2.1 Optimization of Protocol for in vivo Delivery of M108 Peptide ...... 125 4.1.1.2.2 Presence of M108 in the Hippocampus Post-Injection Confirmed via Blue Evans Dye and Western Blot ...... 126 4.1.1.2.3 Impact of Acute Injection of M108 into the Hippocampus on CFC ...... 129 4.1.1.2.3.1 Acute Injection of M108 Prior to Conditioning Session in CFC Does Not Impact Memory Formation but Increases Memory Extinction During Secondary Downstream Retrieval ...... 129 4.1.1.2.3.2 Contextual Memory Formation Is Not Impacted by Acute in vivo M108 Injection Irrespective of Time-point of Injection ...... 130 4.1.1.2.4 Effect of Acute Injection of M108 into the Right Lateral Ventricle on Performance in T-Maze ...... 131 4.1.1.2.4.1 Times of Injections Rather Than Delay of Retrieval Leads to Performance Impairment in M108 Injected Mice in a Familiar versus New Arm T-maze Task ...... 131 4.1.1.2.4.2 Performance in M108 Injected Mice Is Not Impaired in a Forced Alternation T-Maze ...... 134 4.1.1.3 Discussion ...... 135 4.1.2 Effect of Chronic Enrichment of Aη-α Levels on Synaptic Function and Behavior ...... 139 4.1.2.1 Impact of Chronically Elevated Aƞ-α Levels in a MISEPA2 Mouse Line on Synaptic Plasticity and Behavior ...... 139
VIII 4.1.2.1.1 Influence of Chronically Elevated Aƞ-α Levels in a MISEPA2 Mouse Line on Synaptic Plasticity .... 139 4.1.2.1.1.1 Impaired LTP in MISEPA2 Mice ...... 139 4.1.2.1.1.2 Short-Term Synaptic Plasticity and Basal Transmission Unaltered in MISEPA2 Mice ...... 140 4.1.2.1.2 Influence of Chronically Elevated Aη-α Levels in a MISEPA2 Mouse Line on Behavior ...... 143 4.1.2.1.2.1 No Impairment of Performance in a Spatial Memory Dependent MWM Task for MISEPA2 Mice ...... 143 4.1.2.1.2.2 Indication of External Factors Influencing Contextual Memory of MISEPA2 MICE in CFC ...... 144 4.1.2.1.2.3 Unaltered Diurnal Activity in MISEPA2 Mice ...... 145 4.1.2.2 Impact of Chronically Elevated Aƞ-α Levels in a MISEPA4 Mouse Line on Synaptic Plasticity and Behavior ...... 147 4.1.2.2.1 Synaptic Plasticity in MISEPA4 Mouse Line ...... 147 4.1.2.2.1.1 LTP is Normal in MISEPA4 Mice ...... 147 4.1.2.2.1.2 Impaired Basal Transmission in MISEPA4 Mice but No Alterations in Short-Term Synaptic Plasticity ...... 148 4.1.2.2.2 Impact of Chronically Elevated Aη-α Levels in a MISEPA4 Mouse Line on Behavior ...... 149 4.1.2.2.2.1 No Effect on Recognition Memory in NOR for MISEPA4 Mice ...... 149 4.1.2.2.2.2 No Impairment of Performance in a Spatial Memory Dependent MWM Task for MISEPA4 Mice ...... 149 4.1.2.2.2.3 Insufficient CFC Task Set-Up to Examine an Effect on Contextual Learning for MISEPA4 Mice ...... 150 4.1.2.2.2.4 Normal Diurnal Activity in MISEPA4 Mice ...... 151 4.1.2.3 Discussion ...... 153
Consequences of Inhibition of the APP Processing η-Secretase Pathway on Synaptic Plasticity and Behavior ...... 159 4.2.1 Impact of Deficiency in η-Secretase Processed APP in an APPΔEta Mouse Line on Synaptic Plasticity ...... 159 4.2.1.1 No Alterations of LTP in APPΔEta Mice ...... 159 4.2.1.2 Deficiency in ƞ-Secretase Processed APP Prevents LTD, a Phenotype Rescued by Acute Application of M108 ...... 160 4.2.1.3 Short-Term Synaptic Plasticity and Basal Transmission are Normal APPΔEta Mice ...... 161 4.2.2 Impact of Loss of η-Secretase-dependent Cleavage of APP on Behavior ...... 163 4.2.2.1 Indication of Reduced Anxiety for HOMO in Open Field ...... 163 4.2.2.2 Indication of Reduced Anxiety for APPΔEta Mice in the Light-Dark Box ...... 164 4.2.2.3 Regular Social Interaction Observed for APPΔEta Mice in the 3-Chambers Social Interaction Task ..... 164 4.2.2.4 Impaired Spatial Memory in HOMO in T-Maze Task ...... 165 4.2.2.5 APPΔEta Mice Display Loss of Spatial Memory in the MWM...... 167 4.2.2.6 APPΔEta Mice Display Normal Contextual Fear Memory ...... 168
IX 4.2.2.7 Diurnal Activity is Altered in HOMO Mice (Preliminary Data) ...... 169 4.2.3 Discussion ...... 171
5. General Discussion and Perspectives ...... 177
Synaptic Plasticity, Under Acute and Chronic elevated Aη-α Conditions ...... 177
Behavioral Studies, Under Acute and Chronic elevated Aη-α Conditions ...... 178
Comparing the Acute and Chronic elevated Aη-α Conditions ...... 180
Depletion of Aη-α levels ...... 181
APPΔEta and Alternatives: A Comparison ...... 182
Comparing the Outcomes of Aη-α Level Modification ...... 183
Probing the η-Secretase Pathway: Prospective Approaches ...... 184
6. Conclusion ...... 189
Bibliography ...... XXI
Supplementary ...... XLVIII
X Index of Figures
Figure 1 Illustration of the three main APP processing pathways discussed in this Thesis...... 5 Figure 2 Illustration of APP cleavage site of η-secretase...... 16 Figure 3 Cross section through the hippocampus...... 23 Figure 4 Hippocampal Circuitry...... 25 Figure 5 Basic anatomy of the hippocampus...... 26 Figure 6 The two different pathways of information processing in the hippocampus...... 26 Figure 7 Different forms of memory, their subcategories and the brain structures associated with them...... 27 Figure 8 The tripartite synapse...... 34 Figure 9 Excitatory glutamatergic synapse...... 36 Figure 10 Composition of subunits of the iGluR...... 37 Figure 11 Depending on AMPAR composition and post-translational modifications they are added or removed from the post-synaptic density during LTD and LTP...... 38 Figure 12 Schematic of AMPAR structure...... 39 Figure 13 Schematic NMDAR structure and the different binding sites for ligands...... 42 Figure 14 NMDAR subunit diversity and expression pattern throughout development...... 43 Figure 15 The two main forms of long-term plasticity LTD and LTP...... 45 Figure 16 Schematic illustration of facilitation...... 48 Figure 17 Schematic illustration of depression...... 48 Figure 18 Representation of the pSec.2A plasmid expressing Aη-α...... 62 Figure 19 APPΔEta mice harbor the endogenous APP protein with deletion of ƞ-secretase recognition site...... 63 Figure 20 Immunofluorescence images confirming expression of Aƞ-α in different brain regions...... 64 Figure 21 Western blots confirming absence of endogenous Aƞ-α in APPΔEta mice and presence of recombinant human Aƞ-α in MISEPA2 mice...... 65 Figure 22 Gel showing the bands to be expected by the MISEP PCR samples...... 69 Figure 23 Band options for the APPΔEta PCR samples...... 69 Figure 24 Field recordings at the hippocampal CA3-CA1synapse were performed to investigate alterations in synaptic plasticity in our experiments...... 70 Figure 25 The two different types, single and bilateral, cannula guides used for injections of M108...... 76 Figure 26 Schematic illustration of perfusion surgery...... 78
XI Figure 27 Timeline of the MISEPA2 behavioral battery testing...... 84 Figure 28 Timeline of MISEPA4 behavioral battery testing...... 84 Figure 29 Timeline of M108 behavioral testing...... 84 Figure 30 Timeline of APPΔEta behavioral battery testing...... 85 Figure 31 Timeline of the Morris Water Maze experiment...... 86 Figure 32 The three stages of Novel Object Recognition...... 88 Figure 33 Contextual Fear Conditioning consisting of two stages...... 89 Figure 34 Contextual Fear Conditioning protocol for M108...... 90 Figure 35 Contextual Fear Conditioning protocol for the APPΔEta line...... 91 Figure 36 T-maze set-up...... 92 Figure 37 Illustration of the Familiar vs. New arm protocol...... 93 Figure 38 The Forced Alternation protocol for M108 injected mice...... 94 Figure 39 The Open field recorded movement of the mouse for 10 min...... 95 Figure 40 The Light-Dark box...... 95 Figure 41 3-Chamber social interaction task...... 97 Figure 42 Removal of dummies during recovery phase after surgery induces necrosis in brain tissue...... 126 Figure 43 Injection of blue Evans dye distributes throughout all ventricles...... 126 Figure 44 Presence of M108 in the hippocampi post-injection into the CA1 region is confirmed via Western blot...... 127 Figure 45 Distribution and presence of M108 post-injection into the right lateral ventricle was confirmed via Western blot...... 128 Figure 46 A single acute M108 injection prior to the conditioning session does not perturb memory formation but significantly increases memory extinction...... 130 Figure 47 Moving the time point of M108 injection to post- conditioning session does not prevent memory formation independent of time-point of Retrieval...... 130 Figure 48 A 10 min ITI showed no alterations of performance in Retrieval, after acute injection of M108 during the first phase of T-maze...... 132 Figure 49 A 1-hour ITI T-maze protocol showed a significantly reduced ability in M108 injected mice to identify the new arm...... 133 Figure 50 A single 1 h ITI T-maze task, with premier injection of M108, shows no performance impairments...... 134 Figure 51 Forced alternation with 4 trials showing no significant difference between groups, but disability of M108 injected mice to perform above Chance level (50 %)...... 134
XII Figure 52 LTP is impaired for MISEPA2 mice at the SC-CA1 synapse of hippocampal slices...... 140 Figure 53 No short-term plasticity deficits observable in hippocampal slices of MISEPA2. 141 Figure 54 transgenic MISEPA2 mouse line displays normal function of spatial learning and memory in MWM...... 143 Figure 55 Reduced contextual fear memory in transgenic mice line MISEPA2...... 144 Figure 56 Contextual fear memory increases in MISEPA2 when analyzed automatically. .. 145 Figure 57 MISEPA2 mice show normal circadian activity...... 146 Figure 58 Normal LTP in MISEPA2 mice at the SC-CA1 synapse of hippocampal slices. . 147 Figure 59 No deficits in short-term plasticity dependent PPR observable, but a significant decrease in basal synaptic transmission in hippocampal slices of MISEPA4...... 148 Figure 60 MISEPA4 mice show significant exploration time towards novel objects but fails to reach DI criterion...... 149 Figure 61 MWM testing showed no sign of spatial memory impairment in MISEPA4 mice...... 150 Figure 62 A single low intensity shock proved too mild to test for contextual memory...... 151 Figure 63 MISEPA4 mice show normal diurnal activity...... 151 Figure 64 Normal LTP in HOMO mice at the SC-CA1 synapse of hippocampal slices...... 160 Figure 65 Addition of M108 rescues LTD in HOMO at the SC-CA1 synapse of hippocampal slices...... 161 Figure 66 No pre-synaptic short-term plasticity deficits were observable in APPΔEta mice...... 162 Figure 67 HOMO APPΔEta mice show reduced anxiety in the Open field...... 163 Figure 68 Light-Dark box test hints toward reduced anxiety in HOMO...... 164 Figure 69 APPΔEta mice show no impairment in sociability in the 3-chambers social interaction test paradigm...... 165 Figure 70 A 10 min ITI familiar vs new arm T-maze test indicates a quick wear off for novelty in HOMO...... 166 Figure 71 HOMO display impairments in the 1 h ITI T-maze task...... 166 Figure 72 HOMO show impairment in retrieval of platform location during Probe in the MWM test. 167 Figure 73 A two-day CFC experiment followed by an extinction paradigm revealed no impairments in contextual memory or memory extinction in HOMO...... 168 Figure 74 Diurnal activity is altered in APPΔEta mice...... 169 Figure 75 Illustrating Aη-α as a neuromodulator crucial for LTD...... 183
XIII
XIV Index of Tables Table 1 Deletion of 41 amino acids (blue) containing the ƞ-secretase recognition site (orange) on APP...... 63 Table 2 Comparing MISEPA2 and MISEPA4 and their respective Aη-α expression levels in different brain areas...... 64 Table 3 content of the MISEP PCR master mix...... 67 Table 4 Primer sequence of Myosin and MISEP used in the PCR master mix ...... 67 Table 5 content of the APPΔEta PCR master mix ...... 68 Table 6 Sequences of Primers used in APPΔEta PCR master mix ...... 68 Table 7 Amino acid sequence of synthetic proteins ordered...... 70 Table 8 Ingredient list of the cutting solution with their respective concentration ...... 71 Table 9 aCSFI solutions ingredient list with their respective concentration ...... 71 Table 10 aCSFII solutions ingredients list with their concentration...... 72 Table 11 Time points to sacrifice mice post-injection of M108...... 79 Table 12 composition of RIPA buffer ...... 80 Table 13 Loading buffer composition ...... 81 Table 14 Blocking solution composition ...... 81 Table 15 Separation Gel and Spacer gel recipe ...... 81
XV
XVI Abbreviations
A C
Aβ Amyloid β protein C83 see CTF-α
Aβ17-42 p3 C99 see CTF-β Aη-α Amyloid η-α protein CA Cornu Ammonis Aη-β Amyloid η-β protein CAMKII Calcium/calmodulin- ABD agonist-binding domain dependent protein kinase II aCSF artificial cerebrospinal fluid CFC contextual fear conditioning AD Alzheimer’s disease CHO-cells Chinese hamster ovary cells ADAM disintegrin and CNO clozapine-N-oxide metalloproteinase CP-AMPAR Ca2+ permeable AMPAR ADAM10 disintegrin and CSF cerebrospinal fluid metalloproteinase 10, CTF carboxy-terminal fragment α-secretase CTF-α C-terminal APP α fragment AMPAR α-amino-3-hydroxy-5- CTF-β C-terminal APP β fragment methyl-4-isoxazole- CTF-η C-terminal APP η fragment propionate receptor ANOVA analysis of variance D AP anteroposterior APP Amyloid precursor protein DI discrimination index APPLP1 Amyloid precursor like DMSO dimethyl sulfoxide protein 1 dNTP deoxynucleotide mix DREADD designer receptors APPLP2 Amyloid precursor like exclusively activated by protein 2 designer drugs ASP2 aspartyl protease 2 DTT Dithiothreitol
B DV dorsoventral Dzb decibel
BACE1 beta-site amyloid precursor protein cleaving enzyme 1, β-secretase bp base pair XVII E HOMO homozygote HRP horseradish peroxidase E east Hz Hertz EDTA Ethylenediaminetetraacetic acid I EPSP excitatory post-synaptic potential Ig Immunoglobulin iGluR ionotropic glutamate F receptor I/O input/output fAD familiar or early-onset AD i.p. intraperitoneal ISI inter stimulus interval fEPSP field excitatory post synaptic ITI inter trial interval potential K FV fiber volley
G K kappa kb kilo base
GABA γ-aminobutyric acid kDa kilo Dalton GABABR1 γ-aminobutyric acid type B kg kilogram receptor subunit L GluA AMPAR subunit GluA2L long-tailed GluA2 LTD long-term depression GluA4s short-tailed GluA4 LTP long-term potentiation GluN NMDAR subunit LxWxH length x width x height GLUT plasma membrane glucose lux luminous flux per unit transporter g gram M
H M2 re-entrant pore loop M92 synthetic Amyloid η-α HEPES 4-(2-hydroxyethyl)-1- protein piperazineethanesulfonic M108 synthetic Amyloid η-β acid protein HET heterozygote mA milliampere
XVIII memapsin-2 membrane-associated pH potential of hydrogen PPR paired-pulse ratio aspartic protease 2 PS1 presenilin 1 mg milligram PS2 presenilin 2 mGluR metabotropic glutamate PSD post-synaptic density receptor PSD-95 a neuron-specific PSD ML mediolateral protein mM millimolar MMP metalloproteinase R MT5-MMP membrane-type 5 metalloproteinase, RM repeated measured η-secretase rtTA reverse tetracycline mV millivolt transactivator MWM Morris water maze µgr microgram S µl microliter
S south N sAD sporadic or late-onset AD sAPP-α soluble APP α fragment N north sAPP-β soluble APP β fragment nM nanomolar sAPP-η soluble APP η fragment NMDAR N-methyl-D-aspartate SDS-PAGE sodium dodecyl sulfate- receptor polyacrylamide gel ng nanogram S.E.M. standard error of mean NOR novel object recognition T NTD amino-terminal domain NTF amino-terminal fragment TARP transmembrane AMPAR
P regulatory protein TBST Tris buffered saline with
P postnatal day Tween 20 PB phosphate buffer TCA tricarboxylic acid cycle PBS phosphate buffered saline TM transmembrane PCR polymerase chain reaction tTA tetracycline transactivator PFA formaldehyde
XIX V
V volt
W
W west WT wild type
XX XXI
1. Introduction
1
2 1. Introduction
Alzheimer’s Disease and Amyloid Precursor Protein processing
Alzheimer's Disease (AD) is a neurodegenerative disease familiar by name to a wide audience, scientists and lay-people alike. It was first described in 1906 at the 37th meeting of the Southwest German Psychiatrists in Tübingen by Alois Alzheimer (Alzheimer, 1906). He described symptoms of dementia in his patient Auguste Deter and the post-mortem discovery of insoluble extra- and intracellular proteinaceous deposits in her brain. However, AD received only minor attention post-discovery until 1976 when Robert Katzman made the connection between AD and "senile dementia" identifying the disease and its progression as the leading cause of death in the USA (Katzman, 1976). AD is a neurodegenerative disease mainly affecting the older population, as age is one of the main risk factors. It is a progressive disease starting on the cognitive level with a decline in episodic memory, spreading to affect short-term memory, and finally, affecting procedural memory. The disease is defined by selective neuronal loss and atrophy at some medial temporal lobe structures, which makes it distinct from other dementia (Puzzo, Lee, Palmeri, Calabrese, and Arancio, 2014). The different types of memory and the role the hippocampus plays in its formation are described in more detail in the hippocampus section of the introduction. Since 1976 research focused its investigation on identifying the cause of AD. On the cellular level, we have the two hallmarks of AD, a) the amyloidogenic plaques and b) neurofibrillary tangles, an aggregation of hyperphosphorylated cytosolic tau. In 1985 Masters and colleagues revealed amyloid β (Aβ), a protein discovered the previous year by Glenner and Wong, as the major component of the extracellular plaques described by Alzheimer (Glenner and Wong, 1984; Masters et al., 1985). The subsequent identification of the amyloid precursor protein (APP) as the Aβ producing protein and the linkage of mutations promoting Aβ production and familiar AD, led to the formulation of the amyloid cascade hypothesis (Goate et al., 1991; J. Hardy and Higgins, 1992; John Hardy and Allsop, 1991; Kang et al., 1987; Tanzi et al., 1987). These discoveries directed research efforts to focus on the pathological processing of APP. As research progressed, several other factors contributing to AD have been discovered. Mutations on Presenilin, a protein involved in APP processing have also been linked to AD and we know about several risk-factor genes such as harboring the gene encoding the Apolipoprotein E (APOE) isoform APOE4, a protein involved in lipid metabolism and transportation (Naj and
3 Schellenberg, 2017; Sherrington et al., 1995; Van Cauwenberghe, Van Broeckhoven, and Sleegers, 2016). Today, we have about twelve theories for AD genesis developing and adapting throughout the years trying to explain the cause and associated processes in AD. These theories cover a vast range of fields, ranging from the vascular hypothesis, to the traumatic brain injury hypothesis, to the amyloid hypothesis, the most widely accepted theory. Despite significant efforts in the preceding decades to this date Alzheimer's disease remains incurable. At the moment there exist 5 FDA approved drugs which help minimize the symptoms in AD. These drugs also cause severe side effects. They can be divided into two groups: four of them target the cholinergic system, while Memantine, the fifth drug, acts as an N-methyl-D- aspartate receptor (NMDAR) antagonist. As mentioned before, the plaques first described by Alois Alzheimer in 1906 consist mainly of Aß, a protein resulting from APP processing via the amyloidogenic pathway (Alzheimer, 1906) (see Figure 1). Thus, the main attention of research was focused on this pathway in pathological conditions, the enzymes involved, and the cleavage products. It is therefore not surprising that the physiological role of APP and the amyloidogenic pathway remain elusive. Due to the focus on amyloidogenic processing of APP, knowledge about the non-amyloidogenic pathway, the η -secretase pathway and their products is even more limited.
4
Figure 1 Illustration of the three main APP processing pathways discussed in this Thesis. In the middle is the full-length APP, which can be processed by α-, ß- or η -secretase initiating three different pathways. On the left are the well-known non- amyloidogenic pathway and amyloidogenic pathway. The non-amyloidogenic pathway on the top is initiated by cleavage of APP through α-secretase creating sAPP-α and CTF-α. The latter can be further processed by γ-secretase releasing p3 and AICD. The amyloidogenic pathway shown below, is driven by cleavage of APP by ß-secretase, producing sAPP-ß and CTF-ß. CTF-ß is further cleaved by γ-secretase producing Aß and AICD. Shown on the right is the η -secretase pathway. In this pathway APP cleavage by η -secretase produces sAPP-η and CTF-η. CTF-η is then further processed by either α-secretase generating Aη-α or by ß-secretase producing Aη-ß. Adapted from (Ludewig and Korte, 2017).
Lately, the scope of research on APP also opened up towards new processing pathways and identifying secretases involved in these pathways. The η-secretase pathway is an example of these efforts to shed more light on APP processing. This pathway was discovered and first described in 2015 by two independent teams (Haizhi Wang et al., 2015; Willem et al., 2015). In their work, the teams identified η-secretase as an enzyme able to cleave APP leading to the discovery of a novel secretion pathway. Two of the products of this pathway, Aη-α and Aη-ß, and their physiopathological role, have been the focus of this thesis. We aimed to investigate the physiopathological role of these newly discovered Aeta peptides including studies focusing on their ability to alter synaptic plasticity as well as behavior. The following chapter will introduce the main pathways known in APP processing and describe the different proteins involved in these pathways.
5 1.1.1 The Amyloid Precursor Protein (APP)
The APP, together with the amyloid precursor protein-like protein (APPLP) 1 and APPLP2, constitute a highly conserved protein family (Bhadbhade and Cheng, 2012). Various knock-out models of each of the proteins and combinations have shown that they can replace each other to a certain degree. The knock-out of APPLP2, for example, does not alter the phenotype of mice, indicating that APP and APPLP1 together can replace it. However, the knock-out of APP, APPLP1, and APP/APPLP1 leads to physiological changes in mice, reducing their body weight, grip strength, locomotor activity, and increases age-associated memory deficits. The triple knock-out APP/APPLP1/APPLP2 and double knock-outs APP/APPLP2 and APPLP1/APPLP2 are lethal, demonstrating the importance of this family of proteins and the limits of in vivo substitution of the functions of individual proteins by other family members (Heber et al., 2000; Z. W. Li et al., 1996; Müller et al., 1994; Senechal, Kelly, and Dev, 2008; The Human Protein Atlas, 2018; Von Koch et al., 1997; H. Zheng et al., 1995). While the expression of APPLP1 is limited to the brain, APP and APPLP2 are expressed ubiquitously. These proteins are type 1 transmembrane proteins resembling cell-surface receptors. Their extracellular domain at the N-terminal represents nearly 90 % of the total protein mass. The C-terminal, on the other hand, consists of a 47 amino acid short cytoplasmic domain connected to the N-terminal via a single membrane-spanning domain (Bhadbhade and Cheng, 2012). It is at the C-domain where the family members have the highest sequence similarity, with motifs involved in different functions of the proteins (Gralle and Ferreira, 2007; H. Zheng and Koo, 2011). For example, some of the implied functions of these proteins are cell-cell adhesion and migration, synaptogenesis, and synaptic plasticity, indicating the importance of these proteins in brain development and maturation (Gralle and Ferreira, 2007; Kedikian et al., 2010; Korte, Herrmann, Zhang, and Draguhn, 2011; Nalivaeva and Turner, 2013; Octave, Pierrot, Ferao Santos, Nalivaeva, and Turner, 2013; Shariati and De Strooper, 2013; Soba et al., 2005; Sosa et al., 2017; Zhang, Thompson, Zhang, and Xu, 2011; H. Zheng and Koo, 2011). As APP is the only family member containing the Aβ domain, thus considered highly crucial in AD, it has been by far the most studied member of the family (J. Hardy and Higgins, 1992; John Hardy, 2017; John Hardy and Allsop, 1991; Raphaëlle Pardossi-Piquard et al., 2005). Several studies suggest an essential role for APP in synaptogenesis, spine formation, regulation of intracellular calcium homeostasis, signaling, and in synaptic vesicle and transmitter release. Resembling a receptor, as mentioned above, several binding proteins have been being proposed, among them Aβ (Bignante, Heredia, Morfini, and Lorenzo, 2013; Lorenzo et al., 2000).
6 However, to this date, knowledge about the physiological role of APP is poorly understood due to the complex splicing, proteolysis, co-localization, and similarity to its other family members and proteins generated by APP processing (Gralle and Ferreira, 2007; Kedikian et al., 2010; Korte et al., 2011; Nalivaeva and Turner, 2013; Octave et al., 2013; Shariati and De Strooper, 2013; Soba et al., 2005; Sosa et al., 2017; Zhang et al., 2011; H. Zheng and Koo, 2011).
APP has eight isoforms, among which the following three are the most common ones: APP695,
APP752, and APP770 derived by alternative splicing of exon 7 and exon 8 on chromosome 21 (Cappai, 2014; J. C. Phillips, 2019; Rupert Sandbrink, Masters, and Beyreuther, 1994). Out of the three isoforms APP695 is the main isoform in the brain and mainly expressed in neurons, while the other two forms primarily express in glial cells like astrocytes (Belyaev et al., 2010; Bhadbhade and Cheng, 2012; De Silva et al., 1997; Matsui et al., 2007; Nalivaeva and Turner, 2013; Puig and Combs, 2013; R. Sandbrink, Masters, and Beyreuther, 1996; Simons et al., 1996; Tanaka et al., 1988). Interestingly, this distribution seems altered in AD as an increase in
APP770 mRNA correlating with a decrease of APP695 mRNA can be observed (Cappai, 2014). The location on chromosome 21 first described in 1987 correlates with increased cases of AD for people with trisomy 21, which have a third copy of this chromosome. Additionally, point mutations in the APP gene correspond with familiar AD (fAD), the rarer form of AD comprising about 1-5 % of all AD cases (J. Hardy and Higgins, 1992; John Hardy and Allsop, 1991; Petronis, 1999; Selkoe and Hardy, 2016; St. George-Hyslop et al., 1987). Synthesis and processing of APP is a highly regulated process starting in the endoplasmic reticulum. The synthesized APP continues its journey through the Golgi apparatus to finally reach the cell membrane via the constitutive secretion pathway. Throughout this process, APP undergoes post-translational modifications such as O- and N-glycosylation, ubiquitination, phosphorylation, and tyrosine sulfation. About 10 % of the produced APP reaches the plasma membrane mainly at the axons and dendrites via anterograde transportation, while the majority is stored in the Golgi apparatus in a ready state (Kaether, Skehel, and Dotti, 2000; Kins, Lauther, Szodorai, and Beyreuther, 2006; Plácido et al., 2014). Once at the plasma membrane APP can undergo either endocytosis or is proteolytically processed following down one of the different pathways explained more in detail later: a) non-amyloidogenic, b) amyloidogenic, or c) η- secretase pathway (see Figure 1). If undergoing endocytosis, this process happens due to an internalization motif near the C- terminal and the APP protein goes then either to endosomes, with parts of it recycled to the cell surface, and Golgi apparatus or is degraded in lysosomes (Bhadbhade and Cheng, 2012; De Strooper and Annaert, 2000; Gouras, Willén, and Faideau, 2014; Haass, Kaether, Thinakaran,
7 and Sisodia, 2012; Haass, Koo, Mellon, Hung, and Selkoe, 1992; Koo et al., 1990; Lorenzen et al., 2010; Marquez-Sterling, Lo, Sisodia, and Koo, 1997; Schmidt, Subkhangulova, and Willnow, 2017). When the APP does not undergo endocytosis, it is proteolytically processed, following either one of the pathways further discussed below. Different studies have shown that these pathways stand in direct competition with each other, thus blocking one, strengthens the others. Also, colocalization of APP with secretases like disintegrin and metalloproteinase 10 (ADAM10) or beta-site amyloid precursor protein cleaving enzyme (BACE1) in the vesicles predetermines the following proteolysis pathway of APP (Das et al., 2015; Haass et al., 2012; Szodorai et al., 2009). However, it seems that external factors can influence APP processing too. For example, a study indicates that cholesterol depletion prevents the processing of APP through the amyloidogenic pathway (Kerridge, Belyaev, Nalivaeva, and Turner, 2014).
1.1.2 Amyloidogenic Pathway
As mentioned above, the amyloidogenic pathway gained the greatest attention among all pathways involved in APP processing due to its association to AD. As shown in Figure 1, the pathway is mediated by ß-secretase, which splices the APP protein at its recognition site and leads to the secretion of a soluble APP ß fragment (sAPP-ß) and the membrane-anchored APP ß carboxyl-terminal fragment (CTF-ß), also known as C99. The C99 can then be further cleaved by the γ-secretase complex, which is also involved in the non-amyloidogenic pathway, leading to the secretion of Aß and an APP intracellular domain (AICD) (Haass et al., 2012; Turner, O’Connor, Tate, and Abraham, 2003). Each of these products, sAPP-ß, C99, Aß, and AICD, serve different roles, some of them having the ability to alter synaptic plasticity, gene expression, or even the production of APP itself (see below).
1.1.2.1 ß-Secretase The ß-secretase is the enzyme initiating the amyloidogenic pathway of APP processing. Several proteins can fulfill the role of ß-secretase, but in 1999 the BACE1 also known as membrane- associated aspartic protease 2 (memapsin-2) or aspartyl protease 2 (ASP2) was identified to act as the main secretase (Vassar et al., 1999, 2014; H. Zheng and Koo, 2011). The highest concentration of BACE1 mRNA is in the cortex, while the CA1-CA3 hippocampal region also harbors high concentrations of BACE1. Looking at the neuronal level, the majority of BACE1 concentrations in a healthy state are in pre-synaptic neuronal terminals. However,
8 after stress and inflammatory conditions, and with aging BACE1 is also found in astrocytes. This accumulation in astrocytes is also encountered in AD brains of humans and animal models, with an overall increase of BACE1 levels of 50 % compared to healthy state (Cai et al., 2001; Hartlage-Rübsamen et al., 2003; Kamenetz et al., 2003; Roßner et al., 2005; Tamagno, Guglielmotto, Monteleone, and Tabaton, 2012; Hui Wang et al., 2010; Hui Wang, Megill, Wong, Kirkwood, and Lee, 2014). BACE1 is a type 1 transmembrane protease consisting of 501 amino acids with two active site motifs, which are necessary for its correct function. The maturation of BACE1 occurs in the Golgi apparatus via the removal of a short pro-domain. To increase stability, BACE1 can undergo post-translational modifications like phosphorylation or N-glycosylation before it is transported to its final destination via secretory vesicles. The activity of BACE1 is pH- dependent, reaching the maximum activity under acidic conditions. Therefore, BACE1 mainly resides in subcellular compartments like endosomes and lysosomes. As it follows a similar trafficking route to APP, it can be co-localized in neuronal endosomes and cleaves APP there, giving rise to sAPP-ß and C99 (Cole and Vassar, 2008; Das et al., 2013; Huse et al., 2002; Vassar, 2001; Vassar et al., 2014). Interestingly, the co-localization of ß-secretase and APP depends on both of them internalizing separately and meeting at the early endosomes, producing about 60-70 % of total Aß in this intracellular compartment. The trafficking to the plasma membrane is highly regulated, and production of ß-secretase depends on neuronal activity (Das et al., 2013; Niederst, Reyna, and Goldstein, 2015; Prabhu et al., 2012; Sannerud et al., 2011; Schneider et al., 2008). It is important to note, that while the ß-secretase is the initiating enzyme for the amyloidogenic pathway, it also can cleave other proteins, such as neuregulin 1 and sialyl-transferase ST6Gal I, and fulfills a physiological role. It seems that BACE1 is essential for myelination of peripheral nerves, as indicated by hypomyelination and aberrant axonal segregation in knock- out models (Kitazume et al., 2001; Willem et al., 2006). Furthermore, several studies focusing on blocking BACE1 action on APP or lowering global levels as a therapeutic measurement to prevent AD progression have had disappointing results, and none has surpassed phase III trials so far (Karran, Mercken, and Strooper, 2011; Panza, Lozupone, Logroscino, and Imbimbo, 2019; Vassar et al., 2014).
1.1.2.2 Amyloid ß The Aß is a protein created by cleavage of the C99 fragment at APP 672D by γ-secretase, which is one of the cleavage products of APP processing via ß-secretase as mentioned above. Due to the dependency of Aß cleavage on these two secretases, the main production happens in the
9 early endosomes. It can vary in length from 39-42 amino acids, with the two main forms being
Aß40 and Aß42. The Aß monomers are about 4 kilo Dalton (kDa) and described to have neurotrophic and neuroprotective properties, involved in neural progenitor cell proliferation and synaptic transmission (Abramov et al., 2009; Chasseigneaux and Allinquant, 2012; Giuffrida et al., 2010; J. C. Phillips, 2019; Puzzo et al., 2008, 2011; Rivera, García-González, Khrestchatisky, and Baranger, 2019). Thus, the endogenous Aß can enhance release probability at synapses, with excitatory synapses being the most sensitive to changes in endogenous Aß levels (Abramov et al., 2009). The production and release of Aß correlate positively with neuronal and synaptic activity. Interestingly, sleep deprivation also seems to enhance Aß levels, with the time spent asleep being the critical factor rather than dark/light exposure (Kang et al., 2009). This protein exists not only in monomers but can aggregate, forming dimers, trimers, oligomers, fibrils, and eventually form plaques, one of the hallmarks of AD (Alzheimer, 1906; Rivera et al., 2019; Stelzmann, Norman Schnitzlein, and Reed Murtagh, 1995). Notably, while plaques are an indicator, they are neither the cause nor needed for AD, and may also found in healthy brains post-mortem. Indeed, recent studies identify that Aß dimers and trimers as likely to represent the more toxic forms of this peptide (Herrup, 2015; Lesné et al., 2013).
