Science, Irving K. Barber Faculty of (Okanagan)
DSpace
UBCO
Zurfluh, Noah
Master of Science - MSc
University of British Columbia
Synaptic plasticity is a key cognitive function that allows the brain to remain dynamic. It functions by strengthening and weakening synaptic connections in an activity-dependent manner. Cellular mechanisms such as long-term potentiation (LTP) and long-term depression of synapses (LTD) can induce functional and morphological changes and thereby alter synaptic strength. These changes to synaptic activity and structural integrity are regulated by neurotrophic factors. Any disruption in neurotrophic function, whether due to mutations or variations in expression levels, is likely to lead to imbalances in LTD/LTP dynamics. These imbalances, in turn, contribute to structural and functional alterations often associated with mental illnesses and cognitive dysfunctions. Notably, a mutation in the pro-domain of the brain-derived neurotrophic factor, termed Met66, has been associated with decreasing hippocampal volume and increasing the risk for anxiety, depression, and cognitive dysfunction. Interestingly, Dr. Gibon demonstrated that Met66 can disrupt neurotransmission, however, the mechanism behind how Met66 can interfere with neural activity is unknown. Two proposed mechanisms for Met66 have been proposed; either based on reducing BDNF levels or ligand binding effects. Considering that Met66 can reduce hippocampal volume as well as disrupt neuronal activity and that LTD is the mechanism responsible for synapse weakening and elimination, it was hypothesized that Met66 induces LTD in synapses. This hypothesis was tested by looking at various aspects of the LTD, including morphology, protein expression, and phosphorylation. The results showed that Met66 alone did not significantly alter Ca²⁺ dynamics, morphological changes, or BDNF signaling pathways. However, both Val66 and Met66 affected the pre-synaptic compartment by decreasing the level of SYN-1, while Met66 also affected the post-synaptic compartment by decreasing the PSD-95 protein expression. These observations suggest that Met66 may not induce LTD of synapses by inducing changes in Ca²⁺ dynamics, developmental morphology or interfering with BDNF/TrkB signaling. However, while the precise mechanism remains elusive, our findings suggest that Met66 may impact neuronal activity by modulating specific changes within synaptic compartments. Future research could focus on understanding the role of Met66 in synaptic compartments, confirm its potential aberrant properties, and explore other aspects of LTD.
The Effect of the Brain Derived Neurotrophic Factor Pro-domain Variants, Val66 and Met66, on Neuronal Activity by Noah Zurfluh B.Sc., University of British Columbia, 2021 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Biochemistry & Molecular Biology) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) July 2024 © Noah Zurfluh, 2024 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis entitled: The Effect of the Brain Derived Neurotrophic Factor Pro-domain Variants, Val66 and Met66, on Neuronal Activity submitted by Noah Zurfluh in partial fulfillment of the requirements of the degree of Master of Science. . Dr. Philip A. Barker, Faculty of Science-Biology Supervisor Dr. Julien Gibon, Faculty of Science-Biology Co-Supervisor Dr. Isaac Lee, Faculty of Science-Chemistry Supervisory Committee Member Dr. Deanna Gibson, Faculty of Science-Biology Supervisory Committee Member Dr. Jonathan Little, Faculty of Health and Social Development University Examiner iii Preface This thesis represents the culmination of extensive laboratory work and analysis, all of which were conducted by me, Noah Zurfluh. I am proud to state that I was the sole contributor to the execution of all laboratory experiments and the primary author of this thesis. The identification and design of the research were collaboratively developed by Julien Gibon and myself. I performed all experiments and analyzed the resulting data unless explicitly stated otherwise in the thesis. Brett Bernard, an undergraduate student, assisted with the imaging of growth cones in one set of experiments and contributed to the analysis of that specific data. Svetlana Simtchouk was the creator of the PC12 P75NTR KO CRISPR cell line used in this thesis. Dr. Phil Barker and Julien Gibon provided invaluable guidance throughout the experimental processes, leveraging their expertise in their respective fields to enhance the research's quality and direction. Julien Gibon also supplied preliminary evidence that supported the thesis. For the writing of this thesis, I used generative artificial intelligence, ChatGPT, as a grammatical aid to ensure clarity and correctness. Ethics approval for the research was obtained from the UBC Research Ethics Board, under Certificate Numbers: A20-0105, A20-0106, A19-0274 A19-0275, ACUP_IWRRM_Apr2022luh13Noa33, and ACUP_RSCIPM_Oct2022luh13Noa57 as required. iv Abstract Synaptic plasticity is a key cognitive function that allows the brain to remain dynamic. It functions by strengthening and weakening synaptic connections in an activity-dependent manner. Cellular mechanisms such as long-term potentiation (LTP) and long-term depression of synapses (LTD) can induce functional and morphological changes and thereby alter synaptic strength. These changes to synaptic activity and structural integrity are regulated by neurotrophic factors. Any disruption in neurotrophic function, whether due to mutations or variations in expression levels, is likely to lead to imbalances in LTD/LTP dynamics. These imbalances, in turn, contribute to structural and functional alterations often associated with mental illnesses and cognitive dysfunctions. Notably, a mutation in the pro-domain of the brain-derived neurotrophic factor, termed Met66, has been associated with decreasing hippocampal volume and increasing the risk for anxiety, depression, and cognitive dysfunction. Interestingly, Dr. Gibon demonstrated that Met66 can disrupt neurotransmission, however, the mechanism behind how Met66 can interfere with neural activity is unknown. Two proposed mechanisms for Met66 have been proposed; either based on reducing BDNF levels or ligand binding effects. Considering that Met66 can reduce hippocampal volume as well as disrupt neuronal activity and that LTD is the mechanism responsible for synapse weakening and elimination, it was hypothesized that Met66 induces LTD in synapses. This hypothesis was tested by looking at various aspects of the LTD, including morphology, protein expression, and phosphorylation. The results showed that Met66 alone did not significantly alter Ca2+ dynamics, morphological changes, or BDNF signaling pathways. However, both Val66 and Met66 affected the pre-synaptic compartment by decreasing the level of SYN-1, while Met66 also affected the post-synaptic compartment by decreasing the PSD-95 protein expression. v These observations suggest that Met66 may not induce LTD of synapses by inducing changes in Ca2+ dynamics, developmental morphology or interfering with BDNF/TrkB signaling. However, while the precise mechanism remains elusive, our findings suggest that Met66 may impact neuronal activity by modulating specific changes within synaptic compartments. Future research could focus on understanding the role of Met66 in synaptic compartments, confirm its potential aberrant properties, and explore other aspects of LTD. vi Lay Summary Research has found that people who carry a mutation called Met66 in an important brain protein may struggle with learning and memory compared to those without it. My research focuses on understanding how this mutation affects the brain, hypothesizing that it disrupts connections between neurons. We investigated various aspects of how Met66 affects neuronal behavior and development. However, our results demonstrate that Met66 does not have a significant effect on these processes. To fully understand how the Met66 mutation impacts learning and memory, further research is needed on its effects on neuronal behavior and development. vii List of Abbreviations AMPA - α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (Glutamate Receptor) BDNF – Brain Derived Neurotrophic Factor CNS – Central Nervous System CTX- Cortical ERK – Extracellular Signal-Regulated Kinase LTD – Long-Term Depression LTP – Long-Term Potentiation MAPK – Mitogen-Activated Protein Kinase MET66 – BDNF pro-domain Val66Met mutation mEPSC – Mini Excitatory Post-Synaptic Current NGF- Neurotrophic Growth Factor NMDA - N-methyl-D-aspartate (Glutamate Receptor) NT-3/NT-4 – Neurotrophic 3/4 P75NTR – Protein 75 Neurotrophic Receptor PFC - Pre-frontal Cortex PF- Persistent Firing PLCγ – Phospholipase C gamma PSD-95 – Post-synaptic Density Protein 95 ProBDNF- Pro-Brain Derived Neurotrophic Factor ProNGF – Pro-Neurotrophic Growth Factor SorCS2 - Sortilin-related receptor containing protein 2 SYN-1 – Synapsin-1 Trk – Tropomyosin Receptor Kinase VAL66 – BDNF Pro-domain Wild-type viii Table of Contents Preface ..................................................................................................................................... iii Abstract ................................................................................................................................... iv Lay Summary ......................................................................................................................... vi List of Abbreviations ............................................................................................................. vii List of Tables ......................................................................................................................... xiii List of Figures ....................................................................................................................... xiv Acknowledgment ................................................................................................................... xv Chapter 1: Literature Review ................................................................................................ 1 1.1 Synaptic Plasticity and Synaptic Activity ....................................................................... 1 1.1.2 The Role of Calcium Signaling in Synaptic Plasticity ................................................. 1 1.1.3 The Formation of an Action-Potential and Signal Propagation ................................... 1 1.1.4 Pre-synaptic Release of Neurotransmitters .................................................................. 2 1.1.5 Post-synaptic Morphology ........................................................................................... 4 1.1.6 Synaptogenesis ............................................................................................................. 4 1.1.7 Long-Term Potentiation and Long-Term Depression .................................................. 5 1.1.7.1 AMPA Receptor Dynamics ................................................................................... 5 1.1.7.2 Known Factors Influencing LTD/LTP .................................................................. 6 1.2 Discovery of Neurotrophic Growth Factors ................................................................... 6 1.2.1 Rise of the Pro-Domain and Pro-Neurotrophins .......................................................... 7 ix 1.2.2 ProNGF vs. NGF signaling .......................................................................................... 8 1.2.3 ProBDNF vs. BDNF signaling .................................................................................... 9 1.3 Neurotrophic Receptors .................................................................................................. 10 1.3.1 Tropomyosin Receptor Kinase (Trk) ......................................................................... 10 1.3.2 P75 Neurotrophic Receptor (p75NTR) ...................................................................... 11 1.3.2.1 P75NTR in CNS ................................................................................................. 11 1.3.3 Role of p75NTR as a co-receptor .............................................................................. 12 1.3.3.1 SorCS2 ................................................................................................................ 12 1.3.3.2 TrkA .................................................................................................................... 13 1.4 BDNF Pro-Domain Met66 Polymorphism .................................................................... 13 1.5 Clinical effects of Met66 ................................................................................................. 14 1.5.1 Met66 in Major Depressive Disorder ........................................................................ 15 1.5.2 Met66 in Stress and Post-Traumatic Stress Disorder ................................................. 16 1.5.3 Met66 in Cognitive Decline ....................................................................................... 18 1.6 Molecular effects of Met66 ............................................................................................. 19 1.6.1 Met66 SorCS2/p75NTR Complex ............................................................................. 20 1.6.2 Met66 and LTD/LTP .................................................................................................. 21 1.6.3 Met66 and Synaptogenesis ........................................................................................ 21 1.6.4 Met66 and Neuronal Arborization ............................................................................. 22 1.7 Neuronal Growth Cones ................................................................................................. 22 x 1.7.1 Effect of Met66 on Growth Cones ............................................................................. 23 1.8 Promising Preliminary Evidence ................................................................................... 23 1.9 Hypothesis and Objectives ............................................................................................. 24 Chapter 2: Molecular effect of Met66 on Neuronal Activity ............................................ 26 2.1 Synopsis ............................................................................................................................ 26 2.2 Methods ............................................................................................................................ 29 2.2.1 Animal Ethics ............................................................................................................. 29 2.2.2 Cell cultures ............................................................................................................... 30 2.2.2.1 Preparing Dishes for Primary Hippocampal and Cortical Cell Cultures ............ 30 2.2.2.2 Dissection of wildtype C57BL6 Mice with embryo ........................................... 30 2.2.3 Calcium Imaging ........................................................................................................ 32 2.2.3.1 Preparing Cell Culture Dishes for Calcium Imaging .......................................... 32 2.2.3.2 Perform Fluo4 Calcium Imaging of Neurons using Zeiss Axioscope ................ 33 2.2.3.3 Analyzing Data Obtained via ImageJ and Excel ................................................. 33 2.2.4 Growth Cone Collapse ............................................................................................... 34 2.2.5 Neuronal Arborization ............................................................................................... 35 2.2.6 PSD95/SYN-1 colocalization .................................................................................... 36 2.2.7 Protein Level Quantification ...................................................................................... 38 2.2.7.1 Protein Analysis in Hippocampus ....................................................................... 38 2.2.7.2 Protein analysis in CTX ...................................................................................... 38 2.2.7.3 Lysate SDS-PAGE (Western Blot) ...................................................................... 38 xi 2.2.8 Statistical Analysis ..................................................................................................... 39 2.2.8.1 Determining Sample Size ................................................................................... 39 2.2.8.2 Statistical Tests .................................................................................................... 40 2.3 Results .............................................................................................................................. 41 2.3.1 Calcium Signaling ...................................................................................................... 41 2.3.2 Growth Cone Collapse ............................................................................................... 44 2.3.2.1 Impact of MET66 and VAL66 Variants on Growth Cone Collapse .................... 44 2.3.3 Neural Arborization ................................................................................................... 47 2.3.3.1 Impact of Val66 and Met66 Variants on hippocampal neuronal arborization ..... 47 2.3.4 PSD-95 and Synapsin-1 colocalization ...................................................................... 50 2.3.5 Synaptic Markers PSD-95 and Synapsin-1 ................................................................ 55 2.3.5.1 Changes to SYN-1 and PSD-95 Protein Levels .................................................. 55 2.3.6 Molecular Signaling in Cortical Neurons .................................................................. 57 2.4 Discussion ......................................................................................................................... 60 2.5 Chapter Summary ........................................................................................................... 69 Chapter 3: Characterizing p75NTR CRISPR KO PC12 Cells ......................................... 70 3.1 Synopsis ............................................................................................................................ 70 3.2 Methods ............................................................................................................................ 74 3.2.1 Culturing and Maintaining PC12 Cell lines ............................................................... 74 3.2.2 CRISPR P75NTR KO PC12 Cell lines ...................................................................... 75 xii 3.2.3 Single Clone isolation ................................................................................................ 76 3.2.4 Protein Analysis in PC12 ........................................................................................... 77 3.2.4.1 TrkA Pull-Down .................................................................................................. 77 3.2.4.2 Lysate SDS-PAGE (Western Blot) ...................................................................... 78 3.3 Results .............................................................................................................................. 78 3.3.1 Neurotrophic Signaling in PC12 Cells ....................................................................... 78 3.3.2 NGF induced TrkA phosphorylation .......................................................................... 79 3.3.3 NGF induced ERK, and PLCγ phosphorylation ........................................................ 80 3.3.4 The effect of Val66 and Met66 on P75NTR and TrkA signaling ............................... 82 3.4 Discussion ......................................................................................................................... 85 3.5 Chapter Summary ........................................................................................................... 