In a healthy brain, Aß40 is the more common form, whereas, in AD brains, the ratio shifts towards Aß42, the form more prone to aggregate (Rivera et al., 2019). The aggregation of fibrils to form plaques depends on their hydrophobic side chains. Fibrils possess residues that form a double-horseshoe-like cross-beta-2 sheet burying these hydrophobic chains. Numerous mutations of familiar AD are adjacent to the Aß N-terminals and influence the side chains' ability to cover the hydrophobic side chains and increase the aggregation abilities of Aß (J. C. Phillips, 2019). The importance of Aß in AD was first described in 1984 by Glenner, whom earlier that year isolated Aß from meningeal vessels of AD cases and later could link the protein to a trisomy 21 case. People with trisomy 21 nearly always develop AD, as the additional chromosome 21 copy enhances the Aß burden (Glenner and Wong, 1984). The amyloidogenic plaque composition and undeniable connection between Aß and AD led to the formulation of the amyloid cascade hypothesis (J. Hardy and Higgins, 1992; John Hardy and Allsop, 1991). This hypothesis declared the plaques responsible for the cognitive decline observed in AD patients, initiating an ongoing effort to unravel Aß's role as an originator of the disease.
10 Although fAD, where genetic mutations increase Aß levels and cause an early onset of the disease, comprises only about 5 % of all AD cases, they show a high phenotypic similarity with sporadic or late-onset AD (sAD), which affects the aging population. These similarities suggest that the mechanism involved in fAD applies to sAD paving the foundation of transgenic mouse models of AD (Puzzo et al., 2014). The PDAPP mouse line was the first one developed, overexpressing human APP containing a fAD mutation, which shifts the APP processing towards the more extended Aß peptide variant (Games et al., 1995). Similarly, the famous Tg2576 mouse line contains two point mutations on their overexpressed human APP, which are mutations of the Swedish fAD and increase overall levels of Aß (Hsiao et al., 1996). These mouse lines develop many characteristics of AD, like amyloidogenic plaques, loss of synapses, and synaptic and cognitive deficits. Moreover, when combining the APP mutations with a mutation on the presenilin 1 (PS1) gene, like in the double transgenic APP/PS1 mice, the AD pathology course progresses quicker, starting symptoms around 3 months old (Holcomb et al., 1998; Puzzo et al., 2014). The 5xFAD mice express a total of five mutations, three fAD mutations on APP and two PS1 mutations, highly accelerating AD pathology (Crouzin et al., 2013; Puzzo et al., 2014). However, these transgenic mouse models lack tau pathology, the other hallmark of AD. The 3xTgAPP mouse line addresses this by harboring APP and PS1 mutations and expressing mutant tau too, producing the neurofibrillary tangles and neurodegeneration (Chambon, Wegener, Gravius, and Danysz, 2011; Oddo et al., 2003; Puzzo et al., 2014). All these transgenic mouse models overexpress the APP, thus making it difficult to distinguish between the effects of elevated Aβ and APP contributing to the phenotype. In 2016 Saito et al. presented human mutant APP knock-in mice, which express APP normally and show a developing Aβ pathology more resembling the disease progression (Masuda et al., 2016; Saito et al., 2014). However, while these knock-in mice lines are nowadays used in numerous laboratories worldwide, their abilities to model AD more accurate than overexpressing transgenic mice remains debatable (Huang et al., 2015; Jacob et al., 2019; Mehla et al., 2019). The usage of these transgenic mouse lines advanced the understanding of AD, and they continue to be valuable tools. However, their creation was based on the hypothesis that the plaques are determining the cognitive decline. Today we know that it is not the plaques but rather the soluble Aß levels that correlate with the cognitive impairment. As mentioned above, before plaque formation, Aß exits in soluble form as monomers, dimers, oligomers, globules, and fibrils, all of which could be the toxic formation contributing to the cognitive decline. Thus, the amyloid hypothesis evolved to posit that soluble Aßs are responsible for AD. Indeed
11 electrophysiology studies have shown that small soluble Aß oligomers are capable of impairing synaptic plasticity, reducing long-term potentiation (LTP), and are linked to neurotoxicity (Chambon et al., 2011; S. Li et al., 2009; Shankar et al., 2008). Similar effects have also been proven by studies using globular and fibrillar Aß (Kayed et al., 2009; Shankar et al., 2007). Synaptic plasticity is essential for memory formation. The reduction in LTP observed through acute application of these peptides on hippocampal slices, implies a connection to the deficits observed in AD. To test this hypothesis, a new kind of animal model emerged, mice with intracerebroventricular injections or infusions of Aß peptides. The injection allows the study of AD pathology without the necessity of plaques. Today, we know that already picomolar concentrations of Aß are sufficient to impair different forms of synaptic plasticity (LTP and long-term depression (LTD)) as well as learning and memory performance in mice (Canet et al., 2020; Doran et al., 2017; Meunier, Villard, Givalois, and Maurice, 2013; Morley et al., 2010; Puzzo et al., 2008; Puzzo, Arancio, and Puzzo, 2013; Toombs, n.d.; Wiseman et al., 2018).
1.1.3 Non-Amyloidogenic Pathway
The second well-established pathway in APP processing is the non-amyloidogenic pathway, which mediates the cleavage of APP within the Aß region by α-secretase (Figure 1). This cleavage generates a sAPP-α fragment for extracellular secretion and CTF-α (C83). The C83, similar to the amyloidogenic pathway CTF-ß, can then be further processed by γ-secretase generating AICD and p3 (Haass et al., 2012; Turner et al., 2003). Exploring the physiological role of the non-amyloidogenic pathway has not been a major focus of research. Most attention focused on the pathway’s potential use in curing AD. The amyloidogenic pathway competes with the others to process APP. Thus, enhancement of this non-amyloidogenic pathway decreases the amyloidogenic APP processing and, therefore, Aß aggregation.
1.1.3.1 α -Secretase Different members of disintegrin and metalloproteinase (ADAM) family, which are type 1 transmembrane proteins, can act as α -secretase, of which ADAM10 and ADAM17 are the most common. ADAM17 is not involved in constitutive APP cleavage but plays a role in regulated APP cleavage. Thus, ADAM10 acts as the main α-secretase, mostly found in post-synaptic regions of excitatory synapses. Blocking ADAM10 reduces overall sAPP-α production by up to 90 %, highlighting its importance for non-amyloidogenic processing of APP (Christensen et
12 al., 2008; Goddard, Bunning, and Nicola Woodroofe, 2001; Jorissen et al., 2010; Kuhn et al., 2010; Marcello et al., 2013; Nunan and Small, 2000; Rivera et al., 2019; Zhang et al., 2011). ADAM10 is a member of the zinc proteinase family containing a catalytic domain with a zinc- binding recognition side. The protein consists of a pro-domain, a disintegrin-like domain rich in cysteine, a transmembrane domain, and a short cytosolic C-terminal. Before cleavage of the pro-domain, ADAM10 concentrates in the Golgi apparatus as a pro-enzyme. After activation, ADAM10 undergoes N-glycolisation and, apart from a small fraction of the protein stored at the Golgi apparatus and in vesicles, is mainly concentrated at the plasma membrane. Nevertheless, levels of ADAM10 at the plasma membrane are tightly regulated. Studies suggest that synaptic plasticity plays a significant role in the regulation as LTP induces exocytosis, whereas LTD leads to insertion of ADAM10 at the synapse (Endres and Deller, 2017; Endres and Fahrenholz, 2010; Lammich et al., 1999; Marcello et al., 2013; Seegar et al., 2017). Cleavage of APP by α-secretase produces sAPP-α and C83, which then can be further processed by γ-secretase (Figure 1). While mutations in α-secretase have been observed to shift APP processing away from the non-amyloidogenic pathway and are associated with sporadic AD, it is noteworthy that ADAM10 is not APP specific (Suh et al., 2013). This protein is also a significant player in brain development, and excessive activation of ADAM10 is associated with tumor development (Deuss, Reiss, and Hartmann, 2008; Groot et al., 2014; Jorissen et al., 2010; Postina, 2012; Raucci et al., 2008).
1.1.3.2 P3 Cleavage of CTF-α via γ-secretase gives rise to AICD and a small 3 kDa fragment of about 17-
40 APP residues named p3 (Aβ17-42) (Iwatsubo, Saido, Mann, Lee, and Trojanowski, 1996;
Simons et al., 1996). Together with Aβ42, it has been found to accumulate in plaques and may be involved in neuronal apoptosis. Thus, it is considered neurotoxic but less detrimental than Aβ due to its shorter sequence (Iwatsubo et al., 1996; Nhan, Chiang, and Koo, 2014; Wei, 2002). Knowledge about p3 and its physiological role remains elusive.
1.1.4 γ-Secretase
In both pathways described above, amyloidogenic and non-amyloidogenic, the γ-secretase is the finalizing step to release the AICD fragment and either Aß or p3. Cleavage of APP via γ- secretase occurs near the C-terminal of the transmembrane domain. The cleavage site is not only broad, spanning from 14-43 amino acids, but γ-secretase can also sequentially cleave APP producing peptides of different lengths (Kummer and Heneka, 2014; Moore et al., 2012;
13 Portelius et al., 2012; Takami et al., 2009). The term γ-secretase was first used in 1993 to describe the proteolytic cleavage of APP. Indeed, the γ-secretase is not an enzyme but a high molecular weight multi-subunit protease complex consisting of at least four integral membrane proteins: a) presenilin, b) nicastrin, c) presenilin-enhancer 2 and d) anterior pharynx-defective- 1 (De Strooper, Iwatsubo, and Wolfe, 2012; Haass and Selkoe, 1993; Jiang et al., 2014; Laudon et al., 2005). The presenilin protein can either be PS1 or presenilin 2 (PS2). Both forms span the membrane multiple times, containing a large hydrophilic loop and have their N-and C-terminals oriented towards the cytosol. These terminals undergo further maturation in the assembly of the γ- secretase, thus generating the amino-terminal fragment (NTF) and CTF. The matured proteins then form a heterodimer, each containing a highly conserved aspartate residue, which is essential for the catalytic activity of the γ-secretase. PS1 itself is involved in the trafficking of the other γ-secretase components, as well as other transmembrane proteins, including APP. Due to their importance for the γ-secretase complex and involvement in both pathways described above, amyloidogenic and non-amyloidogenic, protein trafficking, mutations in either one of them, PS1 or PS2, are causes for fAD (De Strooper et al., 2012; Gandy et al., 2007; Jiang et al., 2014; Karran et al., 2011; Laudon et al., 2005; T. Li, Ma, Cai, Price, and Wong, 2003; Y. Liu et al., 2009; Pintchovski, Schenk, and Basi, 2013). Of the other three γ-secretase complex proteins, the type 1 transmembrane glycoprotein nicastrin serves as the receptor of the γ-secretase complex being highly involved in the recognition and binding of substrates (Jiang et al., 2014). The presenilin-enhancer 2 is responsible for the maturation of PS1 and PS2 conversing the full-length presenilin into the active heterodimers mentioned above (Knappenberger et al., 2004; Thinakaran et al., 1996). The last protein of the γ-secretase complex is the seven-transmembrane protein anterior pharynx-defective-1, which interacts with nicastrin forming a stable intermediate form of the complex during the early assembly stage (Chiang, Fortna, Price, Li, and Wong, 2012; Raphaëlle Pardossi-Piquard et al., 2009). There exist two different forms, the anterior pharynx-defective- 1a or anterior pharynx-defective-1b, which, together with PS1 and PS2, make up at least four alternative possibilities for the γ-secretase complex structure. The γ-secretases complex containing PS1 seems to be the one mainly involved in the amyloidogenic pathway, secreting more Aß than the PS2 containing complex (De Strooper, 2003; Jiang et al., 2014; Takasugi et al., 2003; Tamagno et al., 2012). Synthesis of the different compartments of the γ-secretases complex happens in the endoplasmic reticulum. The exact process of assembly, maturation, and trafficking of the γ-
14 secretase are ambiguous. As mentioned above, anterior pharynx-defective-1 and nicastrin form a stable intermediate, which then binds the full-length presenilin (PS1 or PS2) (Capell et al., 2003; Kaether et al., 2004; LaVoie et al., 2003). Somewhere between transportation from the endoplasmic reticulum to the Golgi apparatus, the presenilin-enhancer 2 binds to the transmembrane domain of the presenilin protein. The presenilin-enhancer 2 then converts presenilin via cleavage into a 30 kDa NTF and a 20 kDa CTF, which continue to form the heterodimer. During trafficking through the Golgi apparatus, nicastrin is glycosylated, and the γ-secretase complex maturated. All of the compartments of the γ-secretase complex are necessary for its function, and deficiency in any of them affects the enzymatic activity of the complex (Jiang et al., 2014; Takasugi et al., 2003; Tamagno et al., 2012). About 5 % of all maturated γ-secretases reach the plasma membrane, with the majority cycling between the endoplasmic reticulum and Golgi. At the plasma membrane, the γ-secretase undergoes endocytosis to the endosomes or is transported to the lysosomes for degradation. Besides its role in APP processing, the γ-secretase plays a vital role in the Notch pathway, thus crucial for cell survival (Dries and Yu, 2008; Jiang et al., 2014).
1.1.5 η-Secretase Pathway
The η-secretase pathway of APP processing is the most recently discovered among the three presented in this introduction, first described in 2015 by two independent groups (Haizhi Wang et al., 2015; Willem et al., 2015). This pathway is initiated by cleavage of APP by η-secretase, leading to the secretion of sAPP-η fragment and a CTF-η fragment (Figure 1). The CTF-η, when further processed by either α-secretase or ß-secretase gives rise to the Aη-α peptide or the shorter Aη- ß peptide, respectively. Whether the processing of CTF-η to Aη-α and Aη-ß occurs in sequence or parallel is currently unknown. Studies concerning the distribution and compartmentalization of α-secretase and ß-secretase make it more likely that production of the two Aη peptides occur in parallel (Haass et al., 2012; Haizhi Wang et al., 2015; Willem et al., 2015). APP processing via η-secretase seems to be more common than amyloidogenic processing, exceeding it up to five-fold. It is noteworthy that in a healthy individual, non-amyloidogenic processing is also more common than APP cleavage via β-secretase. It seems that η-secretase activity is BACE-1 dependent, as inhibition of BACE-1 enhances η-cleavage (Willem et al., 2015). Furthermore, MT5-MMP (the main η-secretase, see below) and CTF-η, a product of APP cleavage via η-secretase, have been identified around senile plaques. CTF-η can also be found in dystrophic neurons in AD brains (Sekine-Aizawa et al., 2001; Willem et al., 2015).
15 1.1.5.1 η -Secretase Earlier studies proposed the membrane-type (MT) 3- metalloproteinase (MMP) and MT1-MMP among MT5-MMP as proteinases able to cleave APP. However, inhibition of MT5-MMP significantly reduced CTF-η production, identifying it as the main η-secretase (Haizhi Wang et al., 2015; Willem et al., 2015). MT5-MMP cleaves APP965 at VLAN504-M505IPSEPR, termed η-site, generating CTF-η and sAPP-η (Figure 2). The ~ 30 kDa CTF-η can then be further cleaved by α-secretase to generate Aη-α or ß-secretase to generate Aη-ß, respectively (Willem et al., 2015).
Figure 2 Illustration of APP cleavage site of η-secretase. Indicated are also the cleavage sites of α-and β-secretase, which give rise to Aη-α and Aη-β, respectively. The γ-secretase is involved in the non- and amyloidogenic pathway. Adapted from (ALZFORUM, 2018).
MT5-MMP expresses mainly in the nervous system. Its expression level reaches its maximum in rodents before birth and remains at a high concentration into adulthood in defined areas like the hippocampus or cerebellum. This expression window indicates the importance of MT5- MMP in brain development and maintenance (Hayashita-Kinoh et al., 2001; Jaworski, 2000; Pei, 1999; Sekine-Aizawa et al., 2001; Warren, Reeves, and Phillips, 2012). MT5-MMP is a member of a larger family of metalloproteinases (MMP), consisting of 24 proteinases divided into five subcategories, one of them termed MT-MMPs. Thought to be extracellular matrix-degrading enzymes, increasing evidence suggests essential roles in non- matrix related areas such as interaction with signaling molecules, trophic factors, receptors and involvement in neuroinflammatory processes (Marchant et al., 2014; Ould-Yahoui et al., 2009, 2013; Rosenberg, 2002, 2017). The MT-MMPs convey significant homological protein structure within their protein family. MT5-MMP, for example, shares about 60 % sequence homology with MT1-MMP. They have
16 a hydrophobic signal peptide consisting of 17-29 amino acids that destines them for the endoplasmic reticulum for editing. A pro-domain ranging from 77-87 amino acids, containing a cysteine sequence, follows the signal peptide. The cysteine sequence interacts with the Zn2+ of the catalytic domain, thus inactivating the enzyme. A specific sequence in the pro-domain, recognized by serine endoproteinase furin leads to its proteolytic cleavage from the rest of the molecule in the Golgi network. This mechanism termed "cysteine switch" breaks the cysteine and Zn2+ connection between pro-domain and catalytic site, activating the protein. The highly conserved catalytic domain connects to the hemopexin domain via a short hinge region. The hemopexin domain comprises about 220 amino acids and is quite variable in its sequence, crucial for protein-substrate specifically among the MMPs. Linkage to the plasma membrane can occur via two different mechanisms in MMPs; either via glycosylphosphatidyl inositol or, as is the case for MT5-MMP, by a transmembrane domain. This transmembrane domain is followed by a short intracytoplasmic domain, which plays an essential role in MT5-MMP's cell trafficking and proteolytic activity. When internalized in endosomes, the last three residues of the MT5-MMP C-domain can interact with Mint3, a PDZ protein, to be recycled again to the membrane, or interact with APP (Okada, 2017; Pei, 1999; Sakamoto and Seiki, 2009; Uekita, Itoh, Yana, Ohno, and Seiki, 2001; P. Wang, Wang, and Pei, 2004; X. Wang and Pei, 2001). Human and mouse MT5-MMP carry a unique dibasic motif in their stem region, which can be cleaved by furin-like proteases generating a catalytic active enzyme form lacking the C- terminal part. This form of MT5-MMP is only transitory at the plasma membrane, released as a soluble protein (García-González, Pilat, Baranger, and Rivera, 2019). The role of η-secretase cleavage of APP in AD remains elusive. The absence of MT5-MMP, which likely leads to a reduction in η-secretase cleave of APP, in a bi-genic 5xFAD/MT5- MMP-/- mice strain prevents impairments in LTP and spatial and working memory usually observed in 5xFAD mice. In the advanced stage of disease progression in 16-months-old mice, 5xFAD/MT5-MMP-/- mice show better preservation at the neuronal and synaptic levels when compared to age-matched 5xFAD mice. Interestingly these 5xFAD/MT5-MMP-/- mice had a significant reduction in Aβ production ranging from soluble Aβ40 and Aβ42, up to plaques in hippocampal and cortical regions. Furthermore, inhibition of MT5-MMP reduces numbers of reactive glial cells and astrocytes around amyloid plaques and reduces inflammatory indicators like IL-1β and TNF-α. (Baranger et al., 2017; Baranger, Marchalant, et al., 2016; Crouzin et al., 2013; Kimura and Ohno, 2009). Thus, it seems that the MT5-MMP mediated η-secretase activity might contribute to AD, as inhibition of MT5-MMP reduces amyloidogenic processing in an AD context as observed in 5xFAD/MT5-MMP-/- mice. Additionally, studies indicate that
17 MT5-MMP can be internalized in endosomes and promote endosomal APP sorting, which is the main site of amyloidogenic APP processing (Baranger et al., 2017; Baranger, Marchalant, et al., 2016; P. Wang et al., 2004; Willem et al., 2015). The η-secretase pathway does not employ the γ-secretase complex, which fulfills a crucial role for the other pathways of APP processing. Thus, MT5-MMP could not be detected when co- purifying the high molecular complex formed by BACE1 and γ-secretase (Chen et al., 2015; L. Liu, Ding, Rovere, Wolfe, and Selkoe, 2019). Outside of APP processing, MT5-MMP is involved in brain development regeneration by promoting axonal growth and controlling activation of adult stem cells after nerve injury. Only after imposing mice into stressful conditions like nerve injuries is the involvement of MT5-MMP in regulating neuroinflammatory processes observable. In a healthy state, MT5-MMP knock-out mice show no strong phenotype, indicating functional redundancy with other proteins (Hayashita-Kinoh et al., 2001; Komori et al., 2004; Krämer et al., 2018; Porlan et al., 2014; Warren et al., 2012).
1.1.5.2 Amyloid η-α and Aη-β A search in the recent literature shows that the physiological role of Aη-α and Aη-β remains elusive. The primary reference work remains Willem et al., which provided the first evidence of bioactivity of the Aη-α peptide. Here, they describe the effect of the acute application of Chinese hamster ovary (CHO) cell-produced and secreted recombinant Aη-α and Aη-β on the CA3-CA1 synapse in hippocampal slices (Willem et al., 2015). They observe no effect for recombinant Aη-β when acutely applied to an excitatory post-synaptic response or when measuring LTP. By contrast, acute application of recombinant Aη-α impaired LTP. When applied in vivo on the hippocampal CA1 region an acute reduction in calcium wave activity was observed for Aη-α but not for Aη-β. Furthermore, while Aη-α has been detected in the cerebrospinal fluid (CSF) of AD patients and healthy controls, no differences between groups could be observed. Intriguingly, when looking at a 25 kDa CTF fragment created by APP cleavage through η-secretase differences in concentrations∼ between groups were detected (García-Ayllón et al., 2017; Willem et al., 2015). Together with the data from η-secretase activity, this could challenge the traditional view of α- secretase being beneficial and β-secretase being harmful.
1.1.6 Soluble APP
The three secretases, α-, β- , and η-secretase, cleaving APP generate three different extracellular soluble N-terminal APP fragments a) sAPP-α, b) sAPP-β, and c) sAPP-η (Figure 1). Via the
18 different recognition sites of these secretases, the sAPP vary slightly in length, sufficient to lead to significant structural changes between them, indicated by the detrimental and neuroprotective roles assigned to sAPP-β and sAPP-α, respectively (Chasseigneaux and Allinquant, 2012; Peters-Libeu et al., 2015). These structural changes among them become more intriguing by the recent discovery of all three sAPPs sharing a common receptor (Rice et al., 2019).
1.1.6.1 sAPP-α This approximately 110 kDa sized fragment heavily depends on ADAM10, the main α- secretase, as it interrelates with its production levels. In CSF of AD brains, where APP processing shifts towards the amyloidogenic pathway, levels of sAPP-α are reduced compared to healthy controls. This reduction in sAPP-α levels seems to correlate directly with emerging cognitive deficits (Almkvist et al., 1997; Lannfelt, Basun, Wahlund, Rowe, and Wagner, 1995). On the other hand, data indicate that Aβ oligomers initiate sAPP-α secretion. As sAPP-α can interact with BACE1 inhibiting the amyloidogenic pathway, this could be an initial neuroprotective response in AD pathology (Obregon et al., 2012; Rose et al., 2018). Furthermore, increasing sAPP-α levels reduce impaired LTP and memory performance in AD mouse models (Hick et al., 2015; Postina et al., 2004; Tan et al., 2018). The neuroprotective role of sAPP-α seems not only limited to APP processing as it is presumed to be further involved in cell adhesion, synaptogenesis, neurite outgrowth, neuronal stem cell proliferation and as an actor against demyelination (Chasseigneaux and Allinquant, 2012; Giuffrida et al., 2010; Llufriu-Dabén et al., 2018; Mattson et al., 1993; Mockett et al., 2019).
1.1.6.2 sAPPβ Secreted into the lumen via cleavage of APP by β-secretase, the sAPP-β is 16 amino acids shorter than sAPP-α (Chasseigneaux and Allinquant, 2012). Thought to bind to death receptor 6 (DR6) inducing axonal pruning and neuronal apoptosis via activation of DR6 and caspase-6, sAPP-β is considered more detrimental than neuroprotective (Nikolaev, McLaughlin, O’Leary, and Tessier-Lavigne, 2009). While a later study could disprove sAPP-β involvement in apoptosis via DR6, its involvement in axonal pruning was confirmed (Olsen et al., 2014). Furthermore, a recent study indicates sAPP-β interfering with mitochondrial function, leading to proinflammatory processes and poor insulin sensitivity (Botteri et al., 2018).
1.1.6.3 sAPP-η The sAPP-η or sAPP-95 is the product of the η-secretase cleavage of APP. Its functional relevance is mostly unknown. However, in a recent publication, it has been shown that sAPP-
19 η, together with sAPP-α and sAPP-β, can reduce synaptic vesicles release, thereby modulating synaptic transmission. This modulation is achieved by binding to the γ-aminobutyric acid type B receptor subunit 1a (GABABR1a), leading to modulations of the γ-aminobutyric acid (GABA) and glutamate neurotransmitter system (Rice et al., 2019).
1.1.7 Carboxyl-Terminal Fragment
As with sAPP, the three pathways create different C-terminal APP fragments (CTFs): a) C99, b) C83, and c) CTF-η (Figure 1). Among them, the main focus has been directed towards the C99, product of the amyloidogenic pathway and shown to accumulate in AD brains (Kim et al., 2016; Pera et al., 2013). Interestingly, the accumulation of C99 seems to correlate better with the neurodegeneration observed in AD than increased Aβ production (Pulina, Hopkins, Haroutunian, Greengard, and Bustos, 2019). Thus, there exist numerous studies enhancing pharmacologically or genetically the levels of C99 demonstrating its pathological properties in AD (Bourgeois et al., 2018; Lauritzen et al., 2012, 2016; Matsumoto, Watanabe, Suh, and Yamamoto, 2002; Neve, Boyce, McPhie, Greenan, and Oster-Granite, 1996; Oster-Granite, McPhie, Greenan, and Neve, 1996; Song et al., 2002). The product of the non-amyloidogenic pathway C83 is 83 amino acids long, hence its name. This fragment can inhibit the amyloidogenic processing of APP by interfering with the γ- secretase cleavage of C99 in HEK cell cultures (Tian, Crump, and Li, 2010). Hence it could be considered protective in the pathogenic progression of AD. These CTFs are usually only transient peptides in APP processing and usually further cleaved, giving rise to Aβ, P3, and the smaller APP intracellular C-terminal protein AICD. There is evidence that CTF-η produced in the η-secretase pathway, can accumulate around amyloidogenic plaques and in dystrophic neurons (Willem et al., 2015). A recent study demonstrated that neurons can absorb CTF-η secreted in extracellular vesicles of APP Swedish expressing N2a neuroblastoma cells, suggesting that this fragment might propagate between cells (Laulagnier et al., 2018). Other roles of CTF-η in a more physiological context remain elusive.
1.1.7.1 AICD AICD, representing the C-terminal intracellular domain of APP released at the end of APP processing by different pathways, varies in length as there are many cleavage sites for γ- secretase on APP. When released intracellularly after cleavage, the majority of AICD degrades quickly. Nevertheless, AICD is considered a vital regulator of gene expression (Beckett,
20 Nalivaeva, Belyaev, and Turner, 2012; Belyaev et al., 2010; Passer et al., 2000). For alterations in gene expressions, it undergoes translocation to the nucleus to collaborate with proteins acting as transcription factors (Beckett et al., 2012). These interactions, for example, with Fe65 or Tip60, are regulated via several conserved regions on AICD (Borg, Ooi, Levy, and Margolis, 1996; Raphaëlle Pardossi-Piquard and Checler, 2012; Sabo, Ikin, Buxbaum, and Greengard, 2001). Other than acting as a regulator of gene expression, AICD might be involved in AD pathology through the binding and degradation of Aß (Chang et al., 2006; Kerridge et al., 2014; KIM et al., 2003). Thus, it can act as a promotor for transactivation of genes responsible for APP degrading like the Aβ-degrading enzyme neprilysin (Belyaev, Nalivaeva, Makova, and Turner, 2009; Q. Liu et al., 2007; R. Pardossi-Piquard et al., 2006; Raphaëlle Pardossi-Piquard et al., 2005). The field investigating AICD's physiological role is evolving. AICD is associated with cytoskeleton dynamics, cell cycle control, balancing calcium and ATP levels (Bukhari et al., 2017; Hamid et al., 2007). It is involved in the regulation of synaptic plasticity as it governs the levels of the synaptic GluN2B sub-unit of the NMDA receptor (NMDAR), via a transcription dependent mechanism (Pousinha et al., 2017). It was further shown that levels of neuronal AICD control NMDAR-dependent synaptic signaling and LTP, but not LTD (Pousinha et al., 2017). Also, most recently, it was further shown that increasing neuronal AICD levels perturb intrinsic neuron intrinsic excitability, rendering the neurons hypoexcitable and leading to disruption of brain oscillatory activities. Increasing AICD levels in the brain in vivo perturbs spatial memory encoding, as could be expected from its recently-described impact on neuron signaling (Pousinha et al., 2019).
1.1.8 Other APP Processing Pathways
Alongside the three APP processing pathways presented here, other enzymes cleave APP such as δ-secretase, Meprin-ß, or Legumain. With the rediscovered interested in the physiological role of APP and its proteolytic processing, the number of enzymes cleaving APP and the discovery of new fragments is evolving but describing them all would go beyond the scope of this thesis. These other pathways will not be further explored in this manuscript. This chapter gave an overview of APP and its main pathways, including the η-secretase pathway. It is clear, that the knowledge about the physiological role of these peptides remains elusive.
21 The focus of my thesis is Aη peptides, whose physiological roles in synaptic plasticity have not been further explored since Willem et al. (2015). Most of our experiments involved the hippocampus. We either studied alterations of synaptic plasticity in the hippocampus or submitted mice to hippocampal-dependent memory tasks in the behavioral tests. The following chapter will introduce the hippocampus, the concept of memory, and posit the hippocampus as an essential structure to study memory formation.
22 The Hippocampus
The human hippocampus' shape resembles two different structures, a seahorse and ram's horn. Thus, the name hippocampus derives from the ancient Greek word "hippokampos" meaning seahorse. The subfields of the hippocampus are called Cornu Ammonis (CA) after the horns of the ancient Egyptian god Ammon. It’s simple but distinctively structured anatomy makes the hippocampus an ideal model system for various fields like Learning and Memory, and Electrophysiology. The rodent hippocampus, which has been extensively studied for decades, provides insights into mechanisms ranging from the molecular to the circuit level (Fröhlich, 2016).
1.2.1 Anatomy of the Hippocampus
Figure 3 Cross section through the hippocampus. Illustration of the anatomical organization of the hippocampus formation, with the hippocampus proper and its subfields, the dentate gyrus and the parahippocampal gyrus. The different strati of the hippocampus proper are indicated. Adapted from (Kiernan, 2012).
There are two hippocampi in the brain, one in the temporal lobe of each hemisphere. The lateral ventricle surrounds the hippocampal formation. The structures associated with the hippocampal formation vary depending on the definition but generally include (see Figure 3): a) the hippocampus proper, dividing into four subfields CA1, CA2, CA3, and CA4
23 b) the adjacent cortex named parahippocampal gyrus, which divides into the entorhinal cortex and the subiculum, and c) the dentate gyrus (Amaral and Lavenex, 2007; Anand and Dhikav, 2012; Lorente De Nó, 1934). Among mammals, the neuronal layout and pathways within the hippocampus formation are comparable, but with varying anatomical location nomenclature (Andersen, Morris, Amaral, Bliss, and O’Keefe, 2007; M. B. Moser and Moser, 1998). Hence, in primates, the hippocampus divides into anterior, intermediate, and posterior regions referring to ventral, intermediate, and dorsal regions in other animals, respectively. These regions have a similar structure but belong to different neural circuits and are functionally distinct. Indicated by nomenclature, the intermediate region has overlapping characteristics with the other two. However, studies suggest that the dorsal region is implicated in spatial memory, verbal memory, and learning conceptual information while fear conditioning and affective processing are associated with the ventral region (Cenquizca and Swanson, 2007; Pothuizen, Zhang, Jongen-Rêlo, Feldon, and Yee, 2004). A cross-section through the hippocampus and dentate gyrus disclose their different cell layers (Figure 4). The dentate gyrus has four cell layers, in- to outward order: 1) molecular layer, 2) the inner molecular layer, 3) the granular layer, and 4) the hilus. The hippocampal subfield CA3 contains five strati 1) lacunosum-molecuare stratum, 2) radiatum stratum, 3) lucidum stratum, 4) pyramidal stratum, and 5) oriens stratum, similar to CA1 and CA2, which miss the lucidum stratum (Hammond, 2001; Lein, Callaway, Albright, and Gage, 2005).
24
Figure 4 Hippocampal Circuitry. Different layers of the hippocampal subregions and the dentate gyrus. In CA1 shown are lacunosum-molecuare stratum (LAC MOL), radiatum stratum (RAD), pyramidal stratum (PYR), oriens stratum (OR) and alvear (ALV), in CA3 lucidum stratum (LUC), and in DG molecular layer (MOL) and granular layer (GR). Adapted from (Hammond, 2001).
Information processing in the hippocampus can occur via two pathways, the direct or indirect pathway (Figure 5, Figure 6). In both pathways the entorhinal cortex acts as the input structure and CA1 mediates the output. The direct pathway has axons arising from layer III of the entorhinal cortex form synapses with distal apical dendrites of CA1 neurons. The indirect pathway, known as the trisynaptic circuit, also originates from the entorhinal cortex. The prefrontal pathway projects axons, starting from layer II of the entorhinal cortex to granule cells of the dentate gyrus, the first synapse of the circuit. From here, mossy fibers, consisting of unmyelinated axons, project to pyramidal cells of CA3, producing the second circuit synapse. The third synapse forms between CA3 and CA1 through axons called Schaffer collaterals. CA1, the main output of the hippocampus, projects to the subiculum, which projects back to the entorhinal cortex, completing the circuit. The subiculum projects to other regions, too. For example, the fornix receives input from the subiculum and holds connections to the thalamus and the hypothalamus (Knierim, 2015).
25
Figure 5 Basic anatomy of the hippocampus. Illustration of an overview of the hippocampus, focusing on the trisynaptic circuit originating from the II layer of the entorhinal cortex (turquoise), and the direct pathway arising from the III layer (purple). Adapted from (Neves, Cooke, and Bliss, 2008).
Figure 6 The two different pathways of information processing in the hippocampus. The black arrows represent the trisynaptic circuit. The direct pathway is shown by the red arrow originating from the EC. Taken from (Knierim, 2015).
1.2.2 Functional Role of the Hippocampus
The hippocampus is an essential brain structure. Damaging or removal of the hippocampus and its neighboring structures lead to profound impairments (Anand and Dhikav, 2012; Knierim, 2015). The neuronal activity in the hippocampus also seems dependent on specific information retrieved or position in space. There exist three theories for the primary hippocampal function being responsible for response inhibition, episodic memory, and spatial cognition. The importance of the hippocampus in the concept of memory is accepted, with its precise role still debated (Eichenbaum, 2017; Hodges, 1995; Squire, 1992).
26 1.2.3 Hippocampus and Memory
The crucial role of the hippocampus in memory formation, like many great discoveries, was somewhat accidental. In 1953 Dr. Scoville performed brain surgery removing the temporal lobes and two-thirds of the hippocampus in a patient H.M. to reduce epileptic seizures, developed after a skull fracture during childhood. In that period, the removal of brain parts was a common practice to cure people with a mental health condition, as it was believed that mental functions correlate to defined brain structures. Indeed, the surgery led to a reduction of seizures in both cases, H.M. and mental patients. However, described in the famous case study 1957, H.M. faced impaired declarative memory formation post-surgery. While he was able to retrieve memories concerning the decade pre- surgery and childhood memories, the ability to remember events around the period of surgery and afterward was gone (Scoville and Milner, 1957). He continued to provide valuable insights and redefining the definition of memory. In 1962 Dr. Milner, who studied H.M. and similar cases, published her findings after studying him over an extended period (Corkin, 1984; B Milner, 1962; Brenda Milner, Corkin, and Teuber, 1968; Penfield and Milner, 1958). The findings comprised the distinct differentiation between short term and long term memory, with storage in different brain regions and the existence of different memory forms, such as declarative and procedural memory (Squire, 2009).
1.2.3.1 Definition of Memory
Figure 7 Different forms of memory, their subcategories and the brain structures associated with them. The long-term memory is divided into declarative and non-declarative memory, which each subdivide further. Declarative memory is medial-temporal lobe/diencephalon dependent. Non-declarative memory, depending on the subdivision involves several brain regions. Short- term memory is linked with working memory, both distinct from each other. Adapted from (Paul, Magda, and Abel, 2009).
27 Two different axes define memory, the time of recall, and the type of memory. The time of recall distinguishes between short-term and long-term memory (Figure 7). Short-term memory stores a limited amount of information for a short period. In humans, the capacity is limited to 4 +/- 1 units, forgotten after a few seconds (N. Cowan, 2001; Nelson Cowan, 2008). Capacity can increase through repetition or chunking. Formation of short-term memory modulates synaptic connections and nerve cells via second messenger mediated covalent modifications. This process is independent of protein synthesis and utilizes pre-existing proteins (Goelet, Castellucci, Schacher, and Kandel, 1986; Schwartz, Castellucci, and Kandel, 1971). Still, short-term memory depends on cortical neuron activity in the lateral prefrontal cortex (Squire and Wixted, 2011). The lateral prefrontal cortex is implicated in higher executive functions, including working memory and attention. While there is a relationship between short-term memory and working memory, there exists a consensus that the two concepts are distinct (Nelson Cowan, 2008; Diamond, 2013). Long-term memory comprises the indefinite storage of information lasting from hours up to a lifetime. Different brain structures are involved in the formation of long-term memory, depending on its form (Figure 7). After formation, the neocortex stores the memory, with distribution depending on brain areas active during learning (Rugg and Vilberg, 2013). The domain of long-term memory divides into declarative and non-declarative memory, each containing further subdivisions. Declarative or explicit memory describes the storage of information possible to verbalize and consciously retrieve, like dates, names, or lines in a play. Episodic memory and semantic memory are the subdivisions. One's past confined as a specific event at a specific time and place defines episodic memory, whereas, one's general knowledge refers to semantic memory. The formation of these memories is strongly dependent on the hippocampus. While the hippocampus proper is crucial for episodic memory formation, the other regions of the medial temporal seem critical for semantic memory formation. Non-declarative or implicit memory defines more practical memories like the motor activities during a bike ride. This segment subdivides into procedural memory, priming, simple classical conditioning and non-associative learning. These memory types rely more on the involvement of other brain structures, such as the basal ganglia and the cerebellum, and are considered hippocampus-independent (Knierim, 2015; Tulving, 1972).
28 1.2.3.2 Memory formation In cases of amnesia older memories are often preserved which leads to the theory that memory storage occurs outside the hippocampus (Squire and Schacter, 2002). The formation of long-term memory comprises several steps, encoding, consolidation and storage. Neurons immediately inscribe received information in the cortex. The cortex transmits the information to the hippocampus, where particular proteins then work to strengthening the synaptic connections. If the experience is periodically recalled or was strong enough, the hippocampus transfers the memory back to the cortex for storage, becoming long-term memory (Goelet et al., 1986; Squire and Wixted, 2011).
1.2.3.3 Working memory Working memory refers to routine and the process of thinking. In literature, the concept itself has different definitions and is somewhat associated with short-term memory, with some describing it as the cognitive side of short-term memory. This type of memory is crucial for thinking in the sense of decision-making and reasoning, which sets it apart from the pure storage of information described in simple short-term memory (Baddeley and Hitch, 1974; Nelson Cowan, 2008; Giudice, Klatzky, Bennett, and Loomis, 2013; Tse et al., 2007). Due to the conceptual nature of working memory, there also theories associating it more with long-term memory. The long-term working memory describes the aspects of memories involved in performing daily routines (Nelson Cowan, 2008; Ericsson and Kintsch, 1995). As mentioned in short-term memory, the prefrontal cortex is a crucial brain structure involved in working memory. Lesions within this brain region lead to impairments in performance, while in vivo electrophysiology experiments confirmed activation of neurons within the prefrontal cortex during working memory dependent tasks (Ashby, Ell, Valentin, and Casale, 2005; Fuster, 1973; Lashley, 1920).
1.2.4 Spatial Memory
Spatial memory is yet another concept of memory associated with the hippocampus. One's knowledge about one's position within the spatial environment, the location of a destination and the path connecting the two constitute spatial memory (Stella, Cerasti, Si, Jezek, and Treves, 2012). Unlike the concepts of declarative and non-declarative memory discovered in humans, studies on spatial memory have been conducted primarily in rodents. However, recent advancements in brain imaging allow a greater number of human studies. Due to these different approaches,
29 the two fields of declarative memory and spatial memory remained historically distinct and have only recently began to merge. The field of spatial memory has its origin in the discovery of space cells by O'Keefe and Nadel in 1978 (O’Keefe and Nadel, 1978). These cells are hippocampal pyramidal cells that fire when the animal locates at a specific position within its environment, with individual cells correlating with one position. Since then, the discovery of head direction cells, acting as a neuronal compass within the environment, and grid cells residing in the entorhinal cortex, updating the environmental information of place cells, are noteworthy advancements within the field (Hafting, Fyhn, Molden, Moser, and Moser, 2005; Muller, Ranck, and Taube, 1996). Lesions within the hippocampus impair performance in spatial memory tasks, highlighting it’s crucial role (De Jong et al., 1999; Gasbarri, Sulli, Innocenzi, Pacitti, and Brioni, 1996; E. I. Moser, Moser, and Andersen, 1993).
1.2.5 Anxiety
The limbic system comprises different brain structures to deal with emotions and memory. Revisiting a location, for example, a former school can provoke an emotional response depending on the emotional load that location holds (Godinez, McRae, Andrews-Hanna, Smolker, and Banich, 2016; MacLean, 1952). The center of emotional processing is the amygdala, considered to play a crucial role in fear. However, there exist reciprocal connections between the amygdala and the hippocampus. Additionally, studies in freely moving animals displayed synchronized firing in both regions during fear learning. The consensus is that both structures are involved in the learning of fear memory, while the storage occurs in the anterior cingulate cortex. Within the hippocampus, it seems that especially the ventral part is involved in this kind of task (Ito and Lee, 2016; O’Neil et al., 2015; Toyoda et al., 2011; Y. Yang, Wang, Pizzi, and Leonardo, 2017). In the context of emotions and anxiety, the hippocampus involvement in approach-avoidance conflict situations has been studied. This scenario forces the animal to choose and balance two internal desires, such as safety versus exploratory behavior in the Light-Dark box or open field (Kulesskaya and Voikar, 2014; Willner, 1998).
30 1.2.6 An Object to Study in Neurobiology
The hippocampus has several features making it an ideal brain structure for studies. Compared to other brain structures, its anatomical structure is relatively simple. The trisynaptic circuit is a suitable structure for electrophysiological studies. Furthermore, the hippocampus is involved in numerous crucial mechanisms as described above, and sensitive to changes within its mechanism. The role of the hippocampus as a central region within numerous diseases such as AD, schizophrenia, and depression are additional reasons for its importance in numerous studies (Cooke and Bliss, 2006; Eichenbaum, Otto, and Cohen, 1992; Hodges, 1995; Nakazawa, McHugh, Wilson, and Tonegawa, 2004).
31
32 Methods to Study Physio-Pathological Role of Proteins
Studying proteins and their role within the organism is a complicated task. Depending on the data available, any such endeavor may begin with no guidelines as to "where" and "what" the protein's roles are. Thus, the first decision should be to define the region of interest, for example, in the brain or globally within the organism. Within the brain, we may choose to examine particular regions, for instance the hippocampus.
As for the "what", this may be either: a) Changes in the proteins' expression level: I) over time, ranging from seconds to a lifetime, or II) under particular conditions such as stress or status of health. b) Alterations of the environment in the absence or presence of the protein I) on a molecular, II) cellular, III) regional or IV) global level. The main factor determining the information obtained about the protein of interest are the techniques used in an experiment. They can come from different fields like molecular biology, Electrophysiology, or behavioral biology. Some techniques answer binary questions like the presence or absence of a protein, while others give insights into more complex processes like circuitry or behavior.
1.3.1 Electrophysiology
Electrophysiology in the context of neuroscience is a field focused on studying the electrical properties and activity in neurons. This can either be done in vivo, in brain slices or neuronal cultures. Brain slices like the hippocampal slices used in this thesis have the advantage of being easier to access than in vivo recordings while keeping the integrity of the neuronal organization lacking in neuronal cultures (Selig and Malenka, 1997). Furthermore, using several slices of the same brain allow for intrasubject controls for example in drug studies. The three types of recordings mainly used in brain slices are field potential, intracellular and whole-cell recordings. While intracellular and whole-cell recordings allow the study of single- cell cellular mechanisms, the field potential recordings give an insight into changes of circuitry measuring an area and collecting inputs from hundreds of synapses at a time (Selig and Malenka, 1997).
33 Field potentials encompass rapid waves and baseline shifts detectable throughout the environment of cells of the nervous system. These field potentials are also observable in the conventional electroencephalogram. The source of changes in field potentials creating these waves lies in the changes of membrane potentials. We know that neuronal function correlates with bioelectrical activity and that the resting potential of a neuron lies at approximately -70 mV. Neurons consist of the cell body, axon, and dendrites. While the axons act as the neuronal output structures, the dendrites are the region for information input. Information exchange between neurons occurs at the synapse and is transmitted in the form of action potentials. Upon an action potential, a threshold is surpassed leading to the opening of voltage-dependent membrane channels changing the potential of the neuron. The action potential travels down the axon to the synapse, where it initiates the release of neurotransmitters glutamate for example. These neurotransmitters open another class membrane channels at the post-synapse causing either excitatory or inhibitory membrane potential changes. The opening of these channels and the resulting ion flux is affecting a restricted membrane area at a time, causing localized membrane potential changes. These local changes generate a potential gradient between them and the surrounding membrane area. These intra- and extracellular potential gradients cause a secondary ion current which in the extracellular compartments creates the field potentials studied in field potential recordings (Speckmann, 1997).
1.3.1.1 The Synapse
Figure 8 The tripartite synapse. The synapse consists of the axon of a pre-synapse (green), the dendritic spine of a post-synapse (yellow) and astrocytes (blue). Adapted from (Eroglu and Barres, 2010).
A synapse is a unit of the brain involved in information processing across neurons. The unit consists of a pre-synaptic neuron, a post-synapse, the synaptic cleft spanning the distance
34 between them, and astrocytes, which play a regulatory role (Figure 8). The two main cell types in the brain: neurons, and glial cells, are involved in the information processing dynamics. Neuronal organization in the brain circuitry is fluid, with synapses formed and removed depending on information input as a response to experiences and memory formation. The exact mechanisms are yet not fully understood but essentially mean that physiological changes correspond to connectivity shifts in the brain. These shifts constitute synaptic plasticity. Accordingly, to Hebb's postulate, "Cells that fire together, wire together. Cells that fire apart, wire apart" (Hebb, 1949). Meaning that two neurons firing at the same time, strengthen their connection, thus more likely to fire again in the future. On the other hand, if the firing of two neurons does not match, their connection will be weakened, making connected firing more unlikely. Thus, synaptic strength can be interpreted as the ability to elicit enhanced amplitudes as a response in the post-synaptic neurons. The two main types of synapse in neurons are electrical and chemical synapses. In electrical synapses, information transmission occurs directly via ion exchange between neurons. The chemical synapses, which comprise the majority of synapses, use neurotransmitters (Figure 9). Here, the pre-synapse releases neurotransmitters, which then bind to neurotransmitter receptors at the post-synapse. This binding induces the opening of ion-permeable channels at the post- synaptic site. When evaluating synaptic plasticity, the up- or down-regulation of basal synaptic strength is measured. The basal synaptic strength refers to a one-time release of neurotransmitters at the pre-synapse after an action potential generated via a single stimulation pulse. Changes in synaptic strength can occur via modulation at the pre-or post-synapse, such as alterations in neurotransmitter release or changes in neurotransmitter receptor composition (Cortés- Mendoza, Díaz de León-Guerrero, Pedraza-Alva, and Pérez-Martínez, 2013).
35
Figure 9 Excitatory glutamatergic synapse. The pre-synapse (green) harbors the vesicle filled with glutamate, which are released into the synaptic cleft upon action potential arriving at the pre-synaptic bouton. The post-synapse (orange) contains the glutamate binding receptors. Shown are the mGluR and the three iGluRs: NMDAR, AMPAR, and kainate receptor. The tight regulation of extracellular glutamate concentrations is indicated by the glutamate transporters at the pre- and post- synapse and glial cell (blue), which clear the glutamate form the synaptic cleft within milliseconds. Adapted from (Attwell and Gibb, 2005).
1.3.1.1.1 Glutamate The dominant excitatory neurotransmitter in the brain is glutamate, especially inside the hippocampus. Glutamate is a crucial component involved in the trisynaptic circuit. The metabolic production of glutamate starts with glucose crossing the blood-brain barrier. Glucose can reach the neurons directly or via transportation through endothelial cells and astrocytes using the plasma membrane glucose transporters (GLUT). In the cytosol, glucose then undergoes cytosolic glycolytic breakdown producing pyruvate. This product enters the tricarboxylic acid cycle (TCA), where α-ketoglutarate generates de novo glutamate. Glutamine synthetase in the astrocytes or oligodendrocytes converts glutamate into glutamine, which enters the neurons via glutamine transporters. This glutamine is then transformed back to glutamate via mitochondrial glutaminase and stored in vesicles. Action potentials arriving at the excitatory glutamatergic synapse causes the pre-synapse to release this glutamate into the synaptic cleft. The glutamate concentrations are tightly regulated and upon release cleared up within a scale of milliseconds (Figure 9). Some undergo endocytosis in the neurons and are recycled, and astrocytes absorb others via excitatory amino acid transporters (Niciu, Kelmendi, and Sanacora, 2012). While present at the synaptic cleft after vesicle release, glutamate binds to metabotropic glutamate receptors (mGluRs) or ionotropic glutamate receptors (iGluRs).
36 1.3.1.1.1.1 mGluRs mGluRs are members of the G-protein coupled receptor family, which divides into two subfamilies C and A G-protein coupled receptor family. As members of the C family, they have a large extracellular N-terminal domain-containing ligand-binding site for glutamate. Unlike iGluRs, their activation initiates signal-transduction pathways (Niciu et al., 2012). 1.3.1.1.1.2 iGluR
Activation of iGluRs enables direct ion flux through the plasma membrane. They are tetramers often consisting of two dimers. The subunits share the same composition, consisting of: a) two ligand-binding domains (S1 and S2) for glutamate, b) three transmembrane domains (TM1, TM3, and TM4), and c) one ion-pore lining region (M2) see Figure 10.
Figure 10 Composition of subunits of the iGluR. Each subunit of iGluR (NMDA, AMPA and kainate receptor) is composed of three transmembrane domains (M1, M3 and M4) and one reentrant loop (M2). Moreover, glutamate binding is localized in a pocket that is formed by two extracellular domains (S1 and S2). S1 is present in the N-terminal loop and S2 is localized between M3 and M4. The C-terminus varies in length depending on the subunit specificity. Adapted from (Sanz-Clemente, Nicoll, and Roche, 2013).
The three different iGluRs are α-amino-3-hydroxy-5-methyl-4-isoxazole-propionate receptor (AMPAR), NMDAR, and kainate receptor, located at the post-synapse (Dingledine, Borges, Bowie, and Traynelis, 1999; Niciu et al., 2012). Due to their importance in synaptic plasticity, the focus will be on AMPAR and NMDAR.
1.3.1.1.2 AMPAR AMPAR are responsible for the majority of fast excitatory synaptic transmission, working on a sub-millisecond time scale. They perform a crucial role in the maintenance of LTP and LTD, as both processes depend on AMPAR composition, alterations of numbers of AMPAR present at the post-synapse, post-translational modifications on AMPAR subunits, and auxiliary subunit binding (Figure 11) (Diering and Huganir, 2018; Greger, Watson, and Cull-Candy, 2017). The
37 number of factors involved in determining the kinetics of AMPAR indicates the complexity of the field and various links remain elusive.
Figure 11 Depending on AMPAR composition and post-translational modifications they are added or removed from the post- synaptic density during LTD and LTP. Here pictured are AMPAR, which are modified in number and/or in their affinity during plasticity depending on their subunit composition and post-translational modifications. From (Diering and Huganir, 2018)).
Composition and Assembly As mentioned in the previous chapter, ionotropic glutamate receptors are tetramers. Four different genes encode the four different subunits GluA1, GluA2, GluA3, and GluA4, each of them comprising about 900 amino acids, weighing around 105 kDa. Each subunit holds different channel kinetics, ion selectivity, and receptor trafficking properties (Greger et al., 2017; Henley and Wilkinson, 2016; Kessels and Malinow, 2009). They consist of the highly conserved ligand-binding domain, allowing binding of glutamate, and transmembrane domain, essential for the channel pore assembly. Their extracellular N- terminal domain and cytosolic C-terminal domain are less homolog among subunits, contributing to their disparity (Figure 12). Additionally, post-translational modifications can occur at the C-terminal domain, further enhancing the variance of AMPAR (Diering and Huganir, 2018; Henley and Wilkinson, 2016).
38
Figure 12 Schematic of AMPAR structure. % indicates the identity of each domain between the GluA1-4 subunits. Adapted from (Diering and Huganir, 2018).
Depending on the length of the C-terminal domain, the AMPAR subunits divide into long- and short-tail AMPAR. The long-tail AMPAR comprises GluA1, GluA4, and a splicing variant of GluA2 (GluA2L). Their representation at the synapse is activity-dependent, and the addition of long-tail AMPARs contributes to LTP. The short-tail AMPAR is continuously undergoing endo- and exocytosis and is more associated with LTD (Kessels and Malinow, 2009). The AMPAR subunits GluA2, GluA3, and a splicing variant of GluA4 (GluA4S) harbor the short- tail (Henley and Wilkinson, 2016). The formation of AMPAR tetramers occurs in the endoplasmic reticulum in a two-step dimerization of dimers. The interaction of two subunits' N-terminal- domains initiates their dimerization, which is followed by linking at the ligand and membrane domains, negotiating the second dimerization step. Trafficking through the endoplasmic reticulum depends on subunit composition and assembly rate. Long-tailed GluA subunits, also when combined with short-tail subunits, promote quick trafficking to the synapse. mRNA editing is the limiting factor for the assembly rate. Unedited AMPAR follows quick trafficking to the synapse, which is the case for Ca2+ permeable (CP) AMPARs, which are mainly GluA1 homotetramers and to a small degree GluA2 AMPAR. About 99 % of GluA2, however, is edited and held unassembled in the endoplasmic reticulum. The editing changes the glutamine to arginine at position 607 in the channel pore, thus making them impermeable for Ca2+ (Diering and Huganir, 2018; Henley and Wilkinson, 2016). Distribution in Development Distribution of AMPAR composition varies depending on the developmental stage and brain region. In early development, numerous synapses harbor CP-AMPAR lacking the GluA2 subunit due to low expression levels of GluA2 compared to GluA1. However, at postnatal day (P) 14 AMPAR composition at the synapses changes to GluA2 subunit-containing AMPAR being the majority (Henley and Wilkinson, 2016). Another shift in AMPAR composition occurs 39 at P21, with GluA1 levels decreasing and GluA3 levels increasing. GluA3 containing AMPAR shows reduced deactivation and desensitization than GluA1, likely resembling the increase in the duration of AMPAR responses, post-synaptic excitability, and the reduction in LTP threshold after P21. However, in an adult rodent hippocampus, the majority of AMPAR population in CA1 consists of GluA1/GluA2, representing 80 % of AMPAR population, and GluA2/GluA3 heterodimers. GluA1 homomers' contribution to the AMPAR population is minor (Diering and Huganir, 2018; Henley and Wilkinson, 2016; Lu et al., 2009). GluA4 plays a more prominent role in early development, as homomers are preferentially found in silent synapses P5-7. Nevertheless, they become less abundant in the adult brain, being replaced by GluA2 containing AMPAR through a constitutive process (Henley and Wilkinson, 2016). Post-translational modifications Post-translational modifications occurring at the AMPAR subunits are numerous, including ubiquitination, glycosylation, and phosphorylation. They can occur together or modulate modifications at neighboring sites, either favoring or inhibiting certain combinations of post- translational modifications (Diering and Huganir, 2018). Phosphorylation is the most studied among them, playing a crucial role in LTP and LTD. Phosphorylation, depending on the subunit, is associated with endo- or exocytosis of AMPAR and can impact single-channel properties. Auxiliary subunits AMPAR can assemble with 1-4 transmembrane AMPAR regulatory proteins (TARPs), which are necessary to stabilize AMPAR at the synapse, as loss of TARPs decreases AMPAR expression. They interact via their ligand-binding domain with TARPs. The association with TARPs slows down AMPAR deactivation and desensitization kinetics (Diering and Huganir, 2018). Furthermore, TARPs play an essential role in slot anchoring of AMPAR at the synapse. Slot theory The quantity of AMPAR at the synapse is transient; the short-tail AMPAR undergo continuous endo- and exocytosis, and AMPAR diffuse laterally along the plasma membrane. An increased number of AMPAR at the synapse is one of the critical mechanisms of LTP, giving rise to the slot theory. Slots in the post-synaptic density (PSD), a dense network of synaptic scaffolding, adhesion, and cytoskeletal proteins, can be filled with the lateral diffusing AMPAR (Huganir and Nicoll, 2013; Kessels and Malinow, 2009; Opazo, Sainlos, and Choquet, 2012). The filling is directed via the auxiliary subunit interaction with PSD proteins, for example, stargazin, a
40 TARP, increases binding to PSD-95, a neuron-specific PSD protein. Phosphorylation, occurring during LTP, stabilizes the interaction of PSD-95 and stargazin, thus anchoring the AMPAR/TARP complex.
1.3.1.1.3 NMDAR NMDARs are widely expressed throughout the CNS and are essential mediators in synaptic plasticity due to their Ca2+ ion permeability (Paoletti, Bellone, and Zhou, 2013; Paoletti and Neyton, 2007). The tetramer composition is highly variable with different subunits contributing to the receptors' wide range in biophysical and pharmacological properties (Paoletti and Neyton, 2007). Subunits The subunits divide into three different families: GluN1, GluN2, and GLuN3. The GluN1 subtype has eight different isoforms, all deriving from alternative splicing of one encoding gene. Six different genes encode the four different subunits of GluN2 (A, B, C, and D) and two different subunits of GluN3 (A and B). A GluN1 homodimer is essential in NMDAR, while the other subunits can be either of the GluN families creating di-heteromeric and tri-heteromeric receptors (Paoletti et al., 2013; Paoletti and Neyton, 2007). Assembly The assembly of the subunits is quite conserved among iGluR and GluN subunits. They have a large extracellular N-terminus, a membrane region, and a cytoplasmic C-terminal (Figure 13). The N-terminus of GluN differs from other iGluR by containing two domains the N-terminal domain (NTD) and the agonist-binding domain (ABD). The first 350 amino acids comprise the NTD, playing an essential role in the NMDAR tetramer assembly. It also contains the binding site for allosteric inhibitors, like Zn2+ in the GluN2A and GluN2B subunits. The ABD consists of the pre-transmembrane (TM) 1 region, and a TM3-TM4 loop of the TM segments each of these components about 150 amino acids long. As the name suggests, this region contains the agonist binding site. To activate NMDAR, two agonists have to bind simultaneously, glutamate at the GluN2 subunit, and either glycine or D-serine at the GluN1 or GluN3 subunit (Paoletti and Neyton, 2007).
41
Figure 13 Schematic NMDAR structure and the different binding sites for ligands. Green arrows indicate competitive binding sites for agonists. Orange arrows indicate binding sites for allosteric modulators. Thin orange arrows indicate putative modulatory sites. From (Paoletti and Neyton, 2007).
A membrane region follows the N-terminus, containing three transmembrane segments (TM1, TM3, and TM4) and a re-entrant pore loop (M2), necessary for Ion flux. This region is very homologous among GluN1 and GluN2 subunits, contributing to the channel conductance, Ca2+ permeability, and Mg2+ blockage. The GluN3 subunit differs by an amino acid exchange from neutral to a positively charged amino acid at the site, significantly decreasing these parameters (Paoletti et al., 2013). The cytoplasmic C-terminal varies in size among subunits, explaining the range of 900-1480 amino acids forming the subunits. These variations contribute to their different properties and subunit-specific functions. This region supports interaction with various proteins, is involved in NMDAR trafficking, localization, and downstream signaling (Paoletti et al., 2013; Paoletti and Neyton, 2007). The C-terminal can interact with PDZ domain-containing proteins of the PSD, stabilizing its localization at the post-synapse. Furthermore, phosphorylation of this PDZ- binding motif affects the mobility of the NMDAR subunits, for example, GluNB2 undergoes endocytosis upon phosphorylation (Sanz-Clemente, Matta, Isaac, and Roche, 2010).
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Figure 14 NMDAR subunit diversity and expression pattern throughout development. A Various population of NMDARs that are thought to exist in the CNS. B The expression profile of different NMDAR subunits throughout the mouse brain development. Taken from (Paoletti et al., 2013).
Expression pattern through development The expression of the different subunits varies throughout the brain and development (Figure 14). The GluN1, being essential for NMDAR composition, is ubiquitously expressed from embryonic day 14 onwards. However, the distribution of the different GluN1 isoforms varies across the brain, with GluN1-1 being the principal isoform in the hippocampus (Paoletti et al., 2013). The GluN2 subunits are the main factor contributing to the functional heterogeneity of NMDAR. The expression pattern of the subunits shifts during development. In the embryonic brain, GluN2B and GluN2D are the sole subunits expressed. However, this shifts after birth with GluN2D expression dropping and restriction of expression to the diencephalon and mesencephalon in adult brains. Furthermore, the GluN2A expression begins shortly after birth and rises from then on, replacing GluN2B as the predominant subunit in the brain. While GluN2B expression peaks one week postnatal, from there on levels decline and become progressively restricted to the forebrain. In the adult brain, expression of the GluN2B subunit is associated with excitotoxity and neuronal degeneration, while GluN2A is linked to synaptic plasticity and pro-survival pathways (Hefter, Ludewig, Korte, and Draguhn, 2019). The expression of GluN2C begins postnatally around day ten but is confined to the cerebellum and olfactory bulb (Paoletti et al., 2013). For the GluN3 subunits, expression patterns are converse with GluN3A peaking early postnatal and from there progressively declining, while GluN3B expression increases throughout
43 development, reaching high levels in motor neurons and probably other regions in the adult brain (Paoletti et al., 2013). The defined periods of expression for the different subunits indicate their important role at different stages. While GluN2B, GluN2D, and GluN3A are essential for neuronal development, the GluN2A and GluN2B subunits play a fundamental role in adult synaptic plasticity (Paoletti et al., 2013). Synaptic plasticity involvement As mentioned above, the different subunit composition of NMDAR determines their gating properties. Receptors containing GluN2A have an increased probability of opening compared to the other GluN2 subunits. Interestingly, the GluN1/GluN2A receptors also have the lowest sensitivity to glutamate and glycine. The expression of GluN2A NMDAR is activity-dependent, and they are considered essential for LTP. During LTP, their charge transfer exceeds that of GluN1/GluN2B receptors. However, the GluN2B receptors are independent of the synaptic activity and contributing more to the total charge transfer under low-frequency stimulation. They are considered to be more involved in LTD. It is this involvement in transforming patterns of neuronal activity into long-term changes of synaptic structure and function, which makes NMDARs essential components in synaptic plasticity and memory formation (Paoletti et al., 2013).
1.3.1.2 Long-Term Synaptic Plasticity Post-synaptic plasticity, defined by changes in receptor composition at the post-synapse, is the main force in long-term synaptic plasticity. LTP and LTD are the two main mechanisms of long-term synaptic plasticity. Both mechanisms are considered crucial for long-term memory formation, which can last for days or a lifetime.
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Figure 15 The two main forms of long-term plasticity LTD and LTP. On the left is an illustration of the ongoing processes during LTD. Moderate Ca2+ influx through the NMDAR, dephosphorylation of AMPAR subunits leading to destabilization of their slot position at the post-synapse. Resulting in endocytosis and lateral diffusion of AMPAR, reducing their numbers at the post-synapse. On the right side, we see an illustration of the processes during LTP. A high Ca2+ influx activates signaling cascades. Resulting in exocytosis of AMPAR and recruiting of AMPAR via lateral diffusion to the PSD. There phosphorylation of GluA1 subunits stabilizes their position in the slots. Overall increasing AMPAR numbers at the post-synapse. Adapted from (Vitureira and Goda, 2013).
1.3.1.2.1 LTP In 1973 Bliss and Lømo discovered that a brief stimulation of axonal fibers in a rabbit’s hippocampus is sufficient to significantly enhance the synaptic responsiveness measured as excitatory post-synaptic potentials (EPSPs) (Bliss and Lømo, 1973). This discovery reinforced Hebb's postulate of "Cells that fire together, wire together." leading to intense examination of LTP (Cooke and Bliss, 2006; Hebb, 1949; Neves et al., 2008). Experimentally there are several ways to induce LTP either via high-frequency axonal stimulation in field recordings or targeting the post-synaptic single-cell by injecting a depolarization current or pairing post-synaptic action potential firing with EPSP input to the cell. 1.3.1.2.1.1 Mechanism of LTP
LTP mechanisms of the excitatory glutamatergic synapse in the hippocampus are best understood. The LTP induction protocol in field recordings consists of high-frequency stimulation of the axons, for example two times 100 Hertz (Hz) for 1s. This stimulation burst leads to an increased release of glutamate at the pre-synapse. In baseline conditions, glutamate released is sufficient to activate the AMPAR present at the post-synapse leading to short depolarization and eliciting EPSPs. However, through the increased glutamate levels after LTP induction, more AMPAR are activated over a longer time-period depolarizing the cell further 45 than in baseline condition. Through this enhanced depolarization, the Mg2+ ion blocking the NMDAR is removed, and NMDAR become activated upon glutamate binding. Activation of NMDAR allows Ca2+ flux into the cell, which stimulates Calcium/calmodulin-dependent protein kinase II (CAMKII), activating an intracellular signaling cascade (see Figure 15). CAMKII phosphorylates a variety of targets, among them AMPAR. The addition of a phosphate group changes the conductance of AMPAR, increasing its depolarization abilities (Lisman, Yasuda, and Raghavachari, 2012; Lynch, Larson, Kelso, Barrionuevo, and Schottler, 1983). While NMDAR are necessary for induction, the central feature allowing the maintenance of LTP of synaptic strength is the increase of AMPAR at the post-synapse. AMPAR are present throughout the dendrites of the post-synaptic cell and can travel along the plasma membrane in a two-dimensional way. Activation of CAMKII creates 'slots' at the post-synapse anchoring AMPAR, thus increasing their presence and restricting their movement. Collectively, the post-synaptic modifications increase the sensitivity of the glutamate- dependent post-synaptic response, and a prolonged enhancement of EPSPs can be observed. This enhancement can last days, as observed in in vivo recordings (Ivanova et al., 2017; Moulin et al., 2019; O’Boyle, Do, Derrick, and Claiborne, 2004; Thiels, Xie, Yeckel, Barrionuevo, and Berger, 1996; Y. Zheng et al., 2010).