89 Chapter 4.0: Conclusion ....................................................................................................... 91 4.1 Limitations of Study: .................................................................................................... 91 4.2 The effect of Met66 ....................................................................................................... 92 References .............................................................................................................................. 94 Appendices ............................................................................................................................ 114 Appendix A: Supplementary Raw Data ............................................................................ 114 Appendix B: Detailed Analysis Protocols ......................................................................... 119 xiii List of Tables Table 1: Part I Parameters - Image pre-treatment for enhancing ……………………...…36 Table 2: Part II Parameters - Pre-processing of segmented images ……………………..36 Table 3: Part III Parameters - Measurement of neuritic length and classification……..36 Table 4: The Alt-R CRISPR-Cas9 crRNA sequences……………………………………..75 xiv List of Figures Fig.1 Schematic of the propegation of an action potential………………………………...2 Fig.2 Schematic of proBDNF, its cleavage products……………………………………..14 Fig. 3 Effect of the Val66 and Met66 on Cch-induced calcium ………………………….44 Fig. 4 Impact of Val66 and Met66 on Growth Cone Collapse …………………………...46 Fig.5 Val66 and Met66’s effect on hippocampal neuronal arbor ………………………..49 Fig.6 Met66 or Val66 demonstrate no significant alteration in ………………………….54 Fig.7 Effect of Val66 and Met66 Variants on SYN-1 and PSD95 Levels………………...57 Fig.8 The impact of Met66 on molecular signaling in cortical neurons 7 DIV………….59 Fig. 9 Schematic of P75NTR acting as a co-receptor to TrkA……………………………71 Fig.10 30min NGF induced TrkA phosphorylation in PC12 …………………………….80 Fig.11 30min NGF induced ERK, and PLCγ phosphorylation in PC12 ………………..82 Fig.12 The effect of Val66 and Met66, phosphorylation of PLCγ and ERK ……………85 Fig. S 1 Raw Data Means: Impact of Val66 and met66 on Growth Cone……………...114 Fig. S 2 Raw Data Box Plot: Impact of Val66 and met66 on Growth Cone……...…….114 Fig. S 3 Raw Data Means: Val66 and Met66’s effect on hippocampal ………...………115 Fig. S 4 Raw Data Means: Met66 or Val66 demonstrate no significant …………..…...115 Fig. S 5 Raw Data Box Plot: Met66 or Val66 demonstrates no significant ……………116 Fig. S 6 Raw Data Means: Met66 or Val66 demonstrates no significant……………….116 Fig. S 7 Raw Data Box Plot: Met66 or Val66 demonstrates no significant……….……117 Fig. S 8 Raw Data: Effect of Val66 and Met66 variants on SYN-1 and PSD-95…….…117 Fig. S 9 Raw Data: The impact of Met66 on molecular signaling in …………………..118 xv Acknowledgment I would like to acknowledge my supervisors Julien Gibon, and Phil Barker, for their guidance, support, and invaluable insights throughout this thesis project. A special acknowledgment goes to Julien Gibon for not only providing thorough training in all the laboratory skills utilized in this paper but also for his eagerness to share his extensive knowledge and expertise. I would also like to express my gratitude to my laboratory members; Dr. Andres De Leon, Mahdi Abbasian, Tomas Filip, Michelle Lu, and Abbie Zhou for their collaborative spirit and unwavering willingness to assist with troubleshooting and problem-solving as well as Brett Bernard for his assistance with growth cone imaging and analysis. Special thanks to Svetlana Simtchouk for her role in creating the CRISPR cell line. Thank-you to Jonathan Chirkoff for his unwavering support throughout the entire project. Lastly, I would like to acknowledge my committee members Dr. Deanna Gibson, and Dr. Isaac Li for their valuable feedback, and genuine interest in the project. 1 Chapter 1: Literature Review 1.1 Synaptic Plasticity and Synaptic Activity Synaptic plasticity is essential for learning, memory, and overall brain function, as it allows neural circuits to adapt to new experiences and develop coping mechanisms. Synaptic plasticity refers to the ability of synapses, the connections between neurons, to undergo changes in strength in response to changes in neuronal activity1. These changes can occur through various mechanisms, such as alterations in the rate of signal propagation, modifications in the release of neurotransmitters, and changes in synaptic morphology and synaptogenesis. However, impairments in any one of these mechanisms result in detrimental neurological effects2. 1.1.2 The Role of Calcium Signaling in Synaptic Plasticity Excitatory neurons, constituting the largest population of neurons in the brain, exhibit a remarkable connectivity pattern. These neurons receive inputs from thousands of synaptic connections and reciprocate by forming thousands of synaptic connections onto other neurons3. The firing pattern of neurons can be altered by synaptic membrane properties such as the surface receptor concentration, synaptic morphology, and the effect of neuromodulators4. These alterations at excitatory synapse are key mechanisms for synaptic plasticity, mood regulation, and cognitive functions. 1.1.3 The Formation of an Action-Potential and Signal Propagation When a neuron is stimulated, voltage-gated sodium channels open, allowing for the influx of positively charged sodium ions into the cell, this change in voltage, in turn, opens further sodium channels until the propagation has reached an axon terminal (pre-synaptic 2 compartment)5. Once the pre-synaptic compartment begins to depolarize, voltage-gated Ca2+ channels (L-Type) open, allowing an influx of Ca2+, further depolarizing the cell6. The influx of Ca2+ is particularly important, as it activates the membrane fusion machinery, allowing neurotransmitters such as glutamate, and acetylcholine to be released into the synaptic cleft. Fig.1 Schematic of the propegation of an action potential, influx of Sodium and Calcium induce depolarization in pre-synaptic neuron, Release of neurotransmitters, and Binding and opening of NMDA and AMPA channels to being the process of depolerization on post-synaptic neuron. Created with BioRender.com. 1.1.4 Pre-synaptic Release of Neurotransmitters When an action potential arrives at the nerve terminal, Ca2+ influx first triggers the phosphorylation of synapsin-1 (SYN-1), responsible for tethering synaptic vesicles to the cytoskeleton as a reserve pool, releasing the synaptic vesicles from the cytoskeleton and allowing them to move to the readily releasable pool, where they can fuse with the presynaptic membrane7.Then, the membrane fusion machinery process occurs by Ca2+ binding and activating synaptotagmins18,. 3 Briefly, synaptotagmins, in conjunction with their co-factor complexin, engage with SNARE proteins (Soluble N-ethylmaleimide-sensitive factor Attachment Protein Receptors). These SNAREs function like molecular zippers, bringing the vesicle membrane (v-SNAREs) and the cell membrane (t-SNAREs) into proximity and securely zipping them together. This fusion enables the swift release of neurotransmitters into the synapse, where they bind to receptors on neighboring cells, transmitting signals. Acting as a molecular key, Ca2+ unlocks this process, allowing vesicles to release their contents through the rapid action of SNARE proteins in a matter of microseconds8,9. The dynamics of Ca2+ can control the amount and duration of vesicle fusion, ultimately regulating the firing pattern of the neighboring neuron10. Acetylcholine can bind nicotinic or muscarinic receptors (M). When bound to post-synaptic muscarinic receptors, Transient Receptor Potential-Canonical (TRPC) channels are activated, to induce Ca2+ increase into the cell cytoplasmic space. Acetylcholine that binds to nicotinic receptors on the pre-synaptic compartment can promote the influx of Ca2+, which in turn can promote the further release of neurotransmitters 11. Glutamate released from the pre-synaptic compartment binds 2-amino-3-(3-hydroxy-5-methyl-isoxazol-4-yl) propanoic acid (AMPA)-type glutamate receptors (AMPARs) and N-methyl-d-aspartate (NMDA)-type glutamate receptors (NMDARs) to induce excitatory post synaptic potentials (EPSP). When bound by glutamate, AMPARs allow the relatively rapid influx of potassium and sodium ions, while NMDARs open only when the synaptic membrane is strongly depolarized, allowing for the passage of calcium, potassium, and glutamate ions3. 4 1.1.5 Post-synaptic Morphology A major determinant of neuronal connectivity and function is neuronal morphology12. Aspects such as dendritic branching, spine size, density, and morphology, contribute to the efficiency of synaptic transmission and in turn, synaptic strength and brain connectivity12,13. Dendritic branching, referring to the extent of dendritic arborization, influences the neuron's capacity to receive and integrate incoming signals from other neurons. Meanwhile, spine size and density, which represent the small protrusions on dendrites known as dendritic spines, serve as sites of synaptic contact and modulate the strength of synaptic connections. Each morphological type of dendritic spine – mushroom, thin, stubby, and filopodia – represents a distinct stage of synapse development and is associated with varying levels of synaptic strength. For example, mushroom spines are typically associated with mature synapses exhibiting increased synaptic strength. These mature synapses are stabilized by the presence of post-synaptic density 95 (PSD-95) scaffolding proteins, which play a crucial role in anchoring receptors and signaling molecules at the synaptic membrane14. As dendritic spines undergo structural changes and maturation, they establish synaptic connections with axonal terminals of other neurons, contributing to the process of synaptogenesis. 1.1.6 Synaptogenesis Synaptogenesis is the intricate process of synapse formation that takes place during brain development to form essential neural networks15. In children, there is a substantial overproduction of synapses, exceeding adult levels by approximately 140-150%16. To counter this overproduction, the brain begins synaptic pruning, where the elimination of synapses follows the “use it or lose it” model, guided by mechanism such as LTP and LTD. 5 1.1.7 Long-Term Potentiation and Long-Term Depression The balance between long-term potentiation and depression (LTP, LTD) is one of the most studied forms of synaptic plasticity and represents a cellular model of informational storage17. LTD is a selective process that weakens specific sets of synapses by decreasing the quantity of surface receptors available and has been linked to spine shrinkage18,19. On the other hand, LTP results in the enlargement of dendritic spines through the persistent strengthening of synaptic transmission in an activity-dependent manner17,18. When LTD and LTP are balanced, they induce changes in synaptic plasticity which allows encoding of new information20. Issues arise when LTD becomes more active than LTP thereby reducing synaptic density21. An abnormal decline in synaptic density correlates with an increase in depression and cognitive decline22,23. 1.1.7.1 AMPA Receptor Dynamics Ca2+ plays a dual role in LTD and LTP, acting as a second messenger whose function is dependent upon the specific molecule to which it binds. For example, in LTP, Ca2+ binds to calcium/calmodulin-dependent kinase II (CaMKII), instigating phosphorylation events, while in LTD, it binds to calcineurin, initiating dephosphorylation events10. This is particularly important in mechanisms involving AMPA receptor (AMPAR) dynamics, where SNARE-mediated insertion or dynamin-dependent removal occurs during LTP and LTD, respectively. The heightened activity of CaMKII, influenced by the increased Ca2+ levels, contributes to the insertion of AMPARs, illustrating the intricate interplay between Ca2+ signaling and the molecular processes underlying the homeostatic dynamics of LTP and LTD19,24,25. 6 1.1.7.2 Known Factors Influencing LTD/LTP Neurotrophic growth factors (neurotrophins) are known regulators of LTD/LTP 26–28. These small homodimers are responsible for regulating synaptic transmission, morphological development, synaptic plasticity, cell proliferation and death29. Neurotrophins mediate these activities by binding either p75 neurotrophin receptors (P75NTR) or tropomyosin-related kinase (Trk) receptors30. A pro-neurotrophin consists of a cleavable pro-domain followed by the mature protein sequence. The functional consequence of cleavage results in either the activation of p75NTR via the pro-domain, or Trk by the mature neurotrophin29. 