1.3.1.2.2 LTD LTD is the converse mechanism of LTP, helping to maintain a balance in the brain. While LTP represents a long-term increase in EPSPs amplitude, LTD represents a long-term reduction (depression) of EPSPs amplitude. The induction can occur in field recordings via repetitive low frequency 1 Hz stimulation lasting several minutes or with patch-clamping via injection of a weak depolarization current during low frequency synaptic stimulation. 1.3.1.2.2.1 Mechanisms of LTD
The process of LTD, like in LTP, is NMDAR dependent (Morris, Anderson, Lynch, and Baudry, 1986). The induction partially activates NMDAR, but to a lower degree than observed in LTP (Figure 15). How the NMDARs are involved precisely is unclear. The main hypothesis is that the small but prolonged influx of Ca2+ via the NMDAR during LTD induction activates phosphatases like calcineurin, leading to the dephosphorylation of AMPAR at the post-synapse, but other studies suggest that metabotropic actions NMDARs could occur for this type of plasticity process (Nabavi et al., 2013; Peineau et al., 2007).
46 Again, while NMDARs are necessary for LTD induction, the central feature allowing the maintenance of LTD of synaptic strength is the reduction of AMPAR numbers at the post- synapse, mainly through endocytosis. This reduction lowers the likelihood of a glutamate- dependent post-synaptic response and leads to reduced EPSPs amplitudes post-LTD-induction (Malenka and Bear, 2004; O’Riordan, Hu, and Rowan, 2018; Thiels et al., 1996).
1.3.1.3 Short-Term Synaptic Plasticity The dynamics of the pre-synapse are a critical factor in pre-synaptic plasticity. Depending on the neuron type, synapses can receive action potentials at a high rate like 100 Hz or bursts of action potentials with phases of no activity between them. These patterns of activity are dynamic and can strengthen or weaken the synapse. The number of neurotransmitters released by the pre-synapse depends on its history. Action potentials occurring in a short period leave an imprint on the synapse, influencing the number of neurotransmitters released for the following action potential. The timespan of short-term synaptic plasticity, like long-term synaptic plasticity, has no definite duration, but may last from milliseconds to hours. However, on the timescale of milliseconds to seconds, pre-synaptic plasticity is the dominant form. Other classes of pre-synaptic plasticity include post-tetanic potentiation, on a minute time scale, and long-term pre-synaptic plasticity lasting up to hours. These two mechanisms rely on complex synthesis cascades downstream from initiation. Facilitation and depression are the two main forms of short-term plasticity. They initiate an immediate response after the action potential and rely on the calcium level and available neurotransmitters (Fioravante and Regehr, 2011).
1.3.1.3.1 Facilitation Upon arriving at the pre-synaptic bouton, the action potential initiates Ca2+ influx at the pre- synapse, activating synaptic transmission, thus leading to depolarization at the post-synapse (Figure 16). The arrival of a second action potential within the timeframe of 20-200 milliseconds magnifies the Ca2+ influx, leading to increased neurotransmitter release. This increased level then enhances the post-synaptic response during the following stimulation. Within the 20-200 milliseconds between action potentials, the Ca2+ available within the pre- synapse reduces via different mechanisms. These can be the removal of Ca2+ through ion pumps, by binding to buffers within the pre-synapse or the fusion of Ca2+ to proteins that usher them away from the pre-synaptic ion gated calcium channels.
47 These mechanisms are still ongoing when the second action potential arrives. Therefore, with residual Ca2+ is still present at the pre-synapse, the mechanisms are not able to prevent the increase of Ca2+ levels again. Not having reached baseline conditions, this increase in Ca2+ levels reaches a higher peak compared to the peak of the first action potential. An increase of 20 % in Ca2+ levels at the pre-synapse is sufficient to double neurotransmitter release. This increase and the following chain reaction last less than a second, thus is best studied in the millisecond time scale (Fioravante and Regehr, 2011; Zucker and Regehr, 2002).
Figure 16 Schematic illustration of facilitation. RRP: readily releasable pool of vesicles, Cares: residual calcium (Fioravante and Regehr, 2011).
1.3.1.3.2 Depression Depression in short-term pre-synaptic plasticity describes a decrease in the post-synaptic response between two action potentials. A decrease in neurotransmitter release for the second action potential may be responsible for this effect. In this scenario, the first action potential initiated the majority of the vesicles at the pre-synapse to release their neurotransmitter content. As glutamatergic vesicle refilling takes longer than 20 milliseconds, the diminished vesicle depot releases fewer neurotransmitters upon the second action potential (Figure 17) (Fioravante and Regehr, 2011; Hori and Takahashi, 2012).
Figure 17 Schematic illustration of depression. RRP: readily releasable pool of vesicles (Fioravante and Regehr, 2011)
48 1.3.1.4 Synaptic plasticity reflects behavioral outcome The different forms of synaptic plasticity comprise the cellular phenomenon of behaviors. Numerous studies corelate alterations in plasticity and behavior, such as reduced LTP with memory deficits (Bliss and Collingridge, 1993; Neves et al., 2008; Whitlock, Heynen, Shuler, and Bear, 2006). For example, Gruart et al. showed LTP at the hippocampal CA3-CA1 synapse during acquisition of an associate eye blink task. When inhibiting LTP mice were no longer able to learn the association, indicating a crucial role for LTP in memory formation (Gruart, Muñoz, and Delgado-García, 2006). Behavioral studies are a distinct field, encompassing numerous protocols to study its different facets. The following chapter will give an overview of behavioral studies with the focus on memory.
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50 1.3.2 Behavioral Studies
A wide variety of biological fields use behavioral studies to confirm or reject various hypotheses stemmed from a consensus within their field or previous results. In many cases, this implies testing results obtained on a molecular, cellular, or regional level and submitting them to the organism to test if they withstand. These organisms can be from the animal kingdom like insects, rodents or primates, or be humans, or a combination of them. However, due to factors such as costs, space, availability, and possibilities to manipulate the organism, the majority of behavioral tests are done in rodents like mice and rats. Behavioral studies differ significantly in procedure and complexity, depending on the hypothesis to be tested. A specific question, either confirming or declining a hypothesis, can thus be answered in a single test, whereas more complex questions could need a series of different behavioral tests (Crawley, 2008; Crawley and Paylor, 1997; Moy et al., 2004). Especially alterations within the brain should include an examination of behavior, as it is the main output of this organ.
1.3.2.1 Experimental Design One of the main obstacles in behavior is reproducibility. The behavior of individuals can be affected by several environmental factors, such as season, housing, handling, or noise. Thus, minimizing any changes between and within test groups is crucial for obtaining robust results. Group sizing and composition is another essential factor. Depending on the phenotype, group sizes needed to obtain robust results vary. When analyzing genetically modified animals, between 10-20 animals per group are considered a sufficient number to detect moderate behavioral changes (Crawley, 2008). The composition of groups could be the inclusion of both genders and for genetically modified animals, the inclusion of heterozygote and homozygote groups. Factors to exclude groups are usually time, space, and financial limits.
1.3.2.1.1 Husbandry Ideally, groups have a homogenous background to minimize the environmental factors mentioned above. Thus, the best breeding strategy is the pairing of heterozygote animals, giving rise to homozygote, heterozygote, and wild type littermates. However, groups should arise from different breeding pairs to avoid mutations affecting the outcome. To combine different cohorts, the wild type animals between groups should not significantly differ (Crawley, 2008)
51 1.3.2.2 Behavior When conducting behavioral test batteries, the order of tests and inter-test intervals are crucial for the outcome. Stress levels can influence behavior, thus starting with a moderately stressful test is advisable. The order within test batteries should rank from least to most stressful experiments. To reduce the experimental stress on animals, breaks between the segments of test batteries are advised. Studies found no difference in performance for 1-2 days and a week as inter-test intervals. Thus, the shorter period is advisable to reduce the duration of the test battery (Paylor, Spencer, Yuva- Paylor, and Pieke-Dahl, 2006). The behavioral battery set up depends on the hypothesis. A combination of a minimum of three different tasks increases chances to detect alterations in cognition (Crawley, 2008). Ideally, a battery should contain a mixture of tests from the following fields: motor learning, operant learning, olfactory learning, spatial navigation tasks, aversive learning and recognition memory.
1.3.2.2.1 Spatial Navigation Tasks The complexity of spatial navigation tasks varies between tasks and, on occasions, can be altered within a task. For example, by the addition of a reversal phase or reduction of training trials. The modification of the number of daily trials allows the exposure of different alterations. A high number of daily trials enable the detection of impairments in learning, whereas a reduction of daily trials paired with an extension on days enables the detection for alterations in the acquisition. Types of spatial navigation tasks include Barnes maze, Morris water maze (MWM), and T- maze. Among them, MWM is probably the most extensively used task to detect spatial memory deficits. The complexity of MWM depends on numerous factors, like tank size, platform size, and training period. Due to the emersion of the mice in water and the setup, this test is considered stressful and should be near the end of a behavioral tests battery (Morris, 1984; Pitts, 2018; Sharma, Rakoczy, and Brown-Borg, 2010). The T-maze, on the other hand, utilizes the innate exploratory behavior of mice and elicits moderate stress levels. However, it is considered the most basic spatial task, having to choose between two arms (Gerlai, 2001; Lalonde, 2002).
1.3.2.2.2 Aversive Learning This task applies the conditioning towards unpleasant stimuli by measuring the freezing response during resubmission to the context. The retrieval is mainly hippocampus, and 52 amygdala driven. Contextual associations in these tasks increases hippocampus dependency. Through the aversiveness of the experience in these tasks, for example, the shocks applied during contextual fear conditioning (CFC), they are considered the most stressful experiments. Thus, they should be among the last tests performed in a behavioral test battery (Fanselow and Poulos, 2005).
1.3.2.2.3 Recognition Memory Tasks like Novel Object Recognition (NOR) or 3-chambers social interaction test can be used to test for recognition memory. Unlike MWM and CFC, these tasks do not depend on encoding and retrieval of unpleasant training events reducing the stress level considerably. They use mice's innate exploratory behavior towards novelty, making them one of the earlier tests in a behavioral test battery (Crawley, 2008; Tse et al., 2007; Vogel-Ciernia and Wood, 2014).
1.3.2.2.4 Anxiety As mentioned, stress can alter the behavioral outcome. However, this is not the only factor to be considered when choosing the organization of the battery of tests. Anxiety is another performance altering factor. Thus, it has been shown that mice could perform a Barnes maze task, while the increased anxiety prevented them from acquiring the platform location in an MWM task (Miyakawa et al., 2001). Common anxiety-related tasks comprise the Light-Dark box, Open-field, elevated plus-maze, or zero-maze. They incorporate an approach-avoidance conflict. Such as the explorative desire versus the drive for cover, like the light open compartment versus the dark closed one in the Light-Dark box. Furthermore, it is advisable to evaluate factors like locomotion, diurnal activity, and genetic background when conducting a physiological examination (Crawley, 2008). With these batteries of behavioral tests, one can evaluate the output of alterations observed in plasticity or on the molecular level. Furthermore, they can assist in defining a phenotype, with the results obtained contributing to verify a hypothesis, modify it, or even lead to new hypotheses on the physiopathological role of proteins.
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2. Objectives
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56 2. Objectives The rising consensus in the AD field is that the physiological role of APP and its proteolytic products need to be investigated further. Since the discovery of the η-secretase pathway in 2015, the role of η-secretase (MT5-MMP) has solely been studied in the AD context, without progress on Aη-α and Aη-ß (Baranger et al., 2017; Baranger, Marchalant, et al., 2016; Willem et al., 2015). My first objective was to further investigate the impact of elevated Aη levels on synaptic plasticity mechanisms at excitatory hippocampal neurons. Willem et al., 2015, described that recombinant Aη-α impairs LTP, whereas Aη-ß showed no effect. We started by looking into the pertinence of post-translational modifications and concentrations on the capacity to impair LTP. We then proceeded to explore the impact of Aη-α on LTD and short-term plasticity. Furthermore, using novel transgenic mouse lines, MISEPA2 and MISEPA4, we explored the ability of chronic overexpression of Aη-α to alter long-term and short-term synaptic plasticity mechanism. My second objective was to study the behavioral outcome of these acute and chronic elevated Aη-α levels in the brain. It is reasonable to suggest that the An-α mediated impairment in LTP, as observed in (Willem et al., 2015), could be associated with deficits in memory formation. Thus, we hypothesized that we should observe performance deficits in memory dependent tasks when elevating Aη-α levels in vivo. We used stereotaxic intracranial injections of M108, the synthetic Aη-α, into the CA1 hippocampal region or lateral ventricle, to acutely increase the levels of this peptide in vivo and tested its impact on different memory tasks. For chronically elevated Aη-α levels, we utilized the MISEPA2 and MISEPA4 transgenic mouse lines overexpressing An-α. My third objective was to examine how the absence of the η-secretase processing of APP might alter long-term and short-term hippocampal synaptic plasticity mechanism, and how it might influence cognition. For this, a novel knock-out mouse line, the APPΔEta line, containing a deletion of the η-secretase recognition site on APP, was used. This mouse line allowed us to study how a reduction of η-secretase-processed APP products in heterozygote offspring and a total absence in homozygote offspring could influence plasticity mechanism and cognition. Due to the novelty of this strategy, behavioral battery testing was directed towards phenotyping. The overarching aim of my thesis was to further unravel the role of the η-secretase pathway, with the focus on its proteolytic product Aη-α, in a physiological context.
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58
3. Material and Methods
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60 3. Material and Methods
Animal Model
3.1.1 Acute Effects of Aη on Synaptic Plasticity in Electrophysiology Field Recordings
Male RjOrl:SWISS mice (Janvier Labs, France) aged 5-10 weeks were housed in groups of 4- 5 animals per cage in our behavioral housing facility until used for experiments.
3.1.2 Acute Effects of Synthetic Aη-α Injections into the CA1 Hippocampal Region or Lateral Ventricle
5-weeks-old male C57BL/6JRj mice (Janvier Labs, France) were housed in the behavioral housing facility for one week to acclimate before undergoing surgery. Animals resided in either: a) groups of 5 animals per cage for CA1 hippocampal injections or b) groups of 3 animals per cage for lateral ventricle injections.
3.1.3 MISEPA2: A Transgenic Mouse Line Overexpressing Aη-α in the Brain
MISEPA2 mice are a transgenic mouse line with overexpression of Aη-α in the brain (Table 2). The cDNA of human Aƞ-α was cloned into a 5.2 kilo base (kb) pSec.2A vector. This vector is designed for high-level stable expression with the protein of interest fused to an Immunoglobulin (Ig) kappa (k)-chain leader sequence at the N-terminus. The Ig k-chain allows for the secretion of the protein. Together they were transferred via SalI and XhoI into the XhoI site at position 3920 of pTSC, a plasmid used to introduce the tagged Aƞ-α gene into the target cells (Figure 18). Specific neuronal expression of the gene was assured due to the Thy1.2 expression cassette, allowing reliable expression restricted to neurons in the peripheral and central nervous system (Figure 20). Furthermore, as the onset of gene expression under this cassette is around P6-12 no interference with early nervous system development is ensured.
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Figure 18 Representation of the pSec.2A plasmid expressing Aη-α. This plasmid was used to introduce the Aƞ-α cDNA into the embryonic stem cells.
MISEPA2 mice used in this study came from two different cohorts. The first cohort consisted of mice sent to us prior to behavior testing by collaborator and creator of the line, Dr. Willem, LMU Munich, Germany. The second cohort consisted of offspring bred in-house from founder couples donated to us by Dr. Willem. These couples consisted of a transgenic male paired with two C57BL/6JRj females (Janvier Labs, France). Both males and females were used in this study and tested against their wild type littermates as control group aged 3-6 months.
3.1.4 MISEPA4: A Transgenic Mouse Line Overexpressing Aη-α in the Brain with an Elevated Expression Level Compared to MISEPA2 Line
The transgenic MISEPA4 mice line was created the same way as the MISEPA2 line described in the previous paragraph using the cDNA of human Aη-α. This mouse line has a higher human Aη-α expression throughout the brain when compared to the Aη-α levels observed in the MISEPA2 line (Table 2). Mice used in this study came from a single cohort send by our collaborator and creator of the line, Dr. Willem, LMU Munich, Germany. Both males and females were used and tested against wild type littermates as control group. All mice were tested at 2-3 months.
3.1.5 APPΔEta: A Mouse Model Without η-Secretase Processing of APP due to Deletion the Enzymatic Recognition Site on APP
In the APPΔEta mice, our collaborator and creator of this line, Dr. Willem, LMU Munich, Germany, deleted the recognition sequence for the η-secretase on the APP protein using the Crispr/Cas9 technique as described in (Vazquez et al., 2018) (Table 1). The mice were crossed back to a C57BL/6J (Charles River, France) background.
62 Table 1 Deletion of 41 amino acids (blue) containing the ƞ-secretase recognition site (orange) on APP.
APP region ELL QKE QNY SDD VLA NMI SEP RIS YGN DAL MPS LTE TKT TVE LLP VNG EFS DDL QPW HPF GVD SVP ANT ENE
The deletion of this site prevented processing of APP by η-secretase (Figure 19). This inhibits the production of all peptides normally generated within this pathway, including CTF-η, Aη-α and Aη-ß.
Figure 19 APPΔEta mice harbor the endogenous APP protein with deletion of ƞ-secretase recognition site. The deletion of 41 amino acids ensures that the ƞ-secretase cannot cut APP thus preventing its processing via the ƞ-secretase pathway.
63 3.1.1 Immunofluorescence and Western Blot Verify Expression of Aη-α in MISEPA2 Mice and Absence of Aη-α in APPΔEta Mice
Western blots of brain lysates of the MISEPA4 line showed an evaluated Aη-α expression compared to the MISEPA2 line (Table 2). Immunofluorescence imaging verified Aη-α expression in the whole hippocampus as shown in Figure 20. The absence of Aη-α in APPΔEta mice and presence of recombinant human Aη-α in MISEPA2 mice was verified in Western blots as shown in Figure 21. All Immunofluorescence and Western blot analysis for expression verification was done by our collaborator Dr. Willem, LMU Munich, Germany.
Table 2 Comparing MISEPA2 and MISEPA4 and their respective Aη-α expression levels in different brain areas. Whole brain expression was verified by Western blot (WB) analysis of brain lysates. Expression of Aƞ-α in distinct brain areas was verified through immunofluorescence (IF).
Line Whole brain Cortex (IF) Hippo (IF) Cerebellum (IF) (WB) MisepA2 ++ ++ + (only CA1) ++ MisepA4 +++ +++ + +++
Figure 20 Immunofluorescence images confirming expression of Aƞ-α in different brain regions. The antibodies used are Hoechst (blue) staining DNA, NeuN (green) recognizing the neuron specific protein NeuN, and 2E9 (red) recognizing multiple isoforms of APP via targeting a sequence of 11 amino acids at the C-terminal. Data provided by Dr. Willem, LMU, Germany.
64
Figure 21 Western blots confirming absence of endogenous Aƞ-α in APPΔEta mice and presence of recombinant human Aƞ-α in MISEPA2 mice. Deletion of the ƞ-secretase recognition side in APPΔEta is shown by the absence of Aƞ-α. MISEPA2 mice recombinant Aƞ-α was detected with human specific antibody in MISEPA2 mice. Data provided by Dr. Willem, LMU, Germany.
3.1.2 Housing Conditions
Animals were housed under controlled laboratory conditions with a 12 h dark-light cycle, a temperature of 22 ± 2 °C and access to food pellets and water ad libitum. Breeding of mouse lines MISEPA2 and APPΔEta was performed in our pathogen free animal facility. Animals of all cohorts were moved at least a week prior to behavior testing into our behavioral housing facility. If not stated differently animals were group housed with 5 animals per cage.
3.1.3 Genotyping
The genotype of each animal bred in our facility was determined through DNA purification of tail or toe clip biopsies followed by gene targeted polymerase-chain reaction (PCR). Biopsies were obtained when animals were weaned around P21 and stored at -20 °C until used for lysis.
3.1.3.1 Lysis 100 µl of Rapid Lysis Buffer (0.2 mM EDTA pH 8 and 25 mM NaOH) was used to digest the biopsies for an hour at 95 °C. Immediately afterwards, the tubes were cooled on ice and 100 µl Neutralizations Buffer (40 mM Tris-HCl) added to halt the reaction.
65 3.1.4 Polymerase-Chain Reaction Protocol for MISEPA2 and MISEPA4 Mouse Line
2 µl of the MISEP biopsy lysates were used to amplify their DNA through PCR. A PCR master mix was prepared including the forward and reverse primers for the Aη-α transgene of interest named ‘MISEP’ as well as the forward and reverse primers for myosin, acting as a control for DNA quantity in each probe (see Table 4) Additionally to the biopsy probes three controls were used to validate the results of the PCR performed: 1. A negative control (−) containing DNA only positive for the myosin primer, 2. a positive control (+) containing DNA positive for both primers, myosin and ‘MISEP’, and
3. a control consisting of the water (H2O) used for the PCR master mix to verify that the water used for the PCR was not contaminated with DNA. The master mix was made up as shown in Table 3 and an additional 10 % pipetting error rate calculated to ensure enough mix for all probes and controls. The following PCR program was used: 1. 5 min denaturation of DNA at 95 °C 2. Followed by 10 cycles of the first amplification: a) 94 °C for 30 sec, b) 62 °C for 30 sec and c) 72 °C for 30 sec. 3. The second amplification consisted of 24 cycles with the following settings: a) 94 °C for 30 sec, b) 52 °C for 30 sec and c) 72 °C for 90 sec. 4. A final elongation step at 72 °C for 7 min was performed before the temperature was lowered to 10 °C until the tubes were removed.
66 Table 3 content of the MISEP PCR master mix.
Water 12.37 µl GoTaq Buffer 5x 5 µl MISEP Primer fwd. (10 µM) 1.25 µl MISEP Primer rev. (10 µM) 1.25 µl Myosin Primer fwd. (10 µM) 1.25 µl Myosin Primer rev. (10 µM) 1.25 µl dNTP 0.5 µl GoTaq Polymerase 0.13 µl
total 23 µl
Add 2 µl DNA
Table 4 Primer sequence of Myosin and MISEP used in the PCR master mix
Primer Sequence Myosin forward CCA AGT TGG TGT CAA AAG CC Myosin reverse CTC TCT GCT TTA AGG AGT CAG MISEP forward CGC GCC ATG ATTAGT GAA MISEP reverse GAC CTC TGC AGA GGA AGG A
3.1.5 Polymerase-Chain Reaction Protocol for APPΔEta Mouse Line
2 µl of the APPΔEta lysate is used to amplify the DNA in a PCR. The PCR master mix contains the forward and reverse primers for the APPintron (see Table 6). As the APPΔEta mice have the deletion of the η-secretase recognition sequence the position of the band indicates the genotype as seen in Figure 23. A wild type mice has the full-length APP protein on both chromosomes and therefore a band with a base pair (bp) count around 510 bp. A homozygote APPΔEta mice has the deletion occurring on both chromosomes and a lower band at 387 bp, while the heterozygote APPΔEta mice has a copy of each APP protein and therefore two bands, one at 510 bp and one at 387 bp. Therefore, we used 4 controls, three representing the genotypes wild type (WT), homozygote (−/−) and heterozygote (+/−) APPΔEta, and the fourth control consisting of the water (H2O) used for the PCR master mix to verify that the water used for the PCR was not contaminated with DNA. The master mix was made up as shown in Table 5 and an additional 10% pipetting error rate calculated to ensure enough mix for all probes and controls. The following PCR program was used:
67 1. 3 min denaturation of DNA at 95 °C 2. Followed by 35 cycles of the first amplification: a) 95 °C for 30 sec, b) 60 °C for 30 sec, and c) 72 °C for 45 sec. 3. A final elongation step at 72 °C for 4 min was performed before the temperature was lowered to 10 °C until the tubes were removed.
Table 5 content of the APPΔEta PCR master mix
Water 37.25 µl GoTaq Buffer 5x 10 µl APPintron11-12 Primer fwd. (100 µM) 0.25 µl APPintron12-13 Primer rev. (100 µM) 0.25 µl dNTP(10 nM) 1 µl GoTaq Polymerase 0.25 µl
total 49 µl Add 1 µl DNA
Table 6 Sequences of Primers used in APPΔEta PCR master mix
Primer Sequence APPintron11-12 forward AAG CTC TGA CTT TCC TTA AGG TGC APPintron12-13 reverse TAG GAG TGG TAT CCC TGC GGG T
3.1.6 Gel Electrophoresis
The PCR products were visualized on 2 % agarose gels (50 ml 1xTAE with 1 gr agarose) with 2 % ethidium bromide under UV light. The gel was loaded with either 15 µl of the MISEP PCR samples or 5 µl of the APPΔEta PCR samples. For identification of bands 5 µl of a 100 bp DNA ladder was added. The gel ran at 80-120 V for approximately 20 min. As seen in Figure 22 the band for Aη-α in the MISEP PCR samples runs at 360 bp and the band for myosin at 170 bp.
68
Figure 22 Gel showing the bands to be expected by the MISEP PCR samples. If Aƞ-α is present indicated by the red arrow and the control band for DNA quantity showing myosin by the yellow arrow. Also shown are the three controls: (+) showing bands for Aη-α and myosin, (−) showing only the band for myosin and H2O containing no DNA and therefore showing no band.
For the APPΔEta PCR samples the different bands depending on the genotype are easily distinguishable with the WT running at 510 bp, −/− at 387 bp and +/− having two bands at 510 bp and 387 bp as seen in Figure 23.
Figure 23 Band options for the APPΔEta PCR samples. The homozygote probe (−/−) has one band at 387 bp, the WT one (+/+) at 510 bp. Whereas the heterozygote (+/−) has a copy of each and therefore two bands one at 387 bp and 510 bp.
69 Electrophysiology
To investigate alterations in synaptic plasticity under the influence of Aη-α we performed field recordings in the hippocampus at the CA3-CA1 synapse (Figure 24). As described below, different protocols were applied to differentiate between alterations in short-term and long-term plasticity. We studied function and synaptic plasticity mechanisms with acute application of synthetic Aη-α (M108) and Aη-β (M92) peptides in RjOrl:SWISS mice. We also studied the chronic effects of Aη-α accumulation on these mechanisms in the MISEPA2 mouse line.
Figure 24 Field recordings at the hippocampal CA3-CA1synapse were performed to investigate alterations in synaptic plasticity in our experiments. fEPSP: field excitatory post-synaptic potential
3.2.1 Peptides
The synthetic Aη-α (M108) and synthetic Aη-β (M92) amino acid sequences were purchased from Peptide Specialty Laboratories (PSL; Heidelberg, Germany) as previously described in (Willem et al., 2015) (Table 7). The peptide was dissolved in dimethyl sulfoxide (DMSO) at 100 µM and stored in 20 µl aliquots at -80 °C. On the day of experiment, it was further diluted in artificial cerebrospinal fluid (aCSF) to the required concentration (1-10 nM) before use.
Table 7 Amino acid sequence of synthetic proteins ordered
Peptide Amino acid sequence Synthetic Aη-α MIS EPR ISY GND ALM PSL TET KTT VEL LPV NGE FSL DDL QPW HSF GAD (M108) SVP ANT ENE VEP VDA RPA ADR GLT TRP GSG LTN IKT EEI SEV KMD AEF RHD SGY EVH HQK Synthetic Aη-β MIS EPR ISY GND ALM PSL TET KTT VEL LPV NGE FSL DDL QPW HSF GAD (M92) SVP ANT ENE VEP VDA RPA ADR GLT TRP GSG LTN IKT EEI SEV KM
70 3.2.2 Solutions
Throughout the study different solutions were used to acclimate the hippocampi after dissection and slicing, or to maintain their vital status throughout the day and during recordings. The cutting solution (Table 8) was prepared fresh before each experiment and kept cold in an ice bath while constantly being oxygenated (95 % O2/ 5 % CO2).
Table 8 Ingredient list of the cutting solution with their respective concentration (Marie, Morishita, Yu, Calakos, and Malenka, 2005)
Sucrose 234 nM KCl 2.5 nM
NaH2PO4 1.25 nM
MgSO4, 10 nM
CaCl2 0.5 nM
NaHCO3 26 nM Glucose (pH 7.4) 11 nM
We used two different types of aCSF depending on the experiment. If not otherwise stated, aCSF referred to the solution named aCSFI, consisting of the same ingredients at different concentrations as aCSFII (for comparison see Table 9 and Table 10).
Table 9 aCSFI solutions ingredient list with their respective concentration
aCSFI NaCl 119 mM KCl 2.5 mM
NaH2PO4 1.25 mM
MgSO4 1.3 mM
CaCl2 2.5 mM
NaHCO3 26 mM Glucose 10 mM
71 Table 10 aCSFII solutions ingredients list with their concentration. As described in (Townsend, Shankar, Mehta, Walsh, and Selkoe, 2006).
aCSFII NaCl 124 mM KCl 2.8 mM
NaH2PO4 1.25 mM
MgSO4 2 mM
CaCl2 3.6 mM
NaHCO3 26 mM Glucose 11 mM
For LTD recordings, Picrotoxin was added at 50 µM to either of the aCSF solutions perfusing the slices in the recording chamber.
3.2.3 Harvesting and Slicing of Mice Hippocampi
To harvest the brains, mice were culled via by cervical dislocation and immediately afterwards decapitated to perform brain dissection. A pair of straight iris scissors was used to make an incision along the midline of the skull from the neckline to the nose, removing the integument and exposing the skull. The tip of a curved iris scissor was carefully inserted into the foramen magnum, cutting left and right, before carefully cutting along the midline of the skull towards the distal frontal edge to not damage the brain tissue. Forceps were used to peel the skull away from the brain. When the brain laid free, gentle usage of a spatula teased the brain away from the head, trimming away any dura still connecting the brain to the skull as well as nervous connections along the ventral brain surface. The brain was placed gently on filter paper and a scalpel and spatula were used to dissect the hippocampi. The scalpel cut the brain into two halves along the midline and two spatulas were used to disclose the hippocampus between the cortex and the striatum. A spatula was then used to dissect out the hippocampus and quickly place it in ice-cold oxygenated
(95 % O2/ 5 % CO2) cutting solution for 5 min incubation time. The hippocampi were then gently embedded in Agar molds to fixate them for cutting on a vibratome (Microm HM600V, Thermo Scientific, France) into 350 µm slices. For recovery, slices were then incubated in oxygenated aCSF for 1 h at 37 ± 1 °C and afterwards stored at room temperature as described in (Marie et al., 2005).
72 3.2.4 Rig Set-Up
Recordings for all experiments were done at 27 °C ± 1 °C in a recording chamber on an upright microscope with IR-DIC illumination (Slicescope, Scientifica Ltd, UK). During recordings slices were perfused with oxygenated aCSF solution, with or without the respective peptide as mentioned in the Result section. Field recordings were performed using a Multiclamp 700B amplifier (Molecular Devices, UK), under the control of pClamp10 software (Molecular Devices, UK).
3.2.5 Field Recordings
Field excitatory post-synaptic potentials (fEPSPs) were recorded in the stratum radiatum of the CA1 region using a glass electrode filled with 1 M NaCl and 10 mM 4-(2-hydroxyethil0-1- piperazineethanesulfonic acid (HEPES) (pH 7.4). The stimuli were delivered to the Schaffer collateral pathway by a monopolar glass electrode filled with aCSFI. Electrodes were placed superficially to maximize exposure to peptides. fEPSP response was set to approximately 30 % of the maximal fEPSP response i.e. approx. 0.2-0.3 mV, with stimulation intensity 10 µA +/- 5 µA delivered via a stimulation box (Isoflex, AMPI, Israel).
3.2.5.1 Long-Term Synaptic Plasticity Recordings Before application of long-term induction protocols, a stable baseline of 20 min was recorded. As mentioned above, slices were bathed in aCSF either in control condition, or with the peptide. Picrotoxin (50 µM) was added depending on the protocol. Throughout the recordings for long- term plasticity, the solution was recirculated. We looked at different forms of long-term plasticity: LTP, LTD and an intermediate LTD stage called sub-LTD, which in control conditions is not sufficient to induce an LTD response. LTP was induced by a high frequency stimulation protocol consisting of 2 pulses at 100 Hz for 1 sec with a 20 sec inter stimulus interval (ISI). Sub-LTD was induced by low frequency stimulation consisting of 300 pulses at 1 Hz. LTD was induced with a train of 900 pulses of 1 Hz in presence of 50 μM Picrotoxin. After induction, recording continued for an hour to observe the long-term synaptic plasticity changes and compare alterations in response between control conditions and presence of the peptide or in mutant conditions. The first third of the fEPSP slope was calculated for analysis of fEPSPs. The time courses of LTP and LTD were obtained by normalizing each experiment to the average value of all points of the last 20 min stable baseline before induction. In bar graphs, LTP or LTD magnitude was measured during the last 15 min of recording (45–60 min
73 after induction) and calculated as percentage change fEPSP slope from baseline average. Recordings alternated between control and testing conditions throughout the day for acute effects with sAƞ-α or between days for testing the MISEPA2 line.
3.2.5.2 Short-Term Synaptic Plasticity Recordings To test for alterations in short-term synaptic plasticity we applied three different protocols to look at different facets of short-term plasticity.
3.2.5.2.1 Paired-Pulse Ratio The paired-pulse ratio (PPR) characterizes alterations for the probability of release at the pre- synapse. The PPR protocol consists of two stimuli delivered ranging from 100 to 400 ms ISI, if not stated otherwise in Results. PPRs were calculated as fEPSP2slope/fEPSP1slope (10 sweeps average per ISI).
3.2.5.2.2 Synaptic Fatigue Synaptic fatigue exploits the fact that if stimulation is occurring at a high enough frequency, the neurotransmitter release will be at a faster rate than the re-uptake cycle ultimately leading to reduced transmitter release, a characteristic of synaptic fatigue. Thus, synaptic fatigue can measure alterations in release probability and neurotransmitter depot under drug the different conditions. Synaptic fatigue was measured via a stimulation protocol consisting of a train of 15 pulses at 40 Hz. Measurements of all fEPSPs were normalized to the first fEPSP of the train for statistical analysis.
3.2.5.2.3 Input/ Output The Input/ Output (I/O) curve protocol measures basal synaptic transmission. We controlled the pre-synaptic input by setting the fiber volley (FV) amplitude and measured the post-synaptic response to this input. The I/O curves were generated by calculating the initial slope of the fEPSP to avoid population spike contamination with a corresponding FV amplitude ranging from 0.1 to 0.4 mV or 0.1 to 0.3 mV in increments of 0.1 mV measuring 10 sweeps average. The protocol was performed twice, first under aCSFI condition and then again after slices were perfused for 20 min in aCSFI with peptide or, serving as within subject control, in aCSFI without peptide. Recordings of control and peptide conditions for all experiments were interleaved within the same day.
74 Acute M108 Injection
3.3.1 Surgery
Mice underwent stereotaxic surgery at 6 weeks of age using a stereotaxic frame (Kopf Instruments). They were anaesthetized either with Intraperitoneal (i.p.) injections of a Xylazine/Ketamine from Centravet (France) mix diluted in 4 ml Saline (0.9 % NaCl) (7.5 mg/kg and 11.25 mg/kg, respectively) or 2.5-3 % isoflurane saturated air. After head fixation with ear bars (Kopf Instruments) the animal’s head was shaved, and the eyes covered with CELLUVISCR eye drops (ALLERGAN) to prevent eye dehydration. The operation area was disinfected with 70 % ethanol and Vetadine (Vétoquinol) (both three times alternating). The skin was opened up with a scalpel and the skull scraped to remove excess tissue. To aid adhesion a fishbone pattern was scraped onto the skull before drilling. For the double cannula guide (Bilaney Consultants, Plastic One) implantation into the CA1 hippocampal region the following drilling coordinates with respect to Bregma were used: −2.2 mm anteroposterior (AP), ±1.5 mm mediolateral (ML) and −1.3 mm dorsoventral (DV) (Figure 25). The implanted cannula guide was secured by three screws (two anterior and one posterior to the cannula position) and additionally fixated with dental cement (Bilaney Consultants, Plastic One). For the single cannula guide (Bilaney Consultants, Plastic One) implantation into the lateral ventricle the coordinates −0.5 mm AP, ±1.1 mm ML and −2.5 mm DV with respect to Bregma were used (Figure 25). Due to the more anterior location of the cannula guide only one anterior or one anterior and one posterior screw were used for additional fixation with the dental cement. Anatomical coordinates were taken from Paxinos and Watson’s mice brain atlas (Paxinos and Watson, 1998).
75
Figure 25 The two different types, single and bilateral, cannula guides used for injections of M108. Shown on the left is the single cannula guide with the injection side into the lateral ventricle. The bilateral cannula guide shown on the right was used to inject directly into the CA1 hippocampal regions. Stars on the images mark sites of injection.
The dental cement used was a mix of DENTALONR plus powder and liquid (Bilaney Consultants, Plastic One) freshly prepared before application. If needed skin at the neck area was sewed close with FILAPEAU 4/0 (Péters SURGICAL) after the cement dried. Post-operational care included a saline i.p. injection, 20 mg Carpox vet tablets (KRKA) diluted in the home cage water bottle for pain relief as well as checkups every other day during the 1- 2 weeks recovery phase and wound treatment with Vetadine if necessary. If animals removed cannula guide dummies after the operation, they were replaced upon notice.
3.3.2 Injection Volume and Concentration
We decided to inject 0.5 µl M108 at 0.2 µl/ min for the bilateral injections into the CA1 region of the hippocampus, which is comparable with volume mentioned in literature for injections of peptides into hippocampal regions (Rosenling, 2010; Rudick, Zirretta, and Herndon, 1982). A final concentration of 500 ng M108 (84 µM) was used to enhance the chances of an effect, as the distribution of M108 post-injection throughout the hippocampus is unknown and to enhance the effect of local elevation of M108 levels on behavioral alterations that may occur. As for injections into the right lateral ventricle we increased the injected volume to 5 µl at 0.5 µl/ min as we had to consider the dilution of M108 in ventricle CSF. Literature suggests that the volume of ventricle CSF can be estimated as 40 µl with a turnover rate of 0.325 µl/ min (Badea, Ali-Sharief, and Johnson, 2007; Rosenling, 2010; Rudick et al., 1982). The final concentration of sAƞ-α was calculated as follows: 84 µM 5 µl injection Volume final sA concentration in the brain = 40 µl CSF volume sAƞ − α ∗ η − α
76 This would, by disregarding the turnover rate, dilute our injected 5 µl of 84 µM M108 to a final concentration of approximately 10 µM M108 in 40 µl aCSFI, which is the concentration of M108 worked with in our Electrophysiology experiments.
3.3.3 Verification of Injection Site and Distribution of M108
3.3.3.1 Microscopy imaging for injection side in bilateral hippocampal injections To be sure that injection of sAƞ-α reached target region, injection sites were verified post- mortem after termination of behavioral experiments. Mice were killed by cervical dislocation and immediately their whole brain harvested as described above. Great attention was directed towards harvesting the whole brain without damage of tissue. Brains were stored overnight in 4 % formaldehyde (PFA) solution for tissue fixation. The next day solution was exchanged to 0.1 M Phosphate buffer (PB) solution and brains kept cold in a fridge until further processing. Brains were precut in a mouse brain mold and sliced at 40 µm with a vibratome (Microm HM600V, Thermo Scientific) in cold 0.1 M PB solution. After mounting brain slices on microscope slides, images were taken with an DMD108 Leica microscope to verify injection site.
3.3.3.2 Blue Evans Staining to Verify Correct Placement of Canula Guides and Distribution after Injection Blue Evans dye was the first method used to verify the correct distribution of M108 in the brain and ventricle via the cannula guides to the designated area, either hippocampal CA1 region or right ventricle (see Figure 25). Mice were anesthetized with Ketamine/Xylazine i.p. (150 µl/ 20 gr bodyweight: 750 μl Ketamine and 250 μl Xylazine in 4 ml saline) injection as preparation for the following perfusion and connected to the injector. 0.3 µl blue Evans at 0.2 µl/ min was injected. This lower volume compared to M108 injections in the actual experiments is due to experience in our laboratory, as blue Evans tends to distribute quickly.
3.3.3.2.1 Perfusion Surgery Before starting perfusion surgery, we confirmed surgical plane of anesthesia by use of toe pinch-response method. Perfusion was performed under the hood due to the toxic 4 % PFA solution used. Both the 4 % PFA and 1x phosphate buffered saline (PBS) (PBSx10 Euromedex diluted in
H2O) acting as perfusion buffer are stored on ice, the fixative tubing connected to a pump (Drifton) was placed in the perfusion buffer container and carefully filled to avoid air bubbles
77 and a fresh needle (AGANITMNEEDLE 26Gx ½” (0.45x 13 mm), Terumo®) was placed on the outlet and put aside until needed. Animals were placed on a polyester platform and pinned down with four needles into the limbs, stretching the body out. A small lateral incision just beneath the rib cage cutting through the integument and abdominal wall was made. The diaphragm was cut, and the incision further enlarged by cutting carefully along the rib cage up to the collarbone on both sides to expose the pleural cavity. The sternum was lifted away and fixed next to the head with a needle. The exposed heart was carefully freed from connective tissue. Blunt tweezers were used to position the heart for needle insertion. The needle connected to the fixation tubing was inserted into the posterior end of the left ventricle taking care to not damage the heart (Figure 26). Finally, while keeping the needle stable, an incision to the right atrium using iris scissors was made to create an outlet.
Figure 26 Schematic illustration of perfusion surgery. Taken from (Gage, Kipke, and Shain, 2012).
3.3.3.2.2 Perfusion The pump was switched on transporting the fixation buffer through the tubing into the heart, replacing the blood in the mice. A first indicator for a good perfusion process was the clearing of the liver. Once the liquid leaving the incision made at the atrium became clear too, the tubing inlet was quickly changed from the container containing the perfusion buffer to 4 % PFA to start the fixation process. Within seconds of the 4 % PFA entering through the heart fixation tremors should be observed. After passing 5 min of 4 % PFA the fixation was finished. The mice should be stiff at this moment and the brain ready to be harvested. After fixation we immediately harvested the full brain and depending of injection into ventricle or hippocampus made directly pictures of the full brain (unilateral ventricle injection) or stored the brains overnight in 4 % PFA (bilateral hippocampus injection). The next day solution was exchanged
78 to 0.1 M PB solution and brains kept cold in a fridge until further processing. As described in Microscopy imaging for injection side in bilateral hippocampal injections, we precut the brains in a brain mold and sliced them with a vibratome for mounting on microscope slides and imaging of blue Evans staining in the hippocampus.
3.3.3.3 Western Blot The second method used to verify distribution and analyze the half-life of M108 in the brain was Western blotting. For this experiment, we injected M108 as described above either for hippocampal or ventricle injection and sacrificed mice after the predefined time points post- injection described in Table 11. For time point 0 min we did not inject M108 and these values acted as baseline measurements.
Table 11 Time points to sacrifice mice post-injection of M108.
Time point post -injection Ventricle injection/ unilateral Hippocampal injection/bilateral 0 min Yes Yes 10 min Yes Yes 1h Yes Yes 24 h _ Yes
3.3.3.3.1 Brain Harvesting and Storage Mice were culled via cervical dislocation, their brains harvested similar to described above in brain harvesting for electrophysiology. The difference was that despite hippocampus, we also harvested the cerebellum, the cortex and the striatum divided by hemispheres. Furthermore, we immediately snap froze collected brain parts in liquid nitrogen and stored them at -80 °C until further use.
3.3.3.3.2 RIPA Extraction Protocol Precellys® tubes with ceramic beads (Bertin Instruments) were put on ice and the hippocampus hemisphere placed in them. We added 250 µl RIPA buffer (Table 12), with the PI mix (P8340- 1M SIGMA-ALDRICH) and EDTA (0.5 M, 8 pH) before placing them in the Precellys® homogenizer (Bertin Instruments) for a 30 sec cycle of 6500 rpm at 4 °C. The homogenate was then placed in a centrifuge and spun at 3000 g for 10 min at 4 °C. We continued working with the supernatant, containing the proteins, after verifying concentration of M108 with Bradford assay.
79 Table 12 composition of RIPA buffer
1x RIPA buffer Tris-HCl (7.5 pH) 20 mM NaCl 150 mM
Na2 EDTA 1 mM NP-40 1 % Sodium deoxycholate 1 % Sodium pyrophosphate 2.5 mM
3.3.3.3.3 Immunoblotting 20 µg of protein extracts were resuspended in 5 µl 4x loading buffer and were boiled at 95 °C for 5 min. They were then immediately put on ice. After a quick spin 20 µl of the protein were loaded on either a 12 % polyacrylamide gel and resolved by sodium dodecyl sulfate- polyacrylamide gel electrophoresis (SDS-PAGE) in a Tris-glycine buffer with 0.1 % SDS or on a commercially available NOVEXTM 10-20 % Tricine gel (ThermoFisher) in 1x Tricine buffer (ThermoFisher) at 100 V. Proteins were transferred at 4 °C onto a nitrocellulose membrane in ice-cold transfer buffer (Tris-glycine, 0.1 % SDS, 20 % ethanol) at 400 mA for 1.15 h. Afterwards, we rinsed the membrane in PBS 1x and blocked with blocking solution for 1 h at room temperature, while shaking. The membrane was immunoblotted with the primary antibody Rat anti 2D8 (1:1000) in Tris buffered saline with Tween 20 (TBST)-5 % milk overnight at 4 °C under agitation. The following day, the membrane was rinsed at least 3 times in TBST for 10-15 min each time under agitation. Next, we incubated the membrane with the anti-Rat horseradish peroxidase (HRP)-conjugated secondary antibodies (1:50000; GE Healthcare) in TBST-5 % milk at room temperature for an hour under agitation. After washing the membrane thoroughly like the previous time, proteins were then revealed using the Pierce ECL Western Blotting Substrate (ThermoFischer) chemiluminescent solutions. Images were acquired on a Fusion FX7 system (Vilber Lourmat).
80 Table 13 Loading buffer composition
Loading buffer Tris-HCl (6.8 pH) 230 nM SDS 6.85 % Glycerol 24 % Bromophenol blue 0.008 % β-mercaptoethanol 5 % Dithiothreitol (DTT) 5 %
Table 14 Blocking solution composition
Blocking solution 0.1 PBS 0.2 % Tween
Table 15 Separation Gel and Spacer gel recipe
Separation-Gel 12 % Spacer-Gel
1.5 mm 2x 1x 1.5 mm 2x 1x
H2O 9 ml 4.5 ml H2O 4 ml 2 ml
Acrylamide 40 % 6 ml 3 ml Acrylamide 40 % 500 µl 250 µl
4x Lower Tris 5 ml 2.5 ml 4x Upper Tris 1.3 ml 650 µl
TEMED 40 µl 20µl TEMED 20 µl 10 µl
APS (10 %) 40 µl 20 µl APS (10 %) 20 µl 10 µl
81
82 Behavioral Testing
Throughout this study we performed a series of behavioral testing. The testing groups were: a) M108 injected mice, b) transgenic MISEPA2 mice, c) transgenic MISEPA4 mice, and d) knock-out APPΔEta mice. As described in the introduction each behavioral task tested different aspects of memory, sociability or behaviorism and was designed to reveal alterations in performance under the influence of Aη or in its absence. For each batch of mice tested, the order of the tasks was fixed. However, in some lines we performed only one set of tasks per batch due to the limitations of feasibility. All animals were handled for a week prior to behavioral testing. This meant for MISEPA2, MISEPA4 and APPΔEta mice to be placed in the palm of the hand for 2 min/ day, first in the housing room and for the last two sessions in the habituation room of the experimental setting. For the M108 mice this meant to restrain mice once daily per neck grip, placement on a microfiber towel and tipping on canula guide cap with a tweezer to habituate them for the connection to the injector.
3.4.1 Experimental Design for MISEPA2 and MISEPA4 Lines
To test for changes in mice’s memory formation ability in these two transgenic lines, these mice underwent a one-and-a-half-month-long behavioral testing trial. While both lines, MISEPA2 and MISEPA4 and their respective wild type (WT) littermate controls underwent the same behavioral tests, the order in which they were conducted changed slightly between lines. The MISEPA2 line and WT littermates were the first mice tested in this study. While we tried to arrange experimental design taking into account a sequence with increasing stress levels, we started with MWM in the MISEPA2 line due to experimental set-up booking and time restrictions. The order of experiments was as followed: MWM, NOR (excluded from results due to technical issues), CFC and Actimeter (Figure 27). As several batches were tested and primary CFC results seemed the most promising, later batches were only tested in CFC. MISPEA4 and controls were tested in a single batch with the following task order: NOR, MWM, CFC and Actimeter (Figure 28). All groups had several rest days between different tasks to reduce stress levels to a minimum.
83
Figure 27 Timeline of the MISEPA2 behavioral battery testing. The behavioral testing order was MWM (green), NOR (yellow, data excluded due to technical issues), CFC (black), and Actimeter (blue). Mice were handled before MWM.
Figure 28 Timeline of MISEPA4 behavioral battery testing. Order of testing was as follows: NOR (yellow), MWM (green), CFC (black) and Actimeter (blue). Mice were handled before testing.
3.4.2 Experimental Design of M108 Injected Mice Submitted to Behavioral Tasks
After undergoing surgery as described above and a recovery phase, M108 mice were submitted to behavioral tasks (Figure 29). Due to the limitations of injection times, feasibility of multiple injections and ability to inject M108 during the ongoing tasks, mice were submitted to either CFC or T-maze. We conducted several CFC protocols: i. injection prior Conditioning session of CFC and ii. injection after Conditioning session of CFC to allow dissecting different mechanism of memory formation that may be altered under acute enhancement of Aη-α levels in the hippocampus. The T-maze experiments allowed us to observe alterations in memory formation when Aη-α levels are evaluated during memory formation. Rest days between the different T-maze experiments were assured to reduce stress levels of animals.
Figure 29 Timeline of M108 behavioral testing. This timeline includes the operation and following recovery phase with check points to insure cannula dummy placement. Depending on surgery, mice were either tested in CFC (black) or T-maze (pink). CFC testing included dummy replacement 24 h before Conditioning session, as we injected into the hippocampus. Injections into the lateral ventricle made this step redundant in T-maze testing.
84 3.4.3 Experimental Design for APPΔEta Mice
The experimental set up for the APPΔEta mice was designed to reduce stress levels of animals throughout the experiment and rest days between behavioral tests were given. The first series mainly tested heterozygote APPΔEta mice and wild type as the number of homozygote mice was not sufficient to test in parallel. Order of tasks was as followed: Open field, Light-Dark, Social Interaction, T-maze, CFC and Actimeter. We then repeated this series of behavioral tasks with homozygote APPΔEta mice and wild type littermates altering the experimental set up of CFC by including an extinction phase and adding MWM before the CFC. The order of the tasks for these batches was thus as followed: Open field, Light-Dark, 3-chambers social interaction, T-maze, MWM and CFC (Figure 30).
Figure 30 Timeline of APPΔEta behavioral battery testing. The handling phase before behavioral testing is shown in orange. Behavioral testing included Open field (bright green), Light-Dark Box (blue), 3-chambers social interaction task (grey), T- maze (pink), MWM (green), CFC (black), and Actimeter (blue).
3.4.4 Morris Water Maze
The MWM is widely used with mice and rats to test spatial learning and memory. Different configurations allow the experimenter to adapt the difficulty of the task and to test for distinct aspects of memory (Vorhees and Williams, 2006). Animals were tested in a 90 cm diameter water tank with opacifier added to hide the white platform (8 cm diameter, 1 cm submerged) from the grey tank background. During testing water temperature was kept at 25 °C ± 1 °C with light at a constant 30 lux. The tank was divided into four quadrants with four starting positions assigned between borders: north (N), east (E), south (S) and west (W). To assist the animals with creating a spatial map to find the platform, extra maze cues were positioned at the walls behind each starting position. Curtains were used to hide these cues during the first stage of the paradigm. Testing was divided in three stages: Cue task, Training and Probe (Figure 31). For Cue task and Training each session consisted of 4 trials each lasting a maximum of 90 sec to find the platform and an additional 30 sec on the platform. Each trial started by placing the animal facing the sidewalls at one of the starting positions (randomized between trials and animals) and tracking
85 the animals’ movement trying to find the hidden platform using ANYmaze software (Stoelting, Wood Dale, IL). Should the animal fail to reach the platform within the 90 sec, a ruler was used to guide the animal towards it. The inter-trial-interval (ITI) was 10 min during which animals were placed in a training box laid out with paper towels to help them dry.
Figure 31 Timeline of the Morris Water Maze experiment. The first stage Cue task excludes visual or motor impairment for differences in performance for the Probe and familiarizes animals with the task. Training teaches animals to utilize the external clues (shown as light green lines) to learn the platform location. Probe test for animal’s ability to recall the previous location of the hidden platform.
The first stage Cue task consisted of two consecutive days during which animals get familiarized with the task of finding the hidden platform. Furthermore, this stage allows us to exclude visual or motor impairments as factors for performance of animals in the following stages. The hidden platform was marked with a flag as a visual cue and the extra maze cues were hidden behind the curtains. The platforms position changed on both days: N-E quadrant on the first and S-W quadrant on the second day. Following the Cue task, the animals were afforded two rest days, after which the animals commenced the Training stage. During the four days of Training the platforms location, now without the flag, was fixed in the S-E quadrant. The curtain was removed, and the extra maze cues were to be used by animals to guide them towards the platform. 24 h after the last Training trial animals were submitted to the last stage, the Probe. This stage tests the strength of memory for platform location formed during the Training. To do so, the platform was removed but the extra maze cues were still visible. Animals were released facing the sidewalls either from N or W starting position and were left for 30 sec to search for the platform. During all stages the animal’s movement were tracked and for the first two stages, Cue task and Training, the latency for platform location scored. The mean latency for all sessions of each day were calculated and used for statistical analysis. The animal’s movement and their time spent in each quadrant were scored during the Probe. For statistical analysis the percentage of time spent in each quadrant was calculated using the following formula: time spent in quadrant percentual time spent in quadrant = 100 time spent in all quadrants together 𝑥𝑥 𝑥𝑥 ∗ 86 Additionally, a “platform zone” with a diameter of 24 cm was placed around the previous platform location and the number of crosses into this zone were counted. All animals were allowed to habituate for an hour before testing.
3.4.5 Novel Object Recognition
Animals ability to distinguish between a familiar and novel object was tested in NOR (Vogel- Ciernia and Wood, 2014). The apparatus consists of a white arena (40 cm x 20 cm x 30 cm (length x width x height (LxWxH)). To maximize animal throughput, four arenas next to each other were used concurrently. Testing consists of three stages: Habituation, Training and Retrieval (Figure 32). Additionally, to avoid stress in animals and to familiarize them with the experimenter, they were handled for two days before testing started. Habituation lasted for two days with two 10 min sessions per day. The goal was to familiarize the animal with the arena and avoid undue stress of the animals for the next stage. A good indicator for familiarization is a reduction in distance traveled during the session. Therefore, sessions were video recorded, and animals tracked throughout Habituation. The second stage was a single trial the day following Habituation. During this Trial two identical objects were placed in the arena with the following coordinates: 10 cm from the two longest walls, 11.5 cm from the lateral walls and 17 cm from each other. Objects consisted either of two blue Lego cubes or two yellow surprise eggs. Used object pairs were counterbalanced to avoid object preference. Animals were placed facing one of the longest walls and had 10 min to explore the arena and objects. A 1 cm perimeter zone was drawn around the objects and if the animal entered this zone and explored the object the time was tallied. The total time exploring each object was scored and a discrimination index (DI) calculated with the following formula: 1 2 = 100 1 + 2 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 − 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑝𝑝𝑎𝑎𝑎𝑎𝑎𝑎 ∗ Animals exploring objects less than a total𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 of 3 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡sec or scoring𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 a 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡DI of ± 20 were excluded. For the final stage, Retrieval, one of the objects was replaced by a novel object. Depending on the object pair, the novel object would be one of the objects not previously used. 24 h after the Trial with identical objects animals were placed once more, as per the second stage, to explore the new object constellation for 10 min. Again, the subject's time spent exploring the objects was scored and a DI calculated, this time for the novel object:
= 100 + 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 − 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝐷𝐷𝐷𝐷𝐷𝐷𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 ∗ 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝑜𝑜𝑜𝑜𝑜𝑜𝑒𝑒𝑒𝑒𝑒𝑒 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 87 After each session animals were placed in a training box to avoid mixing naïve and trained mice. The subjects were transferred between the habituation and behavioral rooms one hour before testing. The arena was cleaned with 70 % ethanol, water and paper towels after each animal. All sessions were videotaped and analyzed blind to genotype. Animals with adequate memory spent longer time exploring the novel object during Retrieval and should reach a higher DI.
Figure 32 The three stages of Novel Object Recognition. Habituation consist of two 10 min sessions for two days to avoid stress in animals during the next stages. The Trial presents the animal with two identical objects and for 10 min the time exploring the objects is scored. One of the objects is replaced with a novel object for the stage Retrieval 24 h after Trial. Here, the time spent exploring the objects during the 10 min Trial is scored again.
3.4.6 Contextual Fear Conditioning
The CFC task tests for contextual memory. In this case we tested the association of pain through an electric shock with the apparatus box (the context). At first the box did not represent any particular context for the animal but after receiving foot shocks within this context acting as aversive unconditioned stimuli, the box becomes a conditioned stimulus. Placing the animal again in this box after some delay and observing its freezing behavior without receiving any shocks, shows the strength of associative memory formed during the first session (Curzon, Rustay, and Browman, 2009). The CFC apparatus consisted of a 25 cm x 25 cm x 25 cm cubic box (LxWxH) with black methacrylate walls and a transparent front door. The floor was made up of a metallic grid (spacing 0.6 cm) connected to an electric shock generator and a signal amplification control unit (Startle and Fear System, BIOSEB Allcat Instruments, France).
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Figure 33 Contextual Fear Conditioning consisting of two stages. During the first stage animals receive shocks after a two- minute habituation phase and their freezing behavior is scored. For the second stage “Retrieval” the animal is placed in the same box with no shocks applied and freezing behavior scored.
The testing consisted of two days: Conditioning and Retrieval (Figure 33). The animal was placed into the apparatus and allowed to habituate for two minutes before receiving the first shock. 3 shocks of 2 sec with 0.7 mA intensity were applied (if not stated otherwise in the results section). Each shock was given one minute apart, and the animal was removed from the box one minute after the last shock, giving a total testing time of 5 min. After 24 h the animals were placed in the same apparatus for 5 min without any shocks being applied. Animals were habituated to the experimental room an hour prior to testing and placed in a training box after testing to avoid agitating the naïve housing mates. The box was cleaned between animals with 70 % ethanol, water and paper towels. For MISEPA2 the first experiments were video recorded as the automatic freezing software was faulty at this time. Freezing behavior was scored manually through video analysis and by dividing the 5 min in bins of 10 sec, giving a total of 30 bins. If the animal froze for 2 continuous seconds within a 10 sec bin, it was counted as freezing otherwise the bin was assigned as non- freezing. At the end all bins of each segment (habituation, time in between each shock, and Retrieval) were added and the percent of freezing for each segment was calculated. For the following batches and mice lines the automatic freezing recording software Panlab V1.3 (BIOSEB Allcat Instruments, France) was used to analyze the signal generated by the animal’s movement and score the cumulated freezing time (sec) measured over time.
3.4.6.1 CFC Protocol for the M108 Mice As described previously CFC testing consisted of two days: Conditioning and Retrieval (Figure 34). The animal was placed into the apparatus and allowed to habituate for two minutes before receiving the first shock. If not stated otherwise in the result section, 2 shocks of 2 sec with 0.7 mA intensity were applied. Each shock was 1 min apart from the next one and the animal was removed from the box one minute after the last shock giving a total testing length of 4 min. The next day the animals were placed in the same apparatus for 5 min without any shocks being applied. 89 For injection animals were placed on a grid and restrained by hand. They were then placed on a rolled-up fiber towel to avoid suffocation while the cannula guide dummy was replaced with the injector. Either 0.5 µl at 0.2 µl/ min of aCSF or M108 were injected. During the injection the animal was placed in a small housing box and observed to avoid removal of the injector or biting of the tubing. To allow for distribution and avoid efflux the animal stayed connected to the injector for an additional 2 ½ min after the injection stopped. The animal was placed on the grid, restrained and placed on the towel again to change back from injector to cannula guide dummy. Depending on the time of injection the animals were either directly placed in the testing apparatus or the training box. Habituation to the experimental room was up to an hour prior to testing. To avoid agitating the naïve housing mates, mice were placed in a training box after testing. The CFC-box was cleaned between animals with 70 % ethanol, water and paper towels. Freezing was scored if animals did cross the lower threshold for 2 consecutive seconds and was recorded automatically with the software Panlab V1.3 (BIOSEB Allcat Instruments, France).
Figure 34 Contextual Fear Conditioning protocol for M108. Mice received two shocks of 0.7 mA during Conditioning and were submitted to Retrieval 24 h later to test for contextual memory. Injection of M108 occurred either directly before Conditioning or directly afterwards, depending on experiment.
3.4.6.2 CFC Protocol for APPΔEta Mice For APPΔEta mice, the CFC protocol was slightly modified to test for non-associative memory during this task and fear memory extinction (Figure 35). The conditioning phase was set to 3x0.7 mA shocks being applied, and the session was accompanied by white noise (70 Dzb) playing in the box. Further alternations were done during Retrieval, which was split in two parts. The first part consisted of placing mice in a new “neutral” context, similar to the conditioned context but with some alterations as follow: 1. the background of the box was set to white compared to the conditioned box with black background. 2. the box was prepared and cleaned in between animals with medical disinfection spray (Wyritol) instead of 70 % ethanol and water, changing the smell in the box. 3. Instead of the grid we used a metal plate covering the floor.
90 The testing room and white noise during the Retrieval stayed the same. The mouse was placed in this neutral context and freezing behavior was scored for 10 min. Afterwards mice were placed in a single housing box for 1 h before placing them in the box from the conditioning phase to record the conditioned Retrieval for 5 min. This allowed us to test if animals could differentiate between the neutral and conditioned context. Furthermore, we followed up with an extinction protocol consisting of 6 consecutive days placing the animals for 5 min in the conditioned box and scoring their freezing behavior. Freezing was scored if animals did not cross the lower threshold for 2 consecutive seconds and was recorded automatically with the software Panlab V1.3 (BIOSEB Allcat Instruments, France).
Figure 35 Contextual Fear Conditioning protocol for the APPΔEta line. Mice received 3 shocks at 0.7 mA during the Conditioning phase and were submitted to Retrieval 24 h later. This protocol had an additional neutral context during the Retrieval (mice in circle). We added an Extinction phase after the Retrieval to test for strength of memory. During this phase mice were resubmitted to the contextual box (receiving of shocks during Conditioning) for 6 consecutive days.
3.4.7 T-Maze
T-mazes can access the flexible cognitive ability of animals, which involves the hippocampus, as well as working memory depending on the protocol used (Dellu, Contarino, Simon, Koob, and Gold, 2000). The T-maze set-up was a T shaped arena with 3 arms each 6 cm wide and 35 cm long, and a center square of 5.5 cm x 6 cm (Figure 36). All walls consisted of transparent Plexiglass and had a height of 20 cm. The floor consists of light grey Plexiglas. The end of each arm as well as the entrance to the middle could be closed with a guillotine door consisting of black Plexiglas, with one side matt and the other polished. A starting box consisting of polished black Plexiglas (measurements: 10 cm x10 cm x 20 cm (LxWxH)) was used to habituate the animal and transport it during sessions. Before behavioral testing started the arena was cleaned with 70 % ethanol and fresh bedding placed on the floor, which was mixed between each test phase and animals. A mouse not used for testing was left to explore the arena for 5 min to saturate the arena and bedding with odor cues.
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Figure 36 T-maze set-up. The maze consists of three identical arms, in the shape of a T. Each arm could be closed off with a guillotine door and be opened at the end of the arm to retrieve the mouse.
3.4.7.1 Injection of M108 During T-Maze Testing Before animals were placed into the starting box, they were taken from their housing cage and placed on a grid next to the arena and restrained by hand. They were then placed on a rolled-up fiber towel to avoid suffocation while the cannula guide dummy was replaced with the injector. Either 5 µl at 0.5 µl/ min of aCSF or a final concentration of 10 µM sAη-α (M108) in the brain were injected during testing.
3.4.7.2 Familiar versus New Arm Animals were placed in the starting box to habituate for 5 min while the injection was running (Figure 37). Upon opening of the starting box, the animal had 5 min to explore the arena with the starting arm and one open arm (familiar arm). After exploration the injection stopped, and the animal was guided back into the starting box. For the ITI of 10 min the animal stayed connected to the injector and waited in the starting box. If the ITI was one hour, the animal was removed from the starting box and disconnected from the injector. For this hour it was placed in a test-housing box and returned unconnected into the starting box before Retrieval. Retrieval consisted of opening the starting box to the arena and letting the animal explore all three arms (starting, familiar and new arm) for 5 min. During both test phases the animals’ movement was tracked using the ANYmaze software and percentage of time spent as well as discrete entries into the arms were calculated.
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Figure 37 Illustration of the Familiar vs. New arm protocol. The test consists of several phases. Mice habituate in the starting box (indicated as rectangle in illustration), before they were released into the maze to explore (Acquisition). During this phase one of the arms was blocked. After 5 min the mouse were retrieved for either 10 min or 1 h ITI. For the Retrieval the mouse was resubmitted into the arena and allowed to explore all arms freely for 5 min. Habituation and 10 min ITI were spent in the start box, while for 1 h ITI mice were single placed in a clean housing box. The green line in Habituation and Acquisition indicates injection of aCSF or M108.
3.4.7.2.1 Alterations of the T-Maze Task for Testing APPΔEta Mice When testing the APPΔEta line the protocols did not change, except that animals were not connected to the injector. They habituated 5 min in the starting box, stayed in the starting box for the 10 min ITI and were placed in an extra box for the 1 h ITI as described for the M108 mice.
3.4.7.3 Forced Alternation Forced Alternation was only performed for the M108 experiments and mice stayed connected to the injector during the entire task, see Figure 38. To habituate the animal before releasing it into the arena, it was placed in the starting box for 2 min while the injection was running. One of the arms was blocked leaving the animal with a forced choice to enter the other arm. Once the animal fully entered the arm a guillotine trapped it in the chosen arm. The starting box was placed at the end of that arm and the animal was guided into it. In the starting box the animal was returned to the starting position and maintained there for the ITI (30 sec). When the animal reentered the arena both arms were open. Upon fully entering one arm the other was closed with a guillotine and the animal was guided back to the starting box. After 30 sec in the starting box the animal started the next trial with one of the arms being blocked. Each animal usually went through four trials per session depending on its performance. If the injection stopped before the trial concluded the animal was allowed to finish the trial before placement in a test- housing box.
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Figure 38 The Forced Alternation protocol for M108 injected mice. Mice habituated in the starting box before entering the arena. Here, they were forced to choose one arm, as the other arm was blocked. Mice spent a short 30 sec ITI in the starting box before resubmission into the arena. They now could choose freely between arms and if the new arm was chosen, a correct first entry was scored. Mice were injected with M108 into the lateral ventricle throughout this experiment and managed a minimum of four repetitions before the 10 min injection time stopped.
3.4.8 Open Field
The Open field experiment consisted of placing a mouse in a 40 cm x 40 cm x 30 cm (LxWxH) white opaque arena in a high lit room (300 lux) and its movement were observed over a period of time (Figure 39). The test allowed us to observe alterations in locomotor activity, such as distance travelled and speed but also behavioral changes like alterations in anxiety, which can be measured by number of freezing episodes or preferred placement of the mice within the arena. Other observations can include movement patterns like clockwise or anti-clockwise turns for example. As it is considered a low stress level experiment for mice it is widely used to give an overview of phenotypic changes, which than can be investigated further in follow up experiments (Seibenhener and Wooten, 2015). This test consisted of a single phase with no prior habituation to the arena. Mice were placed in the center of the arena and their movements were video recorded over a time period of 10 min. The arena was cleaned with 70 % ethanol and rinsed with water between each animal. Videos were analyzed by dividing the arena into a center quadrant (20 cm x 20 cm) and the periphery (30 cm x 10 cm around the center quadrant) and calculating the distance and time spent in each compartment via ANYmaze software (Stoelting, Wood Dale, IL). Furthermore, the overall speed of animals was checked to test for locomotor differences between groups.
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Figure 39 The Open field recorded movement of the mouse for 10 min. The arena was divided into two zones, the center (dotted square) and the periphery around it.