1.2 Discovery of Neurotrophic Growth Factors In 1946, a pioneering researcher, Dr. Levi-Montalcini was intrigued by the fact that upon transplantation of a mouse sarcoma tissue (tumour) into a chick embryo, the tumor appeared to stimulate the growth of fibers from neurons of the sensory ganglia into the tumor. Contrary to other theories at the time, she hypothesized that the transplanted tumor tissue induced hyperinnervation of chick organs by releasing an unknown agent that stimulated the growth and differentiation of developing nerve cells. Shortly thereafter, she and Dr. Stanly Cohen were able to purify the molecule from the submandibular glands of a male mouse. This discovery marked the first identification of a growth factor, later named neurotrophic growth factor (NGF)31,32. Based on transplantation, and deprivation experiments, scientists were able to demonstrate that neurons require factors, such as NGF, for proper development and survival. However, by 1982, no one had been able to isolate a molecule from tissues relevant to the 7 developing nervous system as NGF had been derived from the submandibular gland33. Dr. Yves-Alain Barde, from the psychiatric institute in München, DE, identified a factor in glioma-conditioned medium, distinct from NGF, that supported the survival of embryonic sensory neurons. Purifying this new factor from pig brain, he termed it brain-derived neurotrophic factor (BDNF), demonstrating its ability to induce fiber outgrowth in cultured embryonic chick sensory neurons34. Interestingly, the amino acid sequence of NGF and BDNF exhibited significant homology, and the structural similarities between these two proteins resulted in the categorization of a new family of proteins known as neurotrophins. Based on structural homology, scientists have now discovered NT-3, and NT-4 present in humans and neurotrophins have now been found in all mammals and most lower vertebrates35. Neurotrophins have undergone extensive study, emerging as crucial signaling molecules. They play roles in promoting neuronal survival, guiding the differentiation of neurons, and facilitating the growth of axons and dendrites. Neurotrophins contribute to the dynamic process of synaptic plasticity, influencing the strength and flexibility of connections between neurons36–39. Furthermore, neurotrophins are integral to neuroprotection, aiding neurons in withstanding stress and facilitating repair mechanisms in instances of injury. Given their many roles, it is unsurprising that dysregulation of neurotrophin signaling has been implicated in various neurological diseases and disorders such as dementia, parkinson’s disease, major depression, and schizophrenia40,41. 1.2.1 Rise of the Pro-Domain and Pro-Neurotrophins As with most growth factors, neurotrophins are synthesized as precursor peptides (proneurotrophins) consisting of a pro-domain, and a mature domain41. The proneurotrophin 8 homodimer (30-40 kD) is cleaved by either furin or proconvertases in the endoplasmic reticulum (ER) and Golgi body (GB) producing a 13 kD C-terminal mature neurotrophin and an aggregated pro-domain42,43. Initially, proneurotrophins were considered as the inactive pro-forms that, after cleavage, became the mature domain counterpart to exert their biologically active neurotrophic effects. However, subsequent research demonstrated that the neurotrophic pro-domain possessed distinct biological activity, that opposed mature neurotrophic function44. So much so, that the balance between neurotrophic and proneurotrophin became recognized as a regulatory mechanism of neuronal function and development45. Furthermore, the aggregated pro-domain that remained after cleavage of the proneurotrophin, was believed to act as a chaperon for the proper folding and dimerization of the mature molecule46. However, recent research has suggested that it also acts as an independent bioactive ligand involved in neuronal and synaptic development. However, specific mechanisms involved in this role remain relatively unknown47. 1.2.2 ProNGF vs. NGF signaling NGF and its precursor, pro-NGF, are well known for regulating neuronal function via the tropomyosin receptor kinase A (TrkA) and the p75NTR neurotrophic receptor respectively. Although mature NGF can bind the p75NTR receptor, it has a higher binding affinity to TrkA48. When NGF binds to its high-affinity receptor, TrkA, it initiates a cascade of intracellular events, including phosphorylation of tyrosine residues and activation of various signaling pathways such as Mitogen-Activated Protein Kinase/Extracellular Signal-Regulated Kinase (MAPK/ERK) and Phospholipase C y-isoform (PLCγ). This TrkA-mediated signaling promotes neuronal survival and growth. On the other hand, when pro-NGF binds p75NTR, it 9 activates signalling pathways associated with cell death, retraction and apoptosis49. The balance between proNGF and NGF signaling, their interactions with receptors, and the downstream effects play a crucial role in shaping the intricate processes of neurodevelopment and maintenance in the nervous system, and has been highly correlated with a broad spectrum of neurodegenerative disease pathologies50. 1.2.3 ProBDNF vs. BDNF signaling In contrast to NGF, which is expressed in peripheral sensory and sympathetic nerves as well as the brain, mature BDNF (mBDNF) and its precursor, pro-BDNF, is primarily expressed in the brain51–53. mBDNF is expressed and released in an activity dependant manner54. mBDNF binds the TrkB receptor (TrkB), to activate MAPK signalling, which leads to ERK1/2 activation and the phosphorylation of synapsin I and II. Synapsin is a neuronal protein that plays an important role in neurotransmitter release55. In the developmental context BDNF promotes the differentiation, growth, target innervation and survival of neurons56. The activity dependant release of BDNF occurs through secretory pathways via the activation (e.g., depolarization) of neurons following Ca2+ influx. This neuronal activity also regulates the transport of BDNF into dendrites, resulting in synaptic strengthening through processes such as long-term potentiation (LTP) and is considered to be responsible for the ability of mBDNF/TrkB to modulate synaptic plasticity and synaptogenesis57. On the other hand, pro-BDNF appears to elicit opposing effects via the p75NTR receptor, by facilitating long-term depression (LTD) of synapse, reduce spine density and downregulating spine complexity thereby negatively regulating synaptic plasticity21,58. 10 1.3 Neurotrophic Receptors 1.3.1 Tropomyosin Receptor Kinase (Trk) Tropomyosin receptor kinases (Trk) comprises a family of three receptors (Trk A, B, C) activated by one or more of the four neurotrophins (NGF, BDNF, NT-3, NT-4) depending on various affinity complexes59. For instance, NGF binds to TrkA, while BDNF and NT-4 bind to TrkB, and NT-3 binds to TrkC54. Through these receptors, neurotrophins regulate various cellular processes such as cell survival, proliferation, neuronal development (axon and dendritic growth), neurotransmission, and neuronal excitation, and under some circumstances induce cell death60. For example, according to the neurotrophic factor hypothesis, a developing neuron engage in competition for the released neurotrophins from nearby tissue, ensuring the survival of neurons at appropriate densities and specific regions61. A unique aspect of Trk receptors is that their cytoplasmic domains contain multiple tyrosine phosphorylation sites, facilitating the activation of intracellular signaling cascades including the MAPK, PI3-kinase, and PLCγ pathways. The diverse effects of Trk receptors depend on factors such as cell type, presence of co-receptors, and downstream signaling intermediates. Particularly noteworthy is the p75NTR receptor, which can be bound by both mature neurotrophins, and the pro-neurotrophins. Trk signaling can be interrupted or enhanced by the presence of p75NTR by influencing conformational changes, and the binding affinity of the respective neurotrophin59. 