3.4.9 Light-Dark Box
The Light-Dark task tests for anxiety-like behavior in mice (Heredia, Torrente, Colomina, and Domingo, 2014). The test arena with the dimensions 42 cm x 18 cm x 29 cm (LxWxH) was divided into two zones: a) an open/light zone with 28 cm x 18 cm x 29 cm (LxWxH) with white opaque background and 300 lux, and b) the dark zone consisting of a closed box 14 cm x18 cm x 29 cm (LxWxH) with a black opaque background to enhance the darkness, see Figure 40. The two zones were connected by a small open door (7 cm x5 cm (LxH)) allowing transitioning of the mouse between the compartments. Mice were placed in the center of the dark zone, the box cover immediately placed on it, and left for 5 min to explore both zones freely. In between animals the arena was cleaned with 70 % ethanol and rinsed water. ANYmaze software (Stoelting, Wood Dale, IL) was used to analyze the videos by recording the time spent in the light zone as well as numbers of changes between zones.
Figure 40 The Light-Dark box. The arena is divided into two zones, the light zone and the smaller dark zone. Both zones are connected via a door, allowing free passing of the mouse during this testing.
95 3.4.10 3-Chambers Social Interaction Task
The 3-chambers social interaction task tested the sociability of the mouse by exposing the mouse to an unknown mouse and for the social novelty of an animal by forcing the animal to distinguish between a familiar and new mouse (Moy et al., 2004; M. Yang, Silverman, and Crawley, 2011). The testing apparatus consisted of a rectangular opaque plexiglass box (60 cm x 30 cm x 33 cm (LxWxH)) divided into three chambers (each chamber 20 cm x 30 cm x 22 cm (LxWxH) by clear Plexiglas walls (30 cm x 22 cm (LxH)). The walls had a round opening (4 cm diameter), which could be closed, connecting the chambers and allowing the mice to move freely between chambers during testing. We used cylindrical wire cages of 10.5 cm diameter at the bottom and 11 cm height (Galaxy Cup, Spectrum Diversified Designs, Inc, Streetsboro, OH) to restrain the familiar and new mice during testing. The wire bars were 1 cm spaced allowing the test mice to recognize the familiar and new mice without physical contact. To avoid animals climbing onto these cages, we placed small square objects (5 cmx 5 cmx 5 cm (LxWxH)) on top. The light was dimmed to 3.5 lux during testing to avoid anxiety in mice. Between each mice the arena and cages were cleaned with 70 % ethanol and water, while in between test phases paper towels were used to remove feces and absorb urine to not interfere with sensory cues of mice. The experiment consisted of three successive phases: 1. Habituation, 2. Sociability testing and 3. Social Novelty testing (Figure 41). Each phase started with the test mouse being placed in the middle chamber and the gates to the two neighboring chambers opened. The Habituation phase allowed the test mouse to explore all three empty chambers freely for 5 min and familiarize itself with the arena. The test mouse was then restrained into the middle chamber by closing the gates to prepare the second phase. The wired cages were positioned into the two chambers and a mouse of same strain background, gender and age was placed into one of them. 2 min after the first phase the Sociability testing started by opening the gates. The test mice could once again explore all three chambers freely, familiarize itself with the mouse placed under the wire cage and examine the empty wire cage in the other chamber. After 5 min the gates were closed terminating the second stage. Different to the Habituation phase the test mouse was now restrained in the chamber containing the wire cage with the mouse for 2 min. In the meantime, another new mouse was placed under the previously empty wire cage in the third chamber. The test mouse was placed back into the middle chamber for a minute before initiating the third phase by opening the gates. In this last phase the test mouse could again freely move between the three chambers choosing to either revisit the familiar mouse or explore
96 the new mouse. The test is terminated after 5 min by removing the test mouse and placing it back into its home cage. The placement of the new mouse during the 2nd phase of the test was counterbalanced throughout the experiment. If mice failed to explore all chambers for each phase, they were excluded from analysis. Each testing phase was video recorded. Numbers and time of interaction counting as distance smaller than 2 cm between testing mouse and wire cages (empty vs. mouse, and familiar mouse vs. new mouse) were analyzed using ANYmaze software (Stoelting, Wood Dale, IL).
Figure 41 3-Chamber social interaction task. An arena is divided into three chambers, connected by small doors, which can be closed. The task consists of three phases: Habituation, Sociability and Social Novelty. Dotted circles indicate the wires, either empty or containing a mouse. Shown in orange is the new mouse for the Social Novelty phase.
3.4.11 Actimeter
To test for animals’ activity patterns over time, mice were submitted to an Actimeter (Imetronic Apparatus, Pessac, France) for 72 consecutive hours. The Actimeter consisted of a 20 cm x 11 cm x 18 cm (LxWxH) rectangular Plexiglas box with an internal light source to simulate the dark light cycle as needed. The box was equipped with infrared sensors to detect horizontal locomotor. The behavioral data was collected into bins of 30 min. Animals had a 12-hour dark- light cycle to reflect their housing facility and access to food and water ad libitum.
97 Statistical Analysis
3.5.1 Electrophysiology
Results are shown as mean ± standard error of mean (S.E.M). from independent biological samples. Statistical analyses were performed with Prism 8.0 (GraphPad Software Inc, La Jolla, CA, USA) and are presented in detail in Supplementary. For two independent samples with normal distribution, Unpaired t-test was used. One-way analysis of variance (ANOVA) was used for comparison of more than two conditions or Two-way repeated measured (RM) ANOVA followed by Bonferroni test were used for multiple comparisons. The statistical test used for each statistical analysis is included within the text when results are presented. ‘N’ refers to number of animals and ‘n’ to the number of slices examined. Significance was taken at p<0.05.
3.5.2 Behavioral Testing
Difference between groups in MWM were tested using Two-way ANOVA or Two-way RM ANOVA, followed by a post hoc test, either Sidak’s test or Turkey’s test. Differences in NOR were tested using Unpaired t-test or Two-way ANOVA, followed by Sidak’s Post-hoc test. CFC was analyzed with Two-way RM ANOVA or Mann-Whitney test and Kruskal-Wallis test respectively. An Unpaired t-test, Mann Whitney test, Two-way ANOVA, or Kruskal-Wallis test was used for time spent and entries for T-maze testing. Testing against Chance level was done by using a One sample t-test in MWM, DI Retrieval, and T-maze. For analysis of the Forced Alternation task, we used the Mann-Whitney test. Actimeter data was analyzed by dividing time into 12-hour slots followed by Two-way RM ANOVA and Sidak’s analysis. All data analyzed is presented in detail in Supplementary. Normality of data was tested by the Saphiro-Wilk’s test and equality of variances by the Brown- Forsythe test. The data was analyzed using the software Prism 8.0 (GraphPad Software Inc, La Jolla, CA, USA) and presented as mean ± S.E.M. or median with 95% confidence interval for nonparametric data. The statistical test used for each statistical analysis is included within the text when results are presented. ‘n’ refers to number of animals. Statistical significance is defined as p<0.05.
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4. Results
Results
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4.1 Consequences of Elevated Aƞ Levels on Synaptic Plasticity and Behavior
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102 Consequences of Elevated Aƞ Levels on Synaptic Plasticity and Behavior
In the following chapters we present our results obtained while working on the first two aims of my objectives to: a) further investigate the impact of elevated Aη levels on synaptic plasticity mechanism at excitatory hippocampal neurons, in both acute and chronic conditions, and b) study the behavioral outcome of these acute and chronic elevated Aη-α levels in the brain. We first present the results obtained examine the impact of elevated Aη levels under acute conditions. As described in Material and Methods synthetic peptides M108 and M92 were used to study synaptic plasticity, and M108 was used during the behavioral tasks. The second part focuses on the results obtained examine the impact of chronic elevated Aη-α levels. We used two transgenic mice lines MISEPA2 and MISEPA4 displaying elevated Aη-α levels throughout the brain (see Immunofluorescence and Western Blot Verify Expression of Aη-α in MISEPA2 Mice and Absence of Aη-α in APPΔEta Mice). Alterations in synaptic plasticity and behavioral output were studied in both lines.
4.1.1 Effect of Acute Increase of Aη-α Levels on Synaptic Function and Behavior
4.1.1.1 Impact of Acutely Elevated Aƞ-α Levels on Synaptic Plasticity The purpose of my thesis was to expand the understanding of the η-secretase pathway and the Aη peptides and their physio-pathological role. Until now, Willem et al., (2015) is the single publication illustrating the acute effects of Aη peptides on synaptic plasticity. They describe an acute application of cell-derived recombinant Aη-α capable of impairing LTP at the hippocampal excitatory CA3-CA1 synapse. Furthermore, they show that the acute application of this recombinant Aη-α is sufficient to lower neuronal calcium wave activity of the hippocampal CA1 neurons in vivo. These results suggest that Aη-α is playing an essential role in synaptic plasticity. Going beyond these initial observations, we performed an extended analysis of the effect of synthetic Aη-α on long-term plasticities, short-term plasticities, and basal synaptic transmission.
103 We confirmed that synthetic Aη-α, like recombinant Aη-α, alters synaptic plasticity and showed that low nanomolar concentrations are sufficient to acutely impair LTP. Furthermore, our results show that synthetic Aη-α enhanced LTD while we observe no alterations in short-term pre-synaptic plasticity or basal synaptic transmission. Our results identify that Aη-α is implicated in synaptic plasticity, turning the balance towards LTD. This work resulted in a first authorship for the following manuscript (in preparation for submission).
104 4.1.1.1.1 Aη-α, the secreted APP fragment processed by ƞ- and α-secretases, acutely modulates post-synaptic plasticity mechanisms shifting the balance towards depression of synaptic strength.
4.1.1.1.1 Aƞ-α, the secreted APP fragment processed by ƞ- and α-secretases, acutely modulates post-synaptic plasticity mechanisms shifting the balance towards depression of synaptic strength.
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124 4.1.1.2 Impact of Acute in vivo Injection of M108 into the Brain We observed a reduced LTP and enhanced LTD under acutely elevated Aη-α (M108) levels in our field recordings, which might correlate with deficits in memory formation. To test this hypothesis, we injected M108 either in the hippocampal CA1 region or the lateral ventricle to perform memory dependent behavioral tests. We began with hippocampal CA1 injections pre- or post-Conditioning session in a CFC task described in Experimental Design of M108 Injected Mice Submitted to Behavioral Tasks. After a few trials with the CFC protocol, we significantly changed our approach. The injection site changed from the CA1 region to the lateral ventricle, allowing the distribution of M108 throughout the brain. Furthermore, we switched from CFC to T-maze testing, which is less stressful for mice. Additionally, switching to the T-maze allowed us continuous injection during the Acquisition phase, which was not feasible in CFC. Here we show the distribution of M108 post-injection at different time points and present our data obtained in CFC and T-maze.
4.1.1.2.1 Optimization of Protocol for in vivo Delivery of M108 Peptide Animals were implanted with cannulas in the hippocampi as described in 3.3.1 Surgery and were left to recover after the surgery for one to two weeks during which wound healing and correct dummy placement were ensured. Originally, the protocol for the bilateral surgery also included removal and reinsertion of the dummy every two days to avoid blockage of the cannula guide. After conclusion of the first behavioral experiments we noticed increased necrosis around the injection site when checking for correct implantation site (Figure 42 A). Therefore, we changed the protocol to decrease necrosis by only replacing lost dummies during the recovery phase, but still exchanging to the projection dummy 24 h before the CFC testing. As can be seen in Figure 42 B, this resulted in visibly less necrosis after conclusion of the experiments. Thus, we were able to improve the outcome of the experiment by minimally altering the protocol. We maintained these changes for the post-surgery care in unilateral surgery for implantation in the ventricle.
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Figure 42 Removal of dummies during recovery phase after surgery induces necrosis in brain tissue. A Showing the clearly visible necrosis induced by multiple removal of dummies during the recovery phase. B After protocol optimization for the recovery phase a noticeable decrease in necrosis was observable.
4.1.1.2.2 Presence of M108 in the Hippocampus Post-Injection Confirmed via Blue Evans Dye and Western Blot Distribution of injected M108 was first confirmed via injections with blue Evans dye. Shown in Figure 43 is the distribution of blue Evans dye throughout the ventricles directly post- injection via the implanted cannula. Furthermore, we can see a blue staining of the left lateral ventricle surrounding the hippocampus on the left hemisphere, indicating the fast distribution of M108 post-injection into the right hemisphere (Figure 43 C).
Figure 43 Injection of blue Evans dye distributes throughout all ventricles. A Injection side of blue Evans dye. B Stained areas on the ventral side of the brain. C Separating the brain hemispheres shows blue staining of the left lateral ventricle around the hippocampus.
126 As blue Evans dye likely has different parameters of distribution, we confirmed the presence of M108 at different time points post-injection via Western blot. Figure 44 confirms the presence of M108 in the hippocampus 10 min and 1 hour post-injection into the CA1 hippocampal region via bilateral canula injections. As we did not inject M108 for the 0 min time point we were not expecting any bands here. In both gels, acryl and NovexTM, we see that after 24 h post-injection M108 is no longer detectable via Western blot.
Figure 44 Presence of M108 in the hippocampi post-injection into the CA1 region is confirmed via Western blot. Time points tested were 0 min, 10 min, 1h and 24 h post-injection. Two types of gels, acryl and NovexTM, were used to detect the presence of M108 (2D8 antibody, (Willem et al., 2015)). Pure M108 (1 ng) was loaded on the left column (red line) and Actin was used as a loading control.
For the unilateral injections into the right lateral ventricle we used the time points 0 min, 10 min and 1 h post-injection to confirm the presence of M108 in the hippocampi, which corresponds to the times of the T-maze experiments (Figure 45). Like before, no M108 was injected for 0 min post-injection and these hippocampi act as baseline measurements. We can clearly see a band at 10 min for both hemispheres, left and right, confirming the distribution of M108 through the ventricles. Also, at 1 h post-injection bands are visible, however weaker compared to 10 min. Nevertheless, we could confirm the presence of M108 for different time points crucial to our experimental design.
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Figure 45 Distribution and presence of M108 post-injection into the right lateral ventricle was confirmed via Western blot. Both hemispheres, left and right were collected at three different time points: 0 min, 10 min and 1h post-injection. Two types of gels, acryl and NovexTM, were used to detect the presence of M108 (2D8 antibody, (Willem et al., 2015)) and Actin. Pure M108 (1 ng) was used as a loading control (indicated by red line).
128 4.1.1.2.3 Impact of Acute Injection of M108 into the Hippocampus on CFC 4.1.1.2.3.1 Acute Injection of M108 Prior to Conditioning Session in CFC Does Not Impact Memory Formation but Increases Memory Extinction During Secondary Downstream Retrieval
Mice underwent CFC testing, to see if acute M108 injections (500 ng per hippocampus) into the CA1 region of the hippocampus just before the Conditioning session could impact contextual memory formation and/or extinction of associative memory. Animals were submitted to one session with 2x 0.7 mA shocks followed by a retrieval 24 h later to access long-term memory alterations and again four weeks after the initial Conditioning session to observe alterations in memory extinction. The freezing behavior was scored automatically throughout all three sessions. The Conditioning session revealed that both groups, control aCSF and M108 injected mice, behaved similarly throughout conditioning with a Two-way RM ANOVA showing no significance (p=0,1619) (Figure 46 A). Of course, the different time points, habituation, ITI1, and ITI2, are highly significant throughout the test, as we expected an increasing freezing behavior after each shock (p<0,0001). For the first Retrieval 24 h after the Conditioning session shown in in Figure 46 B, both groups showed increased freezing indicating the successful formation of contextual memory ((μaCSF=
47,13 and μM108= 57,78). While the M108 injected mice showed a tendency towards elevated freezing behavior compared to controls, no significant differences between groups were observed. Interestingly, the percentage of freezing observed for the second Retrieval four weeks later showed no difference between groups with a similar mean per group (μaCSF= 38,38 and
μM108= 38,03). The decrease in freezing between Retrieval sessions is significant (p=0,0135), but independently from genotype (ptime over treatment=0,3043), only for M108 injected mice was the decrease in freezing behavior between sessions significant (p=0.0153). Therefore, it seems that the presence of M108 in the hippocampi just prior to the Conditioning session increases memory extinction during subsequent Retrieval four weeks after the first Retrieval.
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Figure 46 A single acute M108 injection prior to the conditioning session does not perturb memory formation but significantly increases memory extinction. A Percentage of freezing during the 5 min Conditioning session analyzed with Two- way RM ANOVA. B Scoring of freezing for 5 min Retrieval at 24 h and 4 weeks post-shock session, analyzed with Two- way RM ANOVA. n= number of animals, *p<0.05 Detailed statistics are shown in Supplementary Table S5.
4.1.1.2.3.2 Contextual Memory Formation Is Not Impacted by Acute in vivo M108 Injection Irrespective of Time-point of Injection
In the previous paragraph, we looked for alterations in freezing behavior when injecting M108 (500 ng per hippocampus) before the Conditioning session with shocks. As the time dependency on the effects of M108 are unknown, we changed the protocol to injections directly after the Conditioning session. We tested for an effect in Retrieval after 1 h and 24 h in two independent experiments (Figure 47).
Figure 47 Moving the time point of M108 injection to post- conditioning session does not prevent memory formation independent of time-point of Retrieval. Scoring of freezing for 5 min Retrieval A 1 h and B 24 h later, analyzed with Unpaired t-test. n= number of animals. Detailed statistics are shown in Supplementary Table S6.
130 We observed no alterations in freezing behavior for each Condition session, respectively (data not shown, for details see statistic tables Table S6 in Supplementary. Retrieval freezing scores showed no differences for 1 h Retrieval (p=0.9212) (Figure 47 A) or 24 h Retrieval (p=0.4235) (Figure 47 B) when analyzed with Unpaired t-test. Therefore, injection of M108 does not impair the formation of contextual memory in CFC independent from the time point of injection, pre- or post-Conditioning session.
4.1.1.2.4 Effect of Acute Injection of M108 into the Right Lateral Ventricle on Performance in T-Maze Bilateral injections in the CA1 hippocampal region allow for a restricted distribution of M108 post-injection. To assure a global distribution of M108 and enhance likelihood to observe alterations in performance under acute injections of M108, we changed the injection side to the lateral ventricle. Furthermore, we changed the behavioral task from CFC to T-maze. This task has the advantage to utilize the mouse’s innate preference for novelty and is considered significantly less stressful than CFC. However, the main advantage of the T-maze is the possibility for continuous injection of M108 during the acquisition phase of the task. 4.1.1.2.4.1 Times of Injections Rather Than Delay of Retrieval Leads to Performance Impairment in M108 Injected Mice in a Familiar versus New Arm T-maze Task
The T-maze set up allowed us to continuously inject M108, while the animal performed the experiment in the arena. As described in detail in the section Injection of M108 During T-Maze Testing of Material and Methods, we injected M108 for 10 min during which the animal habituated to the starting box (5 min) and then explored the arena (5 min). For the 10 min ITI the mice returned to the starting box and stayed connected to the injector throughout the experiment but no more injection of M108 was performed. Upon re-release into the arena with all three arms open, the first choice between old arm and new arm was scored. While M108 injected mice had a higher score than aCSF mice (μaCSF= 0.77 and μM108= 0.88) analysis with Mann-Whitney test revealed no difference between groups (p=0.3607) (Figure 48 C). Looking at the percentage of entries and time spent in the new arm compared to percentage of total arms, we observed no difference in performance between groups (pentries=0.4832 and ptime=0.1125) (Figure 48 A and B). For both parameters, entries and time, M108 mice as well as aCSF mice preferred the new arm significantly above chance level (33 %) (entries: paCSF<0.0001 and pM108<0.0001, time: paCSF<0.0001 and pM108<0.0001). Thus, M108 and aCSF injected mice were able to distinguish the new arm from the previous visited arms in a 10 min ITI T-maze trial.
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Figure 48 A 10 min ITI showed no alterations of performance in Retrieval, after acute injection of M108 during the first phase of T-maze. Both groups, aCSF and MISEP108 injected mice A entered above chance level and B spent time above chance level in the new arm in a free choice T-maze Retrieval. C Both groups also showed a high accuracy in entering the new arm first (inset). Group difference analyzed with Unpaired t-test, correct first entry with Mann-Whitney test, testing against Chance level (33 %) with One sample t-test. n=number of animals, ****p<0.0001 Detailed statistics are shown in Supplementary Table S7.
4.1.1.2.4.1.1 One Hour ITI Highlights Repetitive Injections of M108 Crucial to Impair Performance in T-maze Task We resubmitted the mice of the 10 min ITI T-maze experiment to perform another T-maze session, this time with an 1 h ITI. In between these experiments, mice performed a Forced Alteration experiment in the T-maze and had rest days to reduce the stress (see timeline shown in Injection of M108 During T-maze Testing in Material and Methods, and next paragraph). Again, these mice were injected M108 (500 ng) only during the 5 min habituation in the starting box and 5 min Training session. For the 1 h ITI, mice were disconnected from the injector and placed in a test housing box. During the Retrieval session, the first-choice entry was scored showing no significant differences between groups (μaCSF= 0.75 and μM108= 0.69, p=0.7154) (Figure 49 C). However, a look at the percentages of entries and time spent in the new arm compared to all arms reveal significant differences between aCSF and M108 injected mice
(pentries=0.0039 and ptime=0.0005) (Figure 49 A and B). Furthermore, we observed that M108 injected mice performed significantly below chance level (33 %) for both parameters, entries and time spent, whereas aCSF injected mice entered and spent time above chance level in the new arm (entries: paCSF=0.0804 and pM108<0.05, time: paCSF=0.001 and pM108<0.05) (see Figure 49 A and B).
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Figure 49 A 1-hour ITI T-maze protocol showed a significantly reduced ability in M108 injected mice to identify the new arm. Compared to aCSF injected mice, the MI108 injected mice A enter significantly less into the new arm and B spent significantly less time in the new arm. The aCSF injected mice could still perform above chance level in identifying the new arm. C For first entry into new arms both groups perform similar with no significant differences (inset). Group difference analyzed with Unpaired t-test, correct first entry with Mann-Whitney test and testing against Chance level (33 %) with One sample t-test. n= number of animals, *p<0.05, **p<0.01, ***p<0.001 Detailed statistics are shown in Supplementary Table S9.
As these animals were tested and injected 3 times in total for the three T-maze experiments (10 min ITI, Forced Alternation, and 1 h ITI), we were interested to see if we could confirm these differences for the 1 h ITI T-maze in a single trial experiment. Therefore, we tested a new batch of mice only in the 1 h ITI trial, while undergoing the same preparation as the previous batches with 3 experiments, consisting of: 1. surgery, 2. post-surgery recovery and 3. adaption handling to the injector. We injected M108 (500 ng) during the 5 min Habituation and 5 min Training like done for the first set of experiments. Once again, the injector was removed, and the mouse placed in a single housing box for the 1 h ITI. While the first-choice scoring was similar to the previous observations for 1 h ITI (Figure 50 C), with no significant differences between groups (μaCSF=
0.71 and μM108= 0.67, p>0.9999), observations for percentage of entries and time spent in the new arm compared to all arms were not different between groups and more comparable to the 10 min ITI experiment (see Figure 50 A and B; and Figure 48 and Figure 49 for comparison). Both groups showed entries and time spent in the new arm above chance level with no differences between groups (entries: paCSF<0.05, pM108<0.001 and pentries=0.1437, time: paCSF<0.0001, pM108<0.0001 and ptime=0.5341).
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Figure 50 A single 1 h ITI T-maze task, with premier injection of M108, shows no performance impairments. Both groups, aCSF and MISEP108 injected mice A entered above chance level and B spent time above chance level in the new arm in a free choice T-maze Retrieval. C Both groups also showed a high accuracy in entering the new arm first (inset). Group difference analyzed with Unpaired t-test, correct first entry with Mann-Whitney test and testing against Chance level (33 %) with One sample t-test. n=number of animals, *p<0.05, ***p<0.001, ****p<0.0001 Detailed statistics are shown in Supplementary Table S10.
4.1.1.2.4.2 Performance in M108 Injected Mice Is Not Impaired in a Forced Alternation T-Maze
The forced alternation task was used to asses impairments in working and reference memory (Deacon et al., 2006; Shoji, Hagihara, Takao, Hattori, and Miyakawa, 2012). In our test setting we implemented a forced choice test as in the first stage one of the arms was blocked to be offered as the new arm in the second stage. We scored the ability of mice to choose the new arm when left with a choice in 4 subsequent trials (Figure 51). While a comparison of groups with the Mann-Whitney test showed no significant differences in ability to choose the new arm correctly (p=0.3607), it is noteworthy that only aCSF injected mice succeeded to choose the new arm above chance level (50 %) (paCSF=0.0271, pM1080.1753).
Figure 51 Forced alternation with 4 trials showing no significant difference between groups, but disability of M108 injected mice to perform above Chance level (50 %). Group difference analyzed with Mann-Whitney test, testing against Chance level (50 %) with One sample t-test. n= number of animals, *p<0.05 Detailed statistics are shown in Supplementary Table S8.
134 4.1.1.3 Discussion This chapter explored the abilities of synthetic Aη-α (M108) to acutely alter synaptic plasticity and behavioral output. Field recordings of synthetic Aη-ß (M92) show impaired LTP, in contrast to observations made in Willem et al. (2015) using cell-produced recombinant Aη-ß, which did not impact LTP. The major difference between the two versions of the peptide is the presence of post-translational modifications that can occur during cellular processing in the recombinant protein but are not present in the synthetic version. This difference could explain the discrepancy in the results obtained. In fact, the Aη peptides seem to be heavily glycosylated in vivo (Willem M. personal communication). We can therefore speculate that post-translational modifications might specifically block the function of Aη-ß in vivo, but more work needs to be performed on this hypothesis. This discrepancy was not observed with Aη-α as both versions, recombinant (Willem et al., 2015) and synthetic (this study), impacted LTP in a similar fashion. This effect was not dependent on the type of aCSF used for recordings (3.6/2 or 2.5/1.3 Ca2+/Mg2+ ratio). Furthermore, we could bracket the concentration needed to elicit an impairment for LTP between 1 nM and 10 nM, as the LTP impairment plateaued around this concentration. Being able to use a lower concentration allowed us to study Aη-α's actions on synaptic plasticity in a more physiologically relevant manner. The range of Aß concentrations in human CSF is estimated to be around 1500 pM. Considering that Willem et al. (2015) estimated Aη levels to be five-fold higher, our range of 1-10 nM is within the estimated realm of physiological activity (Puzzo et al., 2013; Willem et al., 2015). Another factor is the minimization of off-target side effects or toxicity due to high protein concentrations. It has been shown that depending on Aß concentrations, the synaptic outcome completely changes. While low physiological levels of Aß are associated with enhanced synaptic function, this effect reverses in pathological conditions with high Aß levels, as observed in AD (Lazarevic et al., 2017; Puzzo et al., 2008, 2013). Data obtained with such low concentrations of Aη-α are thus less likely to be due to off-target side effects. The observed impairments in LTP considered together with the enhancement in LTD response and onset of LTD under subLTD-conditions indicate a shift in synaptic plasticity towards depression under Aη-α influence. As we notice no alteration in pre-synaptic plasticity, tested via PPR and synaptic fatigue, it is likely that this shift is due to a mechanism occurring at the post-synapse. Theoretically, Aη-α could act as a ligand for a receptor at the post-synapse, such as AMPAR or NMDAR. However, we observed no alterations in basal synaptic transmission,
135 a mechanism mainly mediated by AMPAR. Additionally, Willem et al. (2015) show reduced calcium wave activity in CA1 neurons in vivo upon application of Aη-α, indicating the involvement of Aη-α in Ca2+ gating mechanisms, which are AMPAR-independent. Thus Aη-α acting on NMDAR is more likely. Nevertheless, further experiments are necessary to determine the mechanisms behind Aη-α's ability to alter synaptic plasticity. The difference in abilities to alter synaptic plasticity between the recombinant and synthetic versions of Aη-ß are insofar intriguing as Aη-α contains the full-length Aη-ß protein sequence and only Aη-α has the ability to alter synaptic plasticity in both its versions (recombinant and synthetic).(Willem et al., 2015). Initially, the differences between Aη-α‘s and Aη-ß’s abilities to alter synaptic plasticity could be attributed to the 16 amino acids difference in length. These 16 amino acids contain the N- terminal of the Aß sequence, itself a protein able to alter synaptic plasticity as discussed above. Due to the LTP impairments observed under synthetic Aη-ß, it seems that both parts the Aη-ß amino acid sequence (which does not overlap with the Aß sequence) and the 16 amino acids could possess the ability to alter synaptic plasticity. To measure the behavioral output of acutely elevated Aη-α levels, we injected M108 into the CA1 hippocampal region or directly into the lateral ventricle. We confirmed the distribution of our injections visually via blue Evans staining and the presence of M108 in the hippocampus via Western blot. The Western blot analysis of the hippocampus validates that M108 is still present 10 min and 1 h post-injection, the main Retrieval time-points in our behavioral experiments (Figure 44). We expected to observe a reduction in freezing behavior due to the impaired LTP, enhanced LTD and their association in memory processes (Cooke and Bliss, 2006). However, we did not notice significant behavioral changes in CFC independent from the time point of injection. The different time points were chosen to gain insight into which step of memory formation may be impaired under the influence of M108. Thus, injections pre-Conditioning session assessed impairments in the acquisition and consolidation of memory in CFC, whereas post- Conditioning session focused on impairments in memory consolidation. Both processes, acquisition and consolidation, rely on NMDAR activity, whereas AMPAR is more involved in the encoding in CFC (Gao et al., 2010; Quinn, Loya, Ma, and Fanselow, 2005; Sase, Stork, Lubec, and Li, 2015). However, CFC also involves amygdala activity, and studies indicate that hippocampal dependency in CFC depends on complex multimodal cues rather than a discrete, unimodal stimulus (R. G. Phillips and LeDoux, 1992; Quinn et al., 2005). Consequently, a single local injection of M108 into the CA1 hippocampal region might not have been sufficient
136 to show a phenotype in our CFC protocol, considering that the amygdala function remained unaltered. Therefore, we decided to change the approach from local injecting into the hippocampus to injections into the lateral ventricle, allowing a global distribution of M108 throughout the brain. Additionally, changing the testing apparatus to the T-maze, an apparatus testing working and spatial memory, both hippocampus dependent, allowed continuous injection of M108 throughout the acquisition phase. We observed no memory impairments in the 10 min ITI T-maze trial (Figure 48). However, when repeating the trial a few days later with a 1 h ITI, the M108 injected mice indicated significant impairments in recognizing the new arm (Figure 49). Yet, with testing a naïve batch, we observed that M108 mice exclusively submitted to 1 h ITI showed no impairment in recognition of the new arm (Figure 50). Thus, the mice submitted to the 1 h ITI T-maze receiving multiple injections of M108 showed an impairment, while the batch only receiving one injection of M108 did not exhibit deficits. This data suggests that a single injection of M108 during acquisition of a memory is not sufficient to induce impairments in memory formation. Maybe, multiple injections before memory testing might be more prone to induce memory alterations. Indeed, multiple studies conducted on Aß use a more extended time delay between injection and experiment and inject over multiple days (Chambon et al., 2011; Naert et al., 2015). Of note, we also witnessed a significant reduction in speed for M108 mice injected multiple times before the 1 h ITI trial compared to aCSF mice, a phenotype we did not previously observe in the 10 min ITI trial or with the batch submitted exclusively to the 1 h ITI trial (data not shown). This reduction in locomotor activity could indicate a toxicity component rather than memory alterations induced by multiple injections of M108. Similar observations have been made for injections of Aß in the nanomolar range (Dahlgren et al., 2002; Nakamura, Murayama, Noshita, Annoura, and Ohno, 2001). To clarify if the lack of motivation, neurotoxicity, or memory impairment are the reason for the observed differences between the two 1 h ITI tasks, we recommend repeating the experiment with small protocol variations. The protocol could be as followed, multiple injections of M108 before a single 1 h ITI experiment, followed by an assessment of neuronal viability. Damage to the hippocampus, such as lesions, decreases spontaneous alternation rates indicating its importance in performance (Lalonde, 2002). However, besides the reduction in speed, we could not observe profound impairments in M108 injected mice to execute the task after multiple injections.
137 Altogether, our data suggest that acutely enhanced Aη-α levels can alter synaptic plasticity, while we failed to observe a clear behavioral output of these alterations with in vivo in acute injections of the peptide. We discussed several options for the absence of a behavioral phenotype but left out two physiological relevant alternative explanations. The first being that maybe in vivo, Aη-α levels might be saturating pre-injection; thus, increasing its concentration might not alter the behavioral output. Secondly, while we confirmed the presence of Aη-α post- injection via Western blot, the localization of the excess Aη-α remains elusive. Due to the highly regulated nature of APP processing and clearance of its peptides, Aη-α could have undergone endocytosis or be taken up by astrocytes, thus not accessible to the synapse.
138 4.1.2 Effect of Chronic Enrichment of Aη-α Levels on Synaptic Function and Behavior
This thesis aimed to unravel the physio-pathological role of the peptides originating from the processing of APP via the η-secretase pathway. Our collaborating partners, Willem and Haass, created two transgenic mouse lines MISEPA2 and MISEPA4, both overexpressing a secreted human-derived form of the Aη-α peptide (see section Animal Model in Material and Methods). These lines allow for studying alterations in plasticity and behavior under chronic conditions. Stable overexpression of Aη-α may initiate adaptive processes in the brain, leading to a more evident phenotype than observable under acute conditions described in the previous chapter. Following the path of examination as done in acute conditions (M108), we began by studying the alterations in plasticity under chronic elevated Aη-α conditions. A series of behavioral tasks, as described in Material and Methods, followed the examination of synaptic plasticity to screen for impairments in memory formation.
4.1.2.1 Impact of Chronically Elevated Aƞ-α Levels in a MISEPA2 Mouse Line on Synaptic Plasticity and Behavior The MISEPA2 line was the first line screened for alterations in synaptic plasticity and behavior. This line moderately overexpresses the Aη-α peptide, with expression in the hippocampus restricted to the CA1 region as shown in Material and Methods. Hippocampal synaptic plasticity was analyzed with field electrophysiology as performed under acute conditions. Mice also underwent hippocampal-dependent behavioral tasks to test for impairment of memory formation. The behavioral timeline was different from the one used for acute elevated Aη-α (M108) levels. MISEPA2 mice were submitted to MWM, a spatial memory task testing similar hippocampus involvement as the previously used T-maze, CFC, and Actimeter.