11 1.3.2 P75 Neurotrophic Receptor (p75NTR) The developing nervous system is shaped by regulating survival and death signals. This homeostatic function allows for signals, such as neurotrophic factors, to ensure the survival of required neurons, while eliminating others to allow for target innervation62. Among the key players in this regulatory network is the p75 neurotrophin receptor (p75NTR), also known as neurotrophic growth factor receptor (NGFR), which belongs to the tumor necrosis factor receptor (TNFR) superfamily. The ability of a receptor to engage in cyclic binding of ligands is facilitated by its varying affinities, allowing for functional versatility63. In the case of the P75 neurotrophin receptor (p75NTR), it exhibits a high affinity for pro-neurotrophins (e.g., pro-BDNF) and a low affinity for mature neurotrophins (e.g., mBDNF). To allow for cyclic binding of ligands, varying affinities allow the receptor to function in diverse ways. The high affinity to pro-neurotrophins (e.g., pro-BDNF) and low affinity for mature neurotrophins (e.g., mBDNF) plays a crucial role in determining the specific signaling cascade and cellular outcome initiated by p75NTR within the developing nervous system64 Structurally, p75NTR is characterized by a single transmembrane-spanning protein with an extracellular domain (ECD) and an intracellular domain (ICD) with an adaptor protein-binding region, followed by a death domain65. The diverse and complex role of p75NTR relies on which ligands (e.g., proBDNF, BDNF) and co-receptors (e.g., SorCS2, TrkA) are bound, to induce either a cell death or survival signalling cascade in neural development and connectivity62. 1.3.2.1 P75NTR in CNS In the CNS, p75NTR is abundantly expressed during embryonic and postnatal development but levels gradually reduce as the brain matures into adulthood66. In humans, the highest 12 expression exists in the cerebral cortex, followed by the hypothalamus, while in the mouse brain it is highly expressed in the retina and basal ganglia, followed by the hypothalamus67. The functions of p75NTR are context-dependent, and result in the activation of various signaling pathways that influence; neuronal death/survival, growth cone guidance, synaptic plasticity, tumor progression and neurodegenerative diseases66,68. As an illustration, the functional antagonism between mature neurotrophin-Trk survival signaling balances with pro-neurotrophin-p75NTR death signaling. This dynamic equilibrium fosters the capacity for homeostatic plasticity, contributing to the essential processes of proper brain maintenance and development. However, p75NTR's ability to interact with the Trk receptor and co-receptors, such as SorCS2, can alter this dynamic66,69. 1.3.3 Role of p75NTR as a co-receptor 1.3.3.1 SorCS2 Sortilin-related CNS-expressed receptor 2 (SorCS2) and sortilin are the binding contacts for the binding site in the pro-domain of neurotrophins, therefore the preferential interaction of proneurotrophins and pro-domains with p75NTR is dependent on the association of p75NTR and SorCS2 or sortilin70. Interestingly, the binding sites for p75NTR and SorCS2 on pro-NGF are partially overlapping, since pro-NGF exists in dimers, it is possible that one dimer can simultaneously fit into both SorCS2 and p75NTR to form a ternary complex and induce certain signalling processes within the cell71. SorCS2 and sortilin are central to the regulation of synaptic plasticity, secretory pathways and apoptotic signaling71–73. For example, SorCS2 association with p75NTR is required for pro-BDNF-dependent induction of synaptic long-term depression, as well as acting as a molecular switch governing p75NTR-mediated 13 pro-apoptotic pathway73,74. The interaction involving the pro-domain Met66 polymorphism and the SorCS2/p75NTR complex is provided in a subsequent section. 1.3.3.2 TrkA TrkA is activated through the autophosphorylation of specific tyrosine residues when bound by a mature neurotrophin (e.g., NGF). Of interest is the phosphorylation at Y490, which is involved in activating the signalling cascades associated with Phospholipase C y-isoform (PLCγ), Mitogen-Activated Protein Kinase/Extracellular Signal-Regulated Kinase (MAPK/ERK), and Phosphoinositide 3-Kinase/Protein Kinase B (PI3K/AKT). The activation of these pathways contribute to cell survival (ERK, PI3K) and Ca2+ influx75. TrkA physically binds p75NTR, acting as a co-receptor to increase the binding affinity of neurotrophins to TrkA during normal brain function and development76. This cooperative action serves to enhance the neurotrophin-induced TrkA survival signals65. Moreover, certain studies suggest that upon cleavage, the intracellular domain (ICD) of p75NTR may contribute to an increased potency in TrkA signaling by generating high-affinity binding sites for TrkA. However, it's important to note that an ongoing debate persists on this matter.65,77,78. 1.4 BDNF Pro-Domain Met66 Polymorphism Despite the homology of neurotrophins across mammals and vertebrates, single nucleotide polymorphisms (SNPs) in the neurotrophic gene have been identified in humans35,79. While many of these SNPs identified in the pro-domain are yet to be fully characterized in terms of function, a particular point of interest within the research community is a frequently occurring polymorphism in the BDNF gene (located on chromosome 11p14.1), present in approximately 20% of the human population35,79. This SNP involves a Valine-to- 14 Methionine substitution at codon 66 in the BDNF pro-domain and has been denoted by various names, including rs6265, Val66Met, pBDNFMet66, and simply Met6680. In carriers of the Met66 allele (Val/Met heterozygotes, Met/Met homozygotes), the pro-domain structure of the BDNF gene undergoes alteration. While the intrinsic biological activity of the mature BDNF protein remains unaffected due to the mutation's location, the cleaved Met66 pro-domain can induce improper protein folding, leading to diminished BDNF secretion81. Given the extensive involvement of BDNF in mental health coupled with the high prevalence of the Met66 polymorphism exclusive to humans, researchers initiated investigations to comprehend the clinical implications of carrying the Met66 SNP. Fig.2 Schematic of proBDNF, its cleavage products (pro-domain, mature BDNF), receptor complexes, and their respective downstream effects. 