4.1.2.1.1 Influence of Chronically Elevated Aƞ-α Levels in a MISEPA2 Mouse Line on Synaptic Plasticity
4.1.2.1.1.1 Impaired LTP in MISEPA2 Mice
The LTP, to test for alterations in long-term synaptic plasticity in MISEPA2 mice, was induced with two trains of 100 Hz/ 1 sec at 20 sec intervals under aCSFI conditions. We observed normal LTP in WT and a significantly reduced LTP in MISEPA2 mice (p=0.0313, Unpaired t- test) (Figure 52 A and B), indicating that chronically enhanced Aƞ-α levels led to alterations of long-term synaptic plasticity.
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Figure 52 LTP is impaired for MISEPA2 mice at the SC-CA1 synapse of hippocampal slices. A Summary graphs of LTP elicited at the SC–CA1 synapse of WT and MISEPA2 slices B Summary of fEPSP magnitude 45–60 min after LTP induction (time 0) at the SC–CA1 synapse as percentage of baseline tested with Unpaired t-test. n= number of slices, N= number of mice *p<0.05, detailed statistics are shown in Supplementary Table S11.
4.1.2.1.1.2 Short-Term Synaptic Plasticity and Basal Transmission Unaltered in MISEPA2 Mice
Following examination of LTP, we continued to study short-term regulation of neurotransmitter release in these mice by measuring PPRs. The PPR protocol consisted of two stimuli applied at different ISI’s ranging from 100 ms to 400 ms. Throughout the experiment the facilitation in MISEPA2 mice is comparable to WT (Figure 53 A). Analysis with Two-way RM ANOVA showed no difference between genotypes over time (p=0.1416). MISEPA2 mice show no changes in basal synaptic transmission as seen in the I/O curves (B). We set the fiber volley amplitude to a fixed value (ranging from 0.1 to 0.3 mV in 0.1 mV increments) and measured the fEPSP Slope to obtain I/O curves. Two-way RM ANOVA indicates no significance between genotypes or interaction between genotype over time
(pgenotype=0.7363 and pgenotypextime=0.9860). Pre-synaptic short-term plasticity and transmission are not altered in MISEPA2 mice indicating that Aη-α probably does not impact these processes.
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Figure 53 No short-term plasticity deficits observable in hippocampal slices of MISEPA2. A SC–CA1 synapse PPRs (fEPSP2 slope/fEPSP1 slope) responses of WT and MISEPA2, at ISI ranging from 100 ms to 400 ms. B SC–CA1 synapse I/O curves (fEPSP slopes versus increasing afferent FV amplitudes) of WT and MISEPA2. All recordings done in aCSFII and analyzed with Two-way RM ANOVA. n= number of slices, N= number of mice, detailed statistics are shown in Supplementary Table S12.
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142 4.1.2.1.2 Influence of Chronically Elevated Aη-α Levels in a MISEPA2 Mouse Line on Behavior
4.1.2.1.2.1 No Impairment of Performance in a Spatial Memory Dependent MWM Task for MISEPA2 Mice
To test if chronic Aη-α overproduction could perturb memory processes, we submitted 3-4- months-old MISEPA2 mice to a 9-day MWM-task as described in the Morris Water Maze section of the Material and Methods. As illustrated in Figure 54, MISEPA2 exhibit normal spatial learning and memory. During the Cue task, both groups, MISEPA2 and WT, significantly decreased their latency over the two days (p=0.001, Two-way RM ANOVA) (Figure 54 A). This continued in the Training phase, as we observed a significant difference in time over the days (p=0.0438). Neither in Training phase nor Cue task did we observe a difference in performance for genotype over time (pCue task= 0.4245 and pTraining=0.3957).
Figure 54 transgenic MISEPA2 mouse line displays normal function of spatial learning and memory in MWM. A The average escape latency (sec) of the four trials of each session during Cue task and Training analyzed with Two-way RM ANOVA. During Cue task the platform is flagged, and location changed in between sessions, whereas the platform is hidden and the location stable during Training. B 24 h after the last Training session the platform is removed, and the strength of spatial memory tested in a Probe, analyzed with Two-way ANOVA. The time spent in each quadrant is measured and compared against chance level (25 %, dotted line) with One sample t-test. The target quadrant, previously containing the platform is highlighted in red. C Entries into the platform zone were measured and analyzed with an unpaired Mann-Whitney test. n= number of animals. ****p<0.0001 Detailed statistics are shown in Supplementary Table S13.
The Probe 24 h after the last trial of the Training tested the long-term memory strength for the learning of the platform location. Both groups swam mostly in the target quadrant, where the platform was previously located, spending significantly more time than chance level (25 %) therein (p <0.0001 for both groups, One sample t-test) (Figure 54 B). Analysis with Two-way ANOVA showed no significant difference between groups during Probe (p=0.8701). In fact, the increased number of platform entries by MISEPA2 (Figure 54 C) indicates that they have a more precise memory of the spatial learning than the WT (p=0.0186).
143 As we tested male and female mice, we checked for a gender effect throughout the experiment but analysis with Three-way ANOVA revealed no interaction for gender with genotype, over time or combined (data not shown). However, it is noteworthy that the majority of animals tested were male in both groups. 4.1.2.1.2.2 Indication of External Factors Influencing Contextual Memory of MISEPA2 MICE in CFC
The same batch of 3-4-months-old MISEPA2 mice was also submitted to the CFC task. As contextual memory is highly hippocampus-dependent, MISEPA2 were tested in CFC to search for memory impairments due to Aη-α overexpression. The CFC is divided into two stages, with the first Conditioning stage applying the shocks. This stage also acts as a first indicator for different pain perception, which could impact the outcome. As seen in Figure 55 A, showing the manually scored freezing behavior, both groups received the shocks as indicated by the increased freezing time between shocks. No difference in freezing behavior between groups was observed in this stage (p=0.093, Two-way RM ANOVA). 24 h later the second stage Retrieval, tested for the strength of the contextual memory by scoring the percentage freezing over a period of 5 min without any shocks being applied (Figure 55 B). Here we can observe significantly less freezing in the MISEPA2 mice, indicating an impairment in contextual memory (p <0.0312, Mann-Whitney test).
Figure 55 Reduced contextual fear memory in transgenic mice line MISEPA2. A Shown is the freezing percentage for each stage during the 5 min Conditioning session, analyzed with Two-way RM ANOVA. B The freezing percentage during the 5 min Retrieval, 24 h after the Conditioning session, analyzed with Mann-Whitney test. n = number of animals, *p<0.05 Detailed statistics are shown in Supplementary Table S14.
Analyzing these results in CFC split by gender indicated a significant difference in freezing behavior during the conditioning phase (pgender=0.0214), which was not significant for the overall outcome as shown by Three-way ANOVA analysis (pshockxgenderxgenotype=0.2084). During Retrieval, the significant differences between groups were dependent on genotype, as Two-way
144 ANOVA revealed no significant differences between groups for gender but for genotype
(pgender=0.0715 and pgenotype=0.0051) (data not shown).
Figure 56 Contextual fear memory increases in MISEPA2 when analyzed automatically. A Freezing percentage for each segment during the 5 min Conditioning session, analyzed with Two-way RM ANOVA. B Freezing percentage during the 5 min Retrieval 24 h post-Conditioning session, analyzed with Mann-Whitney test. n = number of animals, *p<0.05, detailed statistics are shown in Supplementary Table S15.
Interestingly, when we repeated the experiment in another batch, where we tested mice only in CFC, we observed an increase in freezing behavior for Retrieval in MISEPA2 compared to WT (p=0.0435), shown in Figure 56 B. This time, freezing behavior was scored automatically. Analysis of freezing behavior during the conditioning phase again showed no difference in freezing time for genotype over time (p=0.1086) (Figure 56 A). Following experiments with automatic scoring of freezing, while changing amplitude and number of shocks, showed similar tendencies towards increased freezing behavior in MISEPA2, without reaching significance (data not shown). 4.1.2.1.2.3 Unaltered Diurnal Activity in MISEPA2 Mice
As changes in diurnal activity can affect outcome in behavioral tests, we checked if overexpression of Aη-α could alter overall physical activity by placing MISEPA2 mice in an Actimeter for 72 h (Figure 57). The Two-way RM ANOVA revealed no significant differences between groups for activity over time (p=0.2068).
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Figure 57 MISEPA2 mice show normal circadian activity. Horizontal activity was measured for 72 consecutive hours and analyzed by Two-way RM ANOVA. Dark grey areas represent the dark phase of the dark-light cycle (20:00 to 08:00). n = number of animals. Detailed statistics are shown in Supplementary S16.
146 4.1.2.2 Impact of Chronically Elevated Aƞ-α Levels in a MISEPA4 Mouse Line on Synaptic Plasticity and Behavior From the screening of the MISEPA2 line, we transitioned into screening the MISEPA4 line. This line also overexpresses Aη-α in the brain; compared to the MISEPA2 line, we observed further enhanced expression overall and throughout the hippocampus (Table 2). We reasoned that these increased Aη-α levels might intensify alterations in plasticity and behavior, undetectable in the MISEPA2 line. We received this line after the MISEPA2 line and begun testing following the same procedure. Mice were of a younger age (2-3 months) due to the obligation of culling our mouse lines for shut down of our in house animal facility (see Discussion below). Field recordings were performed to test for alterations in LTP, short-term pre-synaptic plasticity, and basal synaptic transmission, as done previously with M108 and for MISEPA2. Following the examination on plasticity, we tested for behavioral alterations submitting the mice to NOR, MWM, CFC, but with a lower number of shocks and decreased intensity to previous CFC settings to avoid saturation of memory, and to the Actimeter.
4.1.2.2.1 Synaptic Plasticity in MISEPA4 Mouse Line 4.1.2.2.1.1 LTP is Normal in MISEPA4 Mice
Alterations in long-term synaptic plasticity under further elevated chronic overexpression of Aη-α in MISEPA4 mice was studied via LTP. The LTP was induced with two trains of 100 Hz/ 1 sec at 20 sec intervals under aCSFII conditions. Analysis with Unpaired t-test showed no differences for genotype (p=0.2943) (Figure 58 A and B).
Figure 58 Normal LTP in MISEPA2 mice at the SC-CA1 synapse of hippocampal slices. A Summary graphs of LTP elicited at the SC–CA1 synapse of WT and MISEPA2 slices B Summary of fEPSP magnitude 45–60 min after LTP induction (time 0) at the SC–CA1 synapse as percentage of baseline tested with Unpaired t-test. n= number of slices, N= number of mice, detailed statistics are shown in Supplementary Table S17.
147 4.1.2.2.1.2 Impaired Basal Transmission in MISEPA4 Mice but No Alterations in Short-Term Synaptic Plasticity
As previously done in MISEPA2 mice, we continued by investigating alterations in short-term plasticity. We measured PPRs to examine alterations in regulation of neurotransmitter release in these mice. As described before, the PPR protocol consisted of two stimuli applied at different ISI’s ranging from 100 ms to 400 ms. We observed no significance for interaction of genotypes over time (p=0.2795, Two-way RM ANOVA) (Figure 59 A), indicating that short- term synaptic plasticity is not altered in MISEPA4 mice. The I/O curves were obtained to evaluate alteration of basic synaptic transmission (Figure 59 B). Fiber volley amplitude was set to a fixed value (ranging from 0.1 to 0.3 mV in 0.1 mV increments) and the fEPSP Slope was measured. Two-way RM ANOVA indicates significant differences for interaction between genotype over time (pgenotypextime=0.0427). These results suggest further enhanced Aη-α to play no major role in alterations of pre-synaptic short-term plasticity but are sufficient to alter basal glutamatergic synaptic transmission.
Figure 59 No deficits in short-term plasticity dependent PPR observable, but a significant decrease in basal synaptic transmission in hippocampal slices of MISEPA4. A SC–CA1 synapse PPRs (fEPSP2 slope/fEPSP1 slope) responses of WT and MISEPA4, at ISI ranging from 100 ms to 400 ms. B SC–CA1 synapse I/O curves (fEPSP slopes versus increasing afferent FV amplitudes) of WT and MISEPA4. All recordings done in aCSFII and analyzed with Two-way RM ANOVA. n= number of slices, N= number of mice, *p<0.05, detailed statistics are shown in Supplementary Table S18.
148 4.1.2.2.2 Impact of Chronically Elevated Aη-α Levels in a MISEPA4 Mouse Line on Behavior After screening our MISEPA4 mice for alterations in synaptic plasticity we continued to asset for alterations in hippocampal memory dependent behavioral tasks as done previously in acute conditions (M108) and for MISEPA2. We submitted mice to three behavioral tasks assessing their memory performance: NOR, MWM, and CFC, and submitted them afterwards to the actimeter to screen for alterations in diurnal activity, which may influence the performance in the other experiments. 4.1.2.2.2.1 No Effect on Recognition Memory in NOR for MISEPA4 Mice
The NOR tasks involves mice’ innate preference for novelty and screens for recognition impairments (Antunes and Biala, 2012; Vogel-Ciernia and Wood, 2014). NOR had a high exclusion rate overall due to side preference during Training and less than the required 3 sec exploration time of objects. Nevertheless, animals that passed these requirements showed no difference in object preference during Training (Figure 60 A) and analysis by Two-way ANOVA indicates no significant differences for objects over genotype (p>0.9999). As seen in Figure 60 B, both groups showed a preference towards the novel object in the 24 h ITI Retrieval, but only WT mice were able to distinguish between novel and familiar object above chance level (pMISEPA4=0.2051 and pWT=0.0321, Unpaired t-test).
Figure 60 MISEPA4 mice show significant exploration time towards novel objects but fails to reach DI criterion. A Exploration time (sec) for objects in Training for WT and MISEPA4, analyzed with Two-way ANOVA. B DI Retention measuring preference towards novel object in WT and MISEPA4, analyzed by Unpaired t-test. *p<0.05, n= number of animals. Detailed statistics are shown in Supplementary Table S19.
4.1.2.2.2.2 No Impairment of Performance in a Spatial Memory Dependent MWM Task for MISEPA4 Mice
The MISEPA4 mice were also submitted to the MWM task. During the first phase, Cue task, no impairment in performance was observed as both groups significantly improved their escape latency over the two days and a Two-way RM ANOVA indicated no differences between
149 groups over time (p=0.2109) (Figure 61 A). As for the next phase, Training, both groups improved their escape latency overall, but failed to reach significance (p=0.4103). Overall, we did not observe a difference in performance for genotype over time (p=0.924).
For the Probe, both groups performed similar in platform crossing (µMISEPA4=3.833 and
µWT=3.381) (Figure 61 C), with no significant differences between groups, but only WT spent more time than chance level in the target quadrant (pMISEPA4=0.0974 and pWT= 0.0270, Two- way ANOVA) (Figure 61 B). Overall however, no significant differences between groups were observed (p=0.994).
Figure 61 MWM testing showed no sign of spatial memory impairment in MISEPA4 mice. A Average escape latency (sec) for Cue task and Training sessions consisting of four trials analyzed with Two-way RM ANOVA. B Probe, 24 h post last Training session, measuring time spent in each quadrant, analyzed with Two-way ANOVA, and comparing against chance level (25 %) with One sample t-test. The target quadrant, previously containing the platform is highlighted in red. C Entries into the platform zone were measured and analyzed with a Mann-Whitney test. n = number of animals. *p<0.05. Detailed statistics are shown in Supplementary Table S20.
4.1.2.2.2.3 Insufficient CFC Task Set-Up to Examine an Effect on Contextual Learning for MISEPA4 Mice
The same batch of MISEPA4 mice was tested in CFC. Due to the increased freezing behavior observed in the previous tested MISEPA2 during Retrieval (above 70 % for WT) we lowered the amount and intensity of shocks to one 0.3 mA shock (Figure 62 A). This shock induced seldom freezing in both, WT and MISEPA4 mice (μWTl= 1.789 and μMISEPA4= 2.423), and no difference between groups were observed (p=0.8409, Two-way RM ANOVA). Despite the low freezing on the previous day both groups froze during Retrieval showing that they learned the association between shock and box without differences in freezing between groups (p=0.6044, Mann Whitney test) (Figure 62 B).
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Figure 62 A single low intensity shock proved too mild to test for contextual memory. A Percentage of freezing during the 3 min Conditioning session analyzed with Two-way RM ANOVA. B Scoring of freezing during the 5 min Retrieval 24 h post- Conditioning, analyzed with Mann-Whitney test. n = number of animals. Detailed statistics are shown in Supplementary Table S21.
4.1.2.2.2.4 Normal Diurnal Activity in MISEPA4 Mice
As previously mentioned, changes in diurnal activity can affect the outcome on various behavioral experiments and complicate interpretation of results. Therefore, we tested the horizontal activity of MISEPA4 and WT over 72 h in the Actimeter (Figure 63). Over the observed time period no differences in horizontal activity between groups were observed (p=0.9548, Two-way RM ANOVA). As expected, activity in both groups increased during the dark phases and decreased during the light phases.
Figure 63 MISEPA4 mice show normal diurnal activity. Overview of total horizontal activity over a 72-consequitive hour period. Areas in dark grey represent light off in a 12 h dark-light cycle (20:00 to 08:00). Analyzed via Two-way RM ANOVA; n = number of animals. Detailed statistics are shown in Supplementary S22.
151
152 4.1.2.3 Discussion After studying the acute effects of elevated Aη-α levels as described in section Effect of Acute Increase of Aη-α Levels on Synaptic Function and Behavior, we focused our efforts on the chronic effects of elevated Aη-α levels. Beginning by screening for alterations in synaptic plasticity in our transgenic mice line MISEPA2. We discovered an impairment in LTP under chronic elevated Aη-α levels, while short-term synaptic plasticity and basal synaptic transmission remained unaffected. These data are completely coherent with our observations made on these under acutely elevated Aη-α levels, as seen in the previous chapter. We can argue that it is the acute action of Aη-α on post-synaptic plasticity mechanisms that is at play even with chronically elevated levels of the peptide as found in this transgenic mouse line. We then proceeded to screen for a behavioral output of the plasticity alterations by performing a behavioral battery of tests. As discussed earlier in 4.1.1.4 Discussion, impairments in LTP could in general be associated with decreased performance in memory dependent tasks, due to the crucial role of LTP in memory formation. Therefore, we tested for impairments in spatial memory and aversive learning for MISEPA2 mice using MWM and CFC, respectively. Both tasks involve hippocampal information processing and are sensitive to modifications in its circuitry (Curzon et al., 2009). Yet, we did not detect spatial memory impairments in MWM in the MISEPA2 line (Figure 54). Our MWM apparatus is smaller in diameter compared to the standard tank size mentioned in the literature (Sharma et al., 2010). It has been used successfully to detect significant alterations in spatial memory tasks in other mouse lines ( see for example Results in APPΔEta Mice Display Loss of Spatial Memory in the MWM and (Salgueiro-Pereira et al., 2019)). It might, however, be less suitable for the detection of minor impairments such as ones that could occur in the MISEPA2 line. In order to increase the complexity of the task for the investigation of more subtle memory alterations, we could reduce the number of trials for the Training phase or add a reversal phase in future experiments (Sharma et al., 2010; Zhou et al., 2009). Regarding the CFC, we obtained two different outcomes depending on the order of experiments. When the CFC was conducted post-MWM, we observed a reduction in freezing during the Retrieval (Figure 55), whereas without prior MWM, the freezing increased (Figure 56). Unfortunately, for technical reasons, we altered not only the order of testing between the two experiments but also the method of analysis; manual versus automatic detection of freezing. These changes make it difficult to compare the two outcomes. Of note, MWM is considered to be among the more stress-inducing behavioral tasks, due to the immersion in water and escape oriented architecture of the task. The two different results in
153 CFC indicate that altered stress levels due to previous behavioral experiments such as MWM could alter the freezing behavior in Retrieval of MISEPA2 mice. Interestingly, MT5-MMP (η- secretase) has been shown to play a vital role in stress response (Komori et al., 2004; Warren et al., 2012). Thus, the stress during the MWM task and the enhanced Aη-α, which are a product of APP cleavage by the η-secretase, could be the modifier for the different CFC results, indicating that Aη-α might be involved in stress response. We tested a second transgenic mouse line MISEPA4, harboring a more pronounced general Aη-α transgene expression when compared to MISEPA2. As in the MISEPA2 line, pre-synaptic plasticity (tested with PPR) was unaltered. However, unlike our observations with the acute application of M108 and in the MISEPA2 line, we observed a decreased basal synaptic transmission (I/O curve) but did not observe any impairment in LTP in this line. Additionally, the behavioral assessment of the MISEPA4 line, testing for alterations in spatial memory, aversive learning, and recognition memory indicated no evident memory impairments. Only subtle alterations were noticed. As the MISEPA4 mice were not able to identify the platform quadrant above chance level in the MWM task and failed to gain a significant DI for the retention of the NOR task. Yet, their overall performance in both tasks was not significantly different from their WT littermates. We changed the CFC protocol significantly between testing of MISEPA2 and MISEPA4 lines. In the MISEPA2 line, with a high number of shocks with strong intensity, we generally obtained very high freezing scores in WT (above 80 % during Retrieval). We reasoned that we might reach a saturation of the fear memory trace with such strong conditioning, which might prevent us from detecting subtle alterations in memory processing for this task. Before testing the MISEPA4 line, we thus decided to reduce the intensity and number of shocks applied in an attempt to average the freezing of WT mice between 60-80 % (Curzon et al., 2009). We considered this range an adequate freezing behavior, as it might allow for the observation of bidirectional alterations in freezing behavior in MISEPA4 mice, above or below controls. However, our changes turned out too powerful, reducing the freezing behavior in both groups below the point of meaningful interpretation. We observe clear differences in plasticity and behavior outputs between our two transgenic MISEPA2 and MISEPA4 lines. Some of the differences observed in the behavioral tasks could be attributed to the age difference between mice. MISEPA2 mice were 4-months-old on average, while MISEPA4 mice were tested at 2-3-months of age. Both lines MISEPA2 and MISEPA4 are within the first generations post-creation of the transgenic lines. The overall consensus in the literature states at least ten generations post-
154 creation are necessary to establish a stable line with minimal polymorphism effects. In creating a transgenic line, embryonic stem cells, deriving from the 129 inbred strain and containing the modified gene, are injected into the C57 blastocyst. Therefore, genes from a different mice strain flanking the modified gene can cause polymorphism effects among offspring and alter the behavioral outcome (Contet, Rawlins, and Deacon, 2001). As the transgene inserts randomly in the genome, we could have an increase in expression as observed in MISEPA4 mice but an alteration in expression of other genes, leading to loss-of- function or altering the activity in our protein of interest Aη-α. The MISEPA4 line has higher expression levels of Aη-α, while the MISEPA2 line gives a more prominent phenotype, both in synaptic plasticity and behavior. Going forward, the MISEPA2 line seems to be the better candidate to further investigate the effects of chronically elevated Aη-α levels on brain functions. Further biochemical and immunohistochemical characterization of the MISEPA2 line is underway in the laboratory of our collaborators, Willem and Haass. Despite some promising data with the MISEPA2 line that warrant further testing, we stopped behavioral testing due to works on our in-house animal facility obligating us to cull our mouse lines for a point zero. This is the reason we performed the behavioral screening on one single large batch of MISEPA4 mice. We recently reintroduced the MISEPA2 line in-house after a rederivation procedure. It will be important to further explore the mechanisms behind the alterations in synaptic plasticity, including the exploration of LTD, as well as to conduct a broader behavioral battery not solely focused on memory.
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156
4.2 Consequences of Inhibition of the APP Processing ƞ-Secretase Pathway on Synaptic Plasticity and Behavior
157
158 Consequences of Inhibition of the APP Processing η-Secretase Pathway on Synaptic Plasticity and Behavior
The previous chapter reported the results obtained in electrophysiology and behavioral studies when we elevated Aη-α levels acutely and chronically in the brain. In this chapter we report the results we obtained when η-secretase processing of APP was prevented, which depleted the brain from all peptides generated from this pathway, including Aη-α. This approach allowed us to analyze in more detail the necessity of the η-secretase pathway and its associated peptides in brain function. We used the APPΔEta knock-out mouse line described in more detail in the section ‘APPΔEta: A Mouse Model Without η-Secretase Processing of APP due to Deletion the Enzymatic Recognition Site on APP’ in Material and Methods to investigate this issue. In brief, this mouse model harbors a deletion on the endogenous APP around the η-secretase cleavage site, preventing APP processing by η-secretase. We analyzed hippocampal synaptic plasticity with field electrophysiology in these mice and their WT littermates to screen for alterations in the absence of the η-secretase pathway of APP processing. Furthermore, we submitted these mice to a series of behavioral experiments. No longer focusing purely on hippocampal dependent memory, we introduced a number of other behavioral experiments to unravel the physiological importance of the η-secretase cleavage of APP and generation of the associated peptides in cognition.
4.2.1 Impact of Deficiency in η-Secretase Processed APP in an APPΔEta Mouse Line on Synaptic Plasticity
4.2.1.1 No Alterations of LTP in APPΔEta Mice We tested for alterations in long-term synaptic plasticity in homozygote APPΔEta mice (HOMO) and WT littermates aged 3-4 months. Our field recordings were conducted at the CA3-CA1 synapse on hippocampal slices. The LTP was induced with two trains of 100 Hz/ 1 sec at 20 sec intervals under aCSFI conditions. We observed normal LTP in HOMO when compared to WT (Figure 64 A and B). Analysis with Unpaired t-test showed no differences for genotype (p=0.9230). Thus η-secretase processing of APP does not seem be necessary for induction or maintenance of LTP at this synapse.
159
Figure 64 Normal LTP in HOMO mice at the SC-CA1 synapse of hippocampal slices. A Summary graphs of LTP elicited at the SC–CA1 synapse of WT and HOMO slices B Summary of fEPSP magnitude 45–60 min after LTP induction (time 0) at the SC–CA1 synapse as percentage of baseline, analyzed with Unpaired t-test. n= number of slices, N= number of mice. Detailed statistics are shown in Supplementary Table S23.
4.2.1.2 Deficiency in ƞ-Secretase Processed APP Prevents LTD, a Phenotype Rescued by Acute Application of M108 We continued our examination of alterations in synaptic plasticity by testing for LTD. Calcium levels were raised to induce LTD in adult mice (using aCSFII). LTD was induced with a low frequency stimulation (900 pulses at 1 Hz) as done in previous experiments. Interestingly, we could not induce LTD in HOMO, as the signal went back to baseline looking at the slope 45- 60 min post- induction (Figure 65 B), while we observed LTD in WT, as expected. To check if lack of LTD is due to absence of Aη-α in HOMO, we performed a rescue experiment by adding 10 nM M108 into the aCSFII prior to LTD induction on HOMO slices. As seen in Figure 65, the addition of synthetic Aη-α is sufficient to restore LTD in HOMO. One-way ANOVA shows significant differences between the groups (p=0.0036). Post hoc analysis shows significant differences in LTD response between HOMO and WT (p=0.0424), and HOMO and HOMO+M108 (p=0.0038). These observations indicate a crucial role for Aη-α in LTD at the synapse.
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Figure 65 Addition of M108 rescues LTD in HOMO at the SC-CA1 synapse of hippocampal slices. A Summary graphs of LTD elicited at the SC–CA1 synapse of WT, HOMO and HOMO+ M108 slices B Summary of fEPSP magnitude 45–60 min after LTD induction (time 0) at the SC–CA1 synapse as percentage of baseline, analyzed with One-way ANOVA. WT against HOMO: # p<0.05, HOMO against HOMO+M108: **p<0.01, n= number of slices, N= number of mice. Detailed statistics are shown in Supplementary Table S24.
4.2.1.3 Short-Term Synaptic Plasticity and Basal Transmission are Normal APPΔEta Mice Next, we investigated alterations in short-term regulation of neurotransmitter release in these mice by measuring PPRs. As described before, the PPR protocol consisted of two stimuli applied at different ISI’s ranging from 100 ms to 300 ms. HOMO did not display alterations in PPR (Figure 66 A) and Two-way RM ANOVA analysis indicates no significance for interaction of genotypes over time (p=0.7123). I/O curves were also obtained in these mice (Figure 66 B). Once again, we set the fiber volley amplitude to a fixed value (ranging from 0.1 to 0.4 mV in 0.1 mV increments) and measured the fEPSP Slope. Two-way RM ANOVA indicates no significance between genotypes or interaction between genotype over time (pgenotype=0.4149 and pgenotypextime=0.6872). These results suggest that processing of APP by η-secretase is not necessary for pre-synaptic short-term plasticity or basal glutamatergic synaptic transmission.
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Figure 66 No pre-synaptic short-term plasticity deficits were observable in APPΔEta mice. A SC–CA1 synapse PPRs (fEPSP2 slope/fEPSP1 slope) responses of WT and HOMO at ISI ranging from 100 ms to 300 ms. B SC–CA1 synapse I/O curves (fEPSP slopes versus increasing afferent FV amplitudes) of WT and HOMO. All recordings done in aCSFI and analyzed with Two- way RM ANOVA. n= number of slices, N= number of mice. Detailed statistics are shown in Supplementary Table S25.
162 4.2.2 Impact of Loss of η-Secretase-dependent Cleavage of APP on Behavior
We continued to submit our APPΔEta mice to a series of behavioral experiments to test if the loss of η-secretase-dependent cleavage of APP impacts behavior, similar to the experiments done in acute and chronic elevated Aη-α levels (M108, MISEPA2 and MISEPA4). As described in Material and Methods we obtained three different kind of mice in our breeding colony, HOMO, heterozygote APPΔEta mice (HET) and WT littermates. This allowed us to screen for alterations in behavior in conditions mimicking the loss of APP processed by η-secretase and with reduced cleavage products of the η-secretase pathway in APP processing. Furthermore, being the first time, this model is examined, we expanded our behavioral series to include experiments assessing alterations in physiology in our animal models. Mice were submitted to a series of experiments consisting of: Open field, Light-dark-box, 3-chambers social interaction task, T-maze, MWM, CFC, and Actimeter.
4.2.2.1 Indication of Reduced Anxiety for HOMO in Open Field We measured the percentage of time spent in the center of Open field as an indicator for anxiety as well as average distance travelled and speed during the 10 min in in the Open field as parameters for locomotor activity. Time spent in center of Open field was significantly higher in HOMO compared to other genotypes (µWT=18.64, µHET=15.31 and µHOMO=27.26) (Figure 67 A). HET and HOMO exhibited comparable locomotor activity to WT with no significant differences observed, neither for speed nor distance (pspeed=0.4546 and pdistnace=0.4488, Kruskal-Wallis test) (Figure 67 B and C). Therefore, the increased percentage of time spent in the center by HOMO is not due to phenotypical changes in locomotor activity but could rather indicate a decrease in anxiety compared to WT.
Figure 67 HOMO APPΔEta mice show reduced anxiety in the Open field. A Percentage of time spent in the center of the Open field B Average distance travelled (m) and C Average speed (m/sec) in the Open field. n= number of animals, all analyzed with Kruskal-Wallis. Detailed statistics are shown in Supplementary Table S26.
163 4.2.2.2 Indication of Reduced Anxiety for APPΔEta Mice in the Light-Dark Box The Light-Dark box test is another experiment to test anxiety levels of animals by measuring their percentage of time spent in the light compartment (Figure 68). While analysis with a Kruskal-Wallis test revealed no significant differences between all groups (p=0.1182), we can observe an increase in percentage of time spent in light for HOMO compared to WT
(µWT=43.89, µHET=46.64 and µHOMO=52.60).
Figure 68 Light-Dark box test hints toward reduced anxiety in HOMO. n=number of animals, analyzed with Kruskal-Wallis. Detailed statistics are shown in Supplementary Table S27.
4.2.2.3 Regular Social Interaction Observed for APPΔEta Mice in the 3-Chambers Social Interaction Task After the Light-Dark box test, mice were tested in the 3-chambers social interaction task. The Habituation phase acclimates the animals to the experimental settings and detects possible side preferences in animals, which could later on interfere with the results. All groups observed the different chambers equally (data not shown). In the next stages we tested for the sociability of mice and then if they could distinguish between a new and familiar animal (Figure 69). In the mouse vs. empty stage, all three groups spent more time with the wire cage containing the mice, with only HET failing to reach significance in distinguishing between them (pWT=0.0002, pHET=0.199 and pHOMO=0.0003) (A). Further analysis with Two-way ANOVA showed high significance distinguishing between compartments but no differences when testing for interaction between genotype and compartments (pcompartment<0.0001 and pgenotypexcompartments=0.2751). During the new versus familiar mice, the third phase of the experiment, Two-way ANOVA analysis indicated that none of the groups could distinguish between the new and the familiar mouse (Figure 69 C, see Supplementary Table S28). Therefore, we concluded that the third phase of this test did not work, rendering it unsuitable for interpretation of phenotype.
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Figure 69 APPΔEta mice show no impairment in sociability in the 3-chambers social interaction test paradigm. A Social interaction phase testing discrimination by time spent between two wire cages with one empty and the other occupied by a mouse. B Novelty discrimination is tested by filling the previous empty cage with a new mouse and test for time spent in proximity to each cage (familiar vs new mouse). n= number of animals, **p<0.01, analyzed with Two-way ANOVA. Detailed statistics are shown in Supplementary Table S28.