1.5 Clinical effects of Met66 In the human brain, BDNF expression is highest in the cerebral cortex and hippocampal formation, two critical brain regions that play significant roles in various aspects of cognition, memory and emotional regulation53,82. In the context of psychiatry, these regions are particularly important as alterations in their structure and function have been associated with 15 several psychiatric disorders83,84. If the expression of brain-derived neurotrophic factor (BDNF) is notably elevated in the cortical and hippocampal regions, it is anticipated that the impact of its cleaved pro-domain would be more pronounced. Intriguingly, studies have demonstrated that the presence of the Met66 polymorphism is associated with a reduction in hippocampal volume as well as changes to the prefrontal cortex (PFC)85,86. It is of little surprise, then, that the Met66 polymorphism is implicated in the etiology of various neuropsychiatric disorders and disease states, including depressive disorders, anxiety disorders, cognitive decline, and Alzheimer’s disease87–91. 1.5.1 Met66 in Major Depressive Disorder Major Depressive Disorder (MDD) is a widely prevalent psychiatric condition wherein individuals consistently endure low or depressed moods, reduced motivation, agitation, poor concentration, sleep disturbances, and even suicidal thoughts, leading to significant social or occupational impairment92. MDD is linked to functional impairment, poor quality of life, medical morbidity, and mortality93. The etiology of MDD is complex, including biological, genetic, environmental, and psychosocial factors94. The monoamine hypothesis, abnormalities with norepinephrine, serotonin, and dopamine, was heavily considered to be the groundworks behind depressive disorders. However, research has failed to demonstrate a primary dysfunction in the monoamine system in MDD95. The neurotrophic hypothesis of depression posits that decreased neurotrophic supports leads to neuronal atrophy and decreased hippocampal neurogenesis evident in MDD. Pathophysiological studies have demonstrated that decreased expression of neurotrophic factors, particularly the brain-derived neurotrophic factor, can be induced by stress and 16 increased by anti-depressive treatments96. It is not surprising, then, that decreased BDNF expression, seen in MDD, results in structural alterations to neurons in the hippocampus and PFC. These alterations encompass the regulation of neurogenesis, dendritic length, and spine density96–98. Advances in molecular genetics provide a means to examine how SNP’s in the BDNF gene may be involved in the etiology of depression. A meta-analysis of studies comparing the frequency of Met66 carriers with MDD cases and non-controls found an association of the Met66 polymorphism with MDD99. Moreover, there is increasing evidence that carriers of the Met66 polymorphism exposed to early life stress are at an increased risk for depression and present hippocampal volume alterations with changes to dendritic complexity100. Considering, that the pro-domain is known to act as a protein-folding chaperone and affect cellular trafficking, it makes sense, that Met66 has been associated with impaired intracellular trafficking of both pro-BDNF, and BDNF and decreased activity-dependant secretion of BDNF into the synaptic cleft81,100,101. These changes to both ProBDNF and BDNF trafficking and secretion induced by Met66 suggest a molecular mechanism behind the structural and functional changes seen in depression which are often unresponsive to antidepressant treatment81,96. However, more recent research suggest that the effect of Met66 may go beyond trafficking and protein folding, and that it may function as an independent ligand (detailed in section 1.6)101. 1.5.2 Met66 in Stress and Post-Traumatic Stress Disorder Post-Traumatic Stress Disorder (PTSD) is a stress induced mental health condition that can develop after exposure to psychological stressors during a specific, intense, potentially 17 psychologically traumatic event or series of events102. Although, PTSD is no longer considered an anxiety-related disorder, the etiology and treatment considerations overlap such as anxiety-related symptom expression103,104. Symptoms present as intrusive thoughts/memories, hyperarousal, sleep disturbances, and mood imbalances102. Symptoms of PTSD are thought to represent stress-induced changes to brain structure and function. Stress involves the release of various hormones (ex; cortisol) and neurotransmitters (ex; norepinephrine) that help prepare the body to respond to a perceived threat, yet homeostatic imbalances from these responses can lead to acute and chronic neurochemical changes that result in long-term alterations to particular brain circuits (hippocampus, amygdala, medial prefrontal cortex)104,105. Of note, while a smaller hippocampal volume is not the result of a traumatic experience, it is a risk factor for PTSD and has been found to be significantly reduced in PTSD patients100,106,107. Met66 has been correlated with decreased hippocampal volume, specifically carriers of the Met66 polymorphism exposed to early life stress present hippocampal volume alterations 100,108. Additionally, in some clinical studies assessing BDNF blood (plasma, serum) levels, there was a significant decrease in BDNF levels109,110. However, another study showed that BDNF plasma levels were increased and correlated with PTSD severity111. This is congruent with rat studies that demonstrates an acute stress response increases BDNF (plasma, hippocampal tissue) levels, possibly as a compensatory mechanism112,113. When looking at the allelic frequency of Met66 carriers with PTSD, the frequency of Met66 was higher in those with PTSD when compared with controls113,114. Additionally, veterans with psychotic PTSD carry more Met alleles than controls115. Notably, BDNF Met66 carriers have been found to drink more alcohol, have significantly higher anticipatory cortisol response and display higher anxious behaviour89. Considering that Met66 carriers have a 18 higher symptom severity, reduced hippocampal volume and fluctuating BDNF levels induced by stress, the Met66 BDNF allele may have a significant impact on vulnerability to PTSD116. 1.5.3 Met66 in Cognitive Decline Cognition