4.2.2.4 Impaired Spatial Memory in HOMO in T-Maze Task We also tested these APPΔEta mice in a 10 min and 1 h ITI familiar versus new arm T-maze task, testing for impairments in spatial memory. Animals habituated to the starting box, then explored the arena including one of the arms, while the other arm (new arm) was blocked for 5 min. They returned to the starting box for the 10 min ITI or a test box for 1h ITI as described in Material and Methods. Upon new release into the arena with all three arms open, we scored the percentage of entries (Figure 70 A) and percentage of time spent (Figure 70 B) in the new arm as a ratio with percentage of all arms. The first choice of entry was also scored for all genotypes (Figure 70 C). When looking at percentage of entries and time spent into new arm over all arms, we see a significance for genotype for both measures (pentries=0.0101 and ptime=0.0376) (A and B). Looking at the comparisons between groups with the post hoc tests we see that this effect is mainly driven by the differences in performance between WT and HOMO (pentries=0.0177 and ptime=0.0385) indicated with the # symbol respectively in Figure 70. For both parameters, entries and time, WT and HET prefer the new arm significantly above chance level, while HOMO fail to do so
(entries: pWT<0.0001, pHET=0.0190 and pHOMO=0.4017, time: pWT<0.0001, pHET<0.0001 and pHOMO=0.1361, One sample t-test) (Figure 70 A and B). Yet, we observe a higher score towards the new arm in HOMO compared to WT, while HET score intermediate between the other two (µWT=0.52, µHET=0.68 and µHOMO=0.91), leading to significant differences between genotype (p=0.0376) (Figure 70 C). Thus, while HOMO show a high ability to initially identify the new arm over the familiar one, the novelty effect seems to wear off quicker than in the other groups, resulting in a lower score for HOMO in the other parameters (entries and time spent) that take into account the behavior over the test period.
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Figure 70 A 10 min ITI familiar vs new arm T-maze test indicates a quick wear off for novelty in HOMO. A Percentage of entries into new arm compared to all arms B Percentage of time spent in new arm compared to all arms C Correct entries into new arm in a first choice test. All analyzed with Kruskal-Wallis test, Chance level with One sample t-test. Against Chance level (33 %): *p<0.05, ****p<0.0001, between WT and HOMO: #p<0.05, n=number of animals. Detailed statistics are shown in Supplementary Table S29.
After a few days, we resubmitted the mice to a 1 h ITI T-maze task. Here we observed a change in overall performance compared to 10 min ITI (Figure 71). No significant differences for genotypes in the percentage for entries or time spent in the new arm compared to all arms were observed in
One-way ANOVA (pentries=0.3807 and ptime=0.9063) (Figure 71A and B). The increased challenge of performance in the 1 h ITI is shown by the reduced significance for performance above chance level in both parameters, with only the WT passing both and HET passing the time spent, but
HOMO, like in 10 min ITI, fail to perform above chance level in both (entries: pWT=0.0049, pHET=0.3281 and pHOMO=0.7129, time: pWT<0.0005, pHET<0.0336 and pHOMO=0.2242, One sample t-test) (Figure 71 A and B). The first-choice entry was scored showing no significant differences between groups (p=0.3754), but quite the change in scoring for HET, previously the intermediate score being the highest now (µWT=0.63, µHET=0.77 and µHOMO=0.55) (C).
Figure 71 HOMO display impairments in the 1 h ITI T-maze task. A Percentage of entries into new arm compared to all arms. B Percentage of time spent in new arm compared to all arms. C Correct entry into new arm in a first choice paradigm. A and B analyzed with One-way ANOVA, C with Kruskal-Wallis test, and Chance level (33 %) with One sample t-test. n= number of animals, *p<0.05, **p<0.01, ***p<0.001. Detailed statistics are shown in Supplementary Table S29.
166 4.2.2.5 APPΔEta Mice Display Loss of Spatial Memory in the MWM MWM tests for spatial memory impairments and was conducted as described in Material and Methods. During the Cue task, both groups, WT and HOMO, could significantly lower their escape latency over the two days, with no difference observed between genotypes (pdays<0.0001 and pdayssxgenotype=0.5217) (Figure 72 A). During the Training a Two-way RM ANOVA revealed no significant difference between genotypes over time (p=0.5585). In the Probe test, WT clearly preferred to spent time in the target quadrant (pWT=0.0043), while HOMO did not remember the previous platform location (pHOMO=0.3834) (Figure 72 B). Two-way ANOVA showed significant differences for genotype and quadrants (p=0.0299). Furthermore, despite failing to reach significance, we observe a tendency towards lower number in crossing of platform location during the Probe for HOMO mice (p=0.2348) (Figure 72C). We conclude that HOMO show impaired spatial memory in MWM.
Figure 72 HOMO show impairment in retrieval of platform location during Probe in the MWM test. A Escape latency of mice for Cue task and Training, analyzed with Two-way RM ANOVA. B Percentage of time spent in each quadrant during Probe, analyzed with Two-way ANOVA. Chance level was analyzed with One sample t-test. C Number of crossing the previous platform location during Probe, analyzed with Mann-Whitney test. n=number of animals. against Chance level: **p<0.01, between groups: # p<0.05, detailed statistics are shown in Supplementary Table S30
167 4.2.2.6 APPΔEta Mice Display Normal Contextual Fear Memory We tested a single batch of HOMO and WT in a CFC experiment followed by a 6 days memory extinction paradigm. As described in the section CFC Protocol for APPΔEta Mice in Material and Methods, this CFC consisted of a Conditioning phase followed by a Retrieval phase 24 h later. Here, we introduced a neutral Retrieval phase in between, by submitting animals into a box with a different environment to see if the context is necessary for freezing after the Conditioning phase with shocks (see Figure 73). If mice show problems to distinguish between the neutral and conditioned contexts, this could imply generalization of memory and thus loss of pattern separation (Curzon et al., 2009). Analysis by Two-way RM ANOVA indicated no differences for genotypes over time during the conditioning phase (p=0.8352) (Figure 73 A). We could observe a low freezing score for mice of both groups when placed in a neutral context 24 h post-Conditioning phase (Figure 73 B). In both groups this freezing score was significantly lower compared to the percentage of freezing scored upon placement into the conditioned box (p<0.0001 for both, Sidak’s). This indicates that both groups made a strong connection between the shocks and conditioned context. The strength of this connection was tested during extinction phase (Figure 73 C). During the following 6 days the animals were placed daily in the conditioned environment for 5 min and their freezing behavior was scored. As expected, a Two-way RM ANOVA revealed a decline in freezing behavior over the following days, but no significant difference between genotypes (ptimexgenotype=0.2814). Although more mice should be tested to complete these groups, we conclude at this stage that loss of η-secretase dependent processing of APP does not impact contextual fear memory.
Figure 73 A two-day CFC experiment followed by an extinction paradigm revealed no impairments in contextual memory or memory extinction in HOMO. A Conditioning consisted of 3 x 0.7 mA shocks applied in a 5 min session. B 24 h ITI Retrieval consisted of 5 min testing in a neutral context followed an hour later by a 5 min session in the conditioned context. C Extinction of this memory was tested by submitting the animal for 5 min to the contextual environment on 6-consequitive days following the Retrieval. All analyzed with Two-way RM ANOVA. n= number of animals, ****p<0.0001. Detailed statistics are shown in Supplementary Table S31.
168 4.2.2.7 Diurnal Activity is Altered in HOMO Mice (Preliminary Data) Lastly, we submitted our mice to the Actimeter to test for alterations in diurnal activity. The horizontal activity was scored over a period of three days (Figure 74). We clearly observe significant differences between groups over the period of time analyzed by Two-way RM ANOVA (p<0.0001). When we look more into the distribution over time, we see that during the light off phases, indicating the active phase in mice, we can observe an increase of activity in HOMO mice compared to WT, while HET mice seem to have a reduced activity (for details see Supplementary Table S32). These observations hold true for the light phases as well, with reduced significance between groups. As the behavioral experiments were done during the light phase and similarity of activity considering distance and speed was verified before each experiment, the other behavioral results are unlikely to be influenced by these diurnal activity differences. Nevertheless, future planning of behavioral testing should consider this discrepancy of activity between groups.
Figure 74 Diurnal activity is altered in APPΔEta mice. Overview of total horizontal activity over a 72-consequitive hour period. Areas in dark grey represent light off in a 12 h dark-light cycle (20:00 to 08:00). Analyzed via Two-way RM ANOVA, n=number of animals, ****p<0.0001, detailed statistics are shown in Supplementary Table S32.
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170 4.2.3 Discussion
The deletion of the η-secretase recognition site in the knock-out mice APPΔEta leads to the abolition of the η-secretase-dependent APP processing pathway, including depletion of Aη-α. Screening for alterations in long-term synaptic plasticity in HOMO APPΔEta mice shows normal LTP but impaired LTD. As we showed in the previous Results chapters, in acute and chronic conditions, LTP is impaired under elevated Aη-α levels. Putting together these data, we can argue that LTP does not depend on Aη-α but increasing Aη-α levels impair this plasticity mechanism. The absence of an LTD observed in the HOMO APPΔEta mice indicates that the processing of APP by η-secretase is necessary for this synaptic plasticity mechanism. In a rescue experiment, adding M108 to the aCSF solution while recording in HOMO APPΔEta mice, we were able to restore LTD. This experiment points out Aη-α as a crucial element of the η-secretase-dependent APP pathway necessary for LTD. Furthermore, we record no significant alterations in short-term pre-synaptic plasticity (PPR) or basal synaptic transmission (I/O) in the absence of η-secretase pathway-dependent APP processing. This was also observed with the acute application of M108 on control slices as reported in the first Results chapter. Taken together, these results suggest that the addition of M108 in the rescue experiment, restoring the LTD, acted via post-synaptic mechanisms, as further discussed in 4.1.2.3 Discussion. Advancing past our previous experiences for behavioral testing in the transgenic lines MISEPA2 and MISEPA4, we expanded the behavioral battery for APPΔEta mice to gain a broader overview of the emerging phenotype. We continued to test for spatial memory and aversive learning and added tests like the Open field, the Light-Dark box and the 3-chambers social interaction task to gain an insight into the animals' emotional state. The Open field and the Light-Dark box showed HOMO spending more time in the zone associated with reduced anxiety. However, an increase in basal locomotor activity or novelty- seeking behavior, both occurring in the genetically modified mice, could lead to a false-positive result (Campos, Fogaça, Aguiar, and Guimarães, 2013). Hence, these tests can suggest a propensity towards anxiety, but it will be important to confirm this putative anxiety phenotype with other behavioral tests such as the elevated plus-maze task. The T-maze, one of the simplest tasks to test spatial memory, registered impairments in the performance of APPΔEta mice. The decrease in performance correlates with the absence of APP processing by the η-secretase pathway, as HOMO show a more significant impairment than HET. The differences in performance between groups are more evident with the 10 min ITI trial than with the 1 h ITI trial. The 1 h ITI trial challenges the imprint of the memory to a
171 higher degree than 10 min ITI trial and other studies report a reduction in performance for wild type mice under prolonged ITI (Dellu et al., 2000). Thus, an overall reduction in performance, rather than the absence of memory impairments in APPΔEta mice, could be contributing to the absence of significance when comparing groups for this 1 h ITI. Lowering the challenge of wild type mice by reducing the ITI to 30 min could restore the observed differences in 10 min ITI, while establishing a stronger context to long-term memory. The second spatial memory task in our behavioral battery of tests, the MWM, gives further evidence that spatial memory is impaired in HOMO. While mice were able to learn the task, the Probe test suggests that they failed to create a spatial map of the location of the platform within the tank. Mice with an impaired LTD have been associated with a loss of flexibility, thus, adding a reversal phase could increase the challenge for APPΔEta mice, giving a more prominent phenotype (Nicholls et al., 2008). The 3-chambers social interaction task has three phases, with the last two phases testing for sociability and novelty. For the social phase, giving the test mouse a choice between an empty wire cage and a wire cage containing an unfamiliar mouse, we observe a significant preference for sociability in HOMO mice and WT mice. This preference indicates that HOMO mice are social and, when given a choice, will interact with a counterpart. The last phase tests the mice's innate preference for novelty by placing an unfamiliar mouse under the previous empty wire cage. If the mouse is able to recognize the unfamiliar mouse, they will spend more time in the new mouse holding compartment. We observed WT mice spending more time in the compartment containing the new mice but failing to reach significance. The HOMO mice, on the other hand, spent nearly the same period in both compartments, the one containing the familiar mouse and the other one holding the new mouse. In a study by Pearson et al. (2010), a reversal for phase three is added, in which the familiar mice were placed in the previously empty wire cage and the novel mice in the wire cage occupied by the familiar mice in phase two (Pearson, Defensor, Blanchard, and Blanchard, 2010). In this condition, B6 mice were no longer able to distinguish between the mice. They suggest that the location of the novel stimulus will determine the detection of novelty. We observed spatial memory impairments in the HOMO mice, which also showed the lowest capacity to differentiate between the new and familiar mice, indicating that they lack the ability to identify the location of novelty. Their impairment in spatial memory would suggest that HOMO mice showed sociability rather than novelty-oriented behavior in the third phase of the 3-chambers social interaction task. In this battery of behavioral tests, we returned to the original CFC protocol, giving three shocks at 0.7 mA. For the Retrieval, a neutral component was added to test for non-associative freezing.
172 We also included a memory extinction paradigm submitting the mice to the contextual context over a 6-day time course after the Retrieval (Curzon et al., 2009). No impairment in freezing behavior for the conditioned context nor increased non-associative freezing in the HOMO APPΔEta mice was detected. Indicating that we do not have aversive learning impairments in our APPΔEta mice, which has been described in other models with impairments of LTD. As previously discussed, the absence of impairments could be influenced by the emotional response elicited during CFC, which involves several brain structures compensating for the hippocampal shortcomings, as resubmission to an environment associated with a strong emotion like fear can elicit the same response (MacLean, 1952). These emotional connections could explain the persistence of freezing we observed throughout the extinction testing. Overall, we discovered that the absence of APP processing by η-secretase pathway does not alter LTP but impairs LTD. Furthermore, we could identify Aη-α as a crucial component necessary for the generation of LTD. The screening for a phenotype in APPΔEta indicates a putative reduction in anxiety and clear impairment in spatial memory.
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5. General Discussion and Perspectives
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176 5. General Discussion and Perspectives My overarching aim was to expand the knowledge about the pathophysiological role of the η- secretase pathway, with the focus on its proteolytic product Aη-α. To achieve this, we used two different approaches: • First, we artificially elevated Aη-α levels within the brain and • Second, we depleted Aη-α and the other cleavage products by hindering the η- secretase from cleaving APP at its recognition site. The first approach encompasses my first two objectives to further study the effects on synaptic plasticity and the behavioral output due to elevated Aη-α levels. We used M108 to acutely elevate Aη-α levels and the novel MISEP transgenic lines to generate chronic elevated Aη-α levels. Both approaches have their advantages and disadvantages.
Synaptic Plasticity, Under Acute and Chronic elevated Aη-α Conditions
Using M108 to acutely elevate Aη-α levels was useful in studying the alterations of Aη-α in synaptic plasticity. We were able to bracket the concentration levels necessary to alter synaptic plasticity between 1-10 nM and expand our knowledge on the alterations at the synapse. It is now evident that Aη-α, when applied acutely, does not alter basal synaptic transmission or short-term pre-synaptic plasticity. Furthermore, we could show that acutely elevating Aη-α levels not only impair LTP but also enhance LTD. In fact, we revealed that Aη-α initiates a shift in synaptic response towards depression. This work resulted in a manuscript for publication (see Results ‘4.1.1.1.1 Aƞ-α, the secreted APP fragment processed by ƞ- and α-secretases, acutely modulates post-synaptic plasticity mechanisms shifting the balance towards depression of synaptic strength.’). We discussed the probability of Aη-α's involvement in Ca2+ gating mechanisms and the likelihood to act as a ligand on post-synaptic receptors (see 4.1.1.4 Discussion). Going forward, we will examine these probabilities utilizing tools such as patch-clamp and Western blot. This could help to identify the receptors involved and molecular mechanisms underlying this Aη-α driven synaptic plasticity alterations. The transgenic mouse lines MISEPA2 and MISEPA4 allowed us to assess the consistency of alterations in synaptic plasticity under chronic conditions. We confirmed an impairment in LTP under chronic elevated Aη-α levels in the MISEPA2 line but not in the MISEPA4 line. Furthermore, in both lines, short-term synaptic plasticity remained unaltered, which is in
177 coherence with our observations in acute M108 conditions. While we observed no alterations in basal synaptic transmission in the MISEPA2 line, concurring with the results in acute conditions, we observed a decline in the MISEPA4 line. We discussed the possible causes for this discrepancy, like our transgenic lines harboring unstable expression of the transgene in different sites in the two lines affecting off-site genes (see 4.1.2.3 Discussion). We concluded that the MISEPA2 line is the better candidate to further investigate the effects of chronically elevated Aη-α levels on synaptic plasticity, notably on LTD processes considering our findings in the APPΔEta line.
Behavioral Studies, Under Acute and Chronic elevated Aη-α Conditions
Having extended our understanding of elevated Aη-α levels effects on synaptic plasticity, we continued to study their effects on behavior. Alterations in synaptic plasticity, especially reduced LTP, have been linked in numerous studies to impairments in memory formation (LaFerla, Green, and Oddo, 2007; Neves et al., 2008; Peineau et al., 2007). As we observed a reduction in LTP under both acute and chronic elevated Aη-α levels, focusing on memory dependent tasks to study the behavioral output was deemed as a promising approach. To achieve acutely elevated Aη-α levels in vivo, we injected M108 into the CA1 hippocampal region or directly into the lateral ventricle of mice. We examined their behavior in CFC or T- maze, testing for impairments in contextual and spatial memory, respectively. The CFC, independent of the time point of injection, pre- or post-Conditioning session, indicated no impairments of contextual memory. The different stages of memory formation, acquisition, consolidation, and Retrieval were thus unaffected in CFC. We discussed the possible involvement of other brain structures like the amygdala and concluded that the CFC is not the optimal test to study the effect of a single M108 injection into the CA1 region. We changed our protocol to lateral ventricle injections, allowing the distribution of M108 throughout the brain and chose the T-maze to test for spatial memory impairments. Furthermore, the T-maze apparatus allowed us to inject M108 continuously throughout the acquisition phase of the task. We tested mice in a familiar vs. new arm paradigm with two different ITI, 10 min and one hour, and in a forced alternation task. When injecting mice once, no impairments in performance in the T-maze task were observed, independent of ITI. The forced alternation task was performed post 10 min ITI task, prior to which the mice received an injection. Here we started to see a decline in performance, as M108 mice scored lower than control, failing to surpass chance level
178 (50 %). However, only after the third injection of M108 for a 1 h ITI T-maze task did we start to observe significant impairments in performance for M108 injected mice. This data suggest multiple injections of M108 might be necessary to induce impairments in memory formation. We compared these observations with similar studies conducted on Aß injections and made suggestions for protocol alterations to determine whether multiple injections or toxicity post-injection are possible reasons for our results (see 4.1.1.4 Discussion). Memory-dependent behavioral tasks were also in our focus when we studied the behavior of transgenic mouse lines MISEPA2 and MISEPA4. The MISEPA2 line was tested in the spatial memory dependent task MWM but showed no signs of impairments. We identified the pool size or protocol set up as possible factors for the lack of a phenotype and suggested adding a reversal phase to the task, increasing the degree of complexity, thus increasing the likelihood of detecting a phenotype. The second memory dependent task performed on MISEPA2 was CFC. Here we observed two different outcomes depending on the order of experiments. As a stand-alone experiment, the freezing of MISEPA2 increased but when CFC was carried out post-MWM, we saw a reduction in freezing. As mentioned in the 4.1.2.3 Discussion, the MWM task is a stress-inducing experiment, and the altered stress levels could influence the freezing behavior of MISEPA2 mice previously tested in MWM. We therefore could not conclude as to clear alterations in the mnesic tasks for this line of transgenic mice. The behavioral assessment of the MISEPA4 line included MWM, CFC, and NOR, testing for impairments in recognition memory. We noticed only subtle alterations in performance for MWM and NOR, with MISEPA4 mice failing to surpass the chance level, and their overall performance not differing from WT littermates. The CFC protocol settings were changed significantly compared to previous testing. We limited the conditioning session to one shock at 0.3 mA to achieve a more moderate freezing outcome (see 4.1.2.3 Discussion). However, these changes reduced the freezing behavior in both groups, MISEPA4 and WT, below the point of meaningful interpretation. Again, these behavior data in this new MISEPA4 transgenic line were not clear-cut. We could not continue working on these lines due to a point zero in our animal house. Recently, the MISEPA2 line was rederived and reintroduced into our clean facility. New behavioral tests will be performed to continue robing these mouse models for cognitive deficits.
179 Comparing the Acute and Chronic elevated Aη-α Conditions
Both approaches, using acute and chronic elevated Aη-α levels, allow us to gain insight into the behavioral output of the observed synaptic alterations. The acute injections of M108 are a useful tool to study the changes at a particular time point, depending on the time of injection. This acute approach will assist us in comprehending the mechanisms behind the alterations and define the role of Aη-α within complex processes, for example, memory formation. Whereas, the transgenic MISEP lines offers insight into adaption processes under chronic elevated Aη-α levels. Thus, the chronic approach presenting a phenotype could be a useful tool in age studies. The behavioral assessment of acute injections of M108 faces some shortcomings. The number of injections seems to influence the performance of mice, and repeated injections increase the chances of inflammation in the brain. The cannula implantation itself is a heavy procedure, putting the animal under high stress, and may cause lesions at the implantation site. Furthermore, each mouse has to be individually verified for correct cannula implantation site post behavioral testing, which is a time-consuming task. Assuring the consistency of the implantation site and correct verification post-testing, as well as low mortality rates post- implantation and correct preparation of the M108 probe, make the acute approach prone to errors unbeknown to transgenic lines. The MISEPA2 line, on the other hand, is continuously overexpressing Aη-α from the onset of gene expression of the promoter used (P6-12 onwards). Levels of the endogenous APP may vary, depending on factors like stress or age, but the transgene expression will consistently elevate the Aη-α levels. Thus, we have a predetermined "On"-state, limiting our behavioral assessment to study the adaptive processes from thereon. While these new transgenic models are useful, ideally, we could optimize this type of model to better control the ‘when’ and ‘where’ of Aη-α expression in our studies. For this, we could for example use a technique that combines Cre/loxP- transgenic line specificity with a tetracycline- inducible system allowing region and period-specific gene expression. The tetracycline- inducing system utilizes complementary working tetracycline transactivator (tTA) or reverse tTA (rtTA), both artificially designed potent transcription factors. They bind to tTA responsive minimal promoters, thus activating them. The systems are called Tet-off and Tet-on and are controlled by doxycycline, a chemical inducer, who controls the binding of tTA or rtTA to the promoters. In Tet-off, doxycycline binds to tTA, initiating a conformational change that prevents further binding of tTA to the promoter, thus turning off the gene expression. The reverse occurs in Tet-on, where doxycycline coupling to rtTA is necessary for binding to the
180 promoter and launches gene expression (Belteki et al., 2005; Dogbevia, Marticorena-Alvarez, Bausen, Sprengel, and Hasan, 2015; T. Das, Tenenbaum, and Berkhout, 2016). This technique is undoubtedly a useful option for the future to study Aη-α expression in more detail. However, at the moment, combining the acute and chronic approaches is the best strategy to advance in unraveling the ongoing processes under elevated Aη-α levels.
Depletion of Aη-α levels
The second approach used in this thesis to hinder the η-secretase from cleaving APP at its recognition site was targeted towards my third objective to examine the alterations in synaptic plasticity and the behavioral outcome by the loss of η-secretase-dependent APP processing. We used a novel knock-out line APPΔEta, with a deletion of the η-secretase recognition site on APP created with Crisp/Cas9 as described in Material and Methods. Therefore, the homozygote offspring (HOMO) has a complete loss of η-secretase-dependent APP processing, while the heterozygote offspring (HET) has a partial reduction. The APPΔEta line allowed us to study the adaption of synaptic plasticity under the absence of η-secretase processed APP products in chronic conditions. HOMO mice show normal LTP and a deficiency in LTD, which can be reversed by an acute M108 application, revealing an essential role of Aη-α in LTD. We found no significant alterations in short-term pre-synaptic plasticity or basal synaptic transmission in HOMO mice, which was coherent with absent alterations observed in enhanced Aη-α conditions, M108 and MISEPA2 mice. Using this line, we need to move towards finer analysis of synapse function using for example patch-clamp electrophysiology, calcium imaging studies and biochemical analysis of proteins involved in LTD. The behavioral battery for APPΔEta mice was comprised of the memory-dependent tests T- maze, MWM and CFC, and was expanded by adding the Open field, the Light-Dark box, and the 3-chambers social interaction task, to gain a broader overview of the emerging phenotype. HOMO showed a propensity towards anxiety in the Open field and the Light-Dark box, which will have to be assessed further in other anxiety behavioral tasks. The 3-chambers social interaction task indicated sociability in all groups, but we were not able to discriminate clearly between familiar and novel mice in the third phase of the task. As presented in 4.2.3 Discussion, C57BL/6JRj mice, which is also the background of our APPΔEta mice, do not seem to display a robust performance in this task. We observed an inclination for impairment in spatial memory in the T-maze, which became more apparent in the MWM task, where HOMO showed significant impairments in platform location during the Probe. Despite the addition of a neutral
181 component to test for non-associative freezing and an extinction phase, we noticed no memory impairments. Suitability of the CFC to test mild impairments in hippocampal-dependent memory has been discussed previously in 4.1.1.4 Discussion and was examined again in 4.1.2.3 Discussion. Our conclusions drawn from the first evaluation of the behavioral profile of APPΔEta strengthens the case that Aη-α might represent a crucial component necessary for cognition. Using this line, we need to confirm these findings and continue the finely phenotype these mice for mnesic and other cognitive phenotypes. Ideally, we would be able to block the η-secretase activity or reduce Aη-α levels acutely, similar to the acute approach in elevating Aη-α levels. This time-dependent deactivation would allow us to assess the mechanisms behind the alterations in the absence of Aη-α in more detail. Timely controlled inhibition of Aη-α could be achieved with injections of a blocking antibody, as done by Pluvinage and colleagues for CD22, a canonical B cell receptor (Pluvinage et al., 2019).
APPΔEta and Alternatives: A Comparison
The APPΔEta line is not the first line to interfere with η-secretase activity. Komori and team announced in 2004 the creation of an MT5-MMP−/− mice line, removing the enzyme that is likely to be at the basis of the η-secretase activity (Komori et al., 2004). However, they targeted MT5-MMP directly, leading to its deactivation, therefore affecting all MT5-MMP associated targets. They report no dominant phenotype under physiological conditions, mentioning only a possibility to lower stress response towards immersion in water. No clear conclusion could be drawn from these negative results as a lack of phenotype could be due to compensation of the enzymatic activity by other members of the MMP family. This mice line has since been used to create a bigenic 5xFAD/MT5-MMP mice line to study the involvement of the η-secretase pathway in AD pathology (Baranger et al., 2017; Baranger, Marchalant, et al., 2016; Baranger, Khrestchatisky, and Rivera, 2016). These studies show a positive correlation between the absence of MT5-MMP and the decrease of AD symptoms, such as a reduction in cognitive decline and diminished amyloid pathology. However, the 5xFAD mice used to create the bigenic line, harbor 3 APP, and 2 PS1 FAD mutations, predetermining the occurrence of AD pathology traits (Elder, Gama Sosa, De Gasperi, and Gregory, 2010). Thus, combining the predetermined development of AD traits in 5xFAD mice and the numerous processes affected by knock-out of MT5-MMP, this bigenic line is not the optimal approach to study the role of the η-secretase, especially in a non-
182 pathological context. The new APPΔEta mouse model we studied is very different in this aspect as it can test the necessity of this APP cleavage, not modifying MT5-MMP (i.e., η-secretase) processing of other targets per se or the overall brain physiological environment. We cannot, however, exclude that in vivo diminution of the availability of one target (here APP) does not impact at all the processing of other MT5-MMP targets, as it might increase the availability of the enzyme of the processing of these other targets.
Comparing the Outcomes of Aη-α Level Modification
While individually interesting, combining our approaches: elevating and decreasing of Aη-α levels will further advance our understanding of the pathophysiological role of Aη-α. By linking the results obtained testing synaptic plasticity under enhanced and decreased conditions of Aη-α, we identify a crucial role of this protein in the generation of LTD, while the effect on LTP might be only due to abnormal elevation of this peptide. The recovery of LTD response after the addition of M108 in decreased conditions highlights the extent of Aη- α role in the mechanism of LTD formation. These observations formed the hypothesis of Aη-α acting as an enhancer of LTD at the post-synapse, crucial to the generation of LTD (see Figure 75).
Figure 75 Illustrating Aη-α as a neuromodulator crucial for LTD.
183 As discussed above, both lines, MISEPA2 and APPΔEta show alterations in synaptic plasticity and behavioral output. While we conducted a rough evaluation of the health of these two lines, observing their reproduction rates, comparing adolescent development, weight gain, and the assessment in the behavioral batteries, we will continue with a more in-depth screening. This screening will include expanding the behavioral batteries by modifying tests like MWM, 3- chambers social interaction task, and CFC to obtain more robust results. Adding anxiety-related tasks such as an elevated-plus maze or O-maze will serve to confirm the reduced anxiety in APPΔEta. We also will check for brain normality in these mice and adaptive modifications to the altered Aη levels. This could be done post-mortem by comparing brain volume and size of different regions. Alteration of APP processing homeostasis through regulation of the η-secretase pathway activity is another exciting path to pursue. Willem et al. (2015) reported enhanced activity of the η-secretase pathway through inhibition of BACE1, while Baranger and colleagues report no alterations in α -, ß- or γ-secretase activity in the absence of MT5-MMP in AD pathology (Baranger et al., 2017; Baranger, Marchalant, et al., 2016; Willem et al., 2015). However, considering the strict regulation of APP processing and activity-dependent interactions of the secretases, it is likely that alterations in the η-secretase pathway activity will affect the processing of APP through other pathways. Thus, our transgenic and knock-out mice lines could be useful tools to examine the interactions between the different APP processing pathways.
Probing the η-Secretase Pathway: Prospective Approaches
The field of η-secretase processing of APP is relatively new, with numerous inquiries still unaddressed. Our examination of the physio-pathological role of the Aη peptides in the brain is still ongoing. We are interested in the mechanism behind Aη-α's post-synaptic plasticity alterations. The utilization of techniques such as patch-clamp or immunofluorescence live imaging will be helpful tools to identify the ongoing processes on a finer level than feasible in field recordings. Additionally, we seek to refine our behavioral batteries to achieve broader phenotyping of our mice lines as previously discussed. A small group of females was included in the MISEPA2 behavioral experiments, but the composition of the different groups in the proceeding behavioral batteries included only male mice. Considering that women are more prone to develop AD, and evidence suggesting gender
184 being a factor to influence APP processing, any future behavioral batteries should include female groups to gain a more complete understanding of Aη-α's role (Alzheimer’s association, 2019; Schäfer, Wirths, Multhaup, and Bayer, 2007). The age of the subjects is another important factor mentioned in studies (Branchi and Ricceri, 2002; Jackson et al., 2017; Senechal et al., 2008). Depending on the protein, the levels of expression can change over time, indicating a crucial role in contemporaneous processes. Consequently, some phenotypes emerge in aged subjects, whereas others arise during ontogeny (Branchi and Ricceri, 2002). APP and MT5-MMP expression are increased during ontogeny (García-González et al., 2019; Hefter et al., 2019). Thus, our mice lines present an opportunity to study their role and interaction in neuronal development. The collection of CSF microdialysis's probes at different time points in both daily cycles and lifetime of mice could elucidate the physiological role of the η-secretase pathway via analysis of the protein levels in the probes. This tool could also be used to asses neuronal activity- dependent changes in Aη-α levels, for example, in combination with the Designer Receptors Exclusively Activated by Designer Drugs (DREADD) technique (Roth, 2016; Zhu et al., 2014). Virally mediated expression of DREADD allows to increase or decrease the firing of distinct neuron population. An i.p. injection of clozapine-N-oxide (CNO), the designer drug, for example, activates the DREADD system receptors M3Dq for an increase and hM4Di for a decrease in neuronal activity. This would allow us to manipulate neuronal activity in a timely manner and study its ability to alter APP processing via the η-secretase pathway.
185
186
6. Conclusion
187
188 6. Conclusion APP processing is a vast evolving field. With the new consensus of the necessity to investigate the physiological of APP and its proteolytic descendants, new pathways are emerging, further expanding the consciousness of the physiological importance of these proteins. My thesis set out to advance the understanding of the physio-pathological role of Aƞ in the brain and behavior. Since the discovery of the ƞ-secretase pathway in 2015 by Willem et al. (2015) and Wang et al. (2015), providing the first evidence of bioactivity of the Aη-α peptide no further advancements in unraveling Aƞ’s physiological role in synaptic plasticity have been reported. We performed an extensive analysis of synthetic Aη-α action on various parameters of synaptic plasticity. Our results show that both synthetic (M108) and cell-expressed recombinant Aη-α (Willem et al. 2015) impact synaptic plasticity at low nanomolar concentration, without affecting basal synaptic transmission. Notably, while Aη-α does not perturb pre-synaptic short-term plasticity, it significantly modifies the induction threshold of LTD and impairs LTP. These observations concluded in a first author manuscript "Aη-α, the secreted APP fragment processed by η- and α-secretases, acutely modulates post-synaptic plasticity mechanisms shifting the balance towards depression of synaptic strength.". Our observations on impaired LTP and unaltered basal synaptic transmission and short-term plasticity were confirmed under chronic conditions in the MISEPA2 line. Regarding the absence of LTD in the knock-out APPΔEta line, harboring a deletion of the η- secretase recognition site on APP, and restoration of LTD by addition of M108, we confirmed Aη- α as a crucial player in synaptic plasticity. These observations formed the hypothesis that Aη-α could act as a neuromodulator, enhancing LTD at the post-synapse and be crucial for LTD. Furthermore, the utilization of the MISEPA2 line and APPΔEta line in behavioral testing batteries allowed us to recognize the η-secretase pathway relevant to behavior outcomes, as we observed significant spatial memory impairments in the APPΔEta line. These results show that despite previous beliefs, other APP fragments may act as important physiological neuromodulators of brain function and associated behaviors. Alternations in η- secretase APP processing, and thus in quantities of these newly identified Aη peptides, could contribute to the synaptic dysfunctions and cognitive impairments observed in diseases, beyond Aß.
189
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XLV Statutory Declaration
I declare that to the best of my knowledge; the content of this thesis is my own work. This thesis has not been submitted for any degree or other purposes. I certify that the intellectual content of this thesis is the product of my own work and that I have not used other than the declared sources/ resources, and that I have explicitly marked all material which has been quoted either literally or by content from the used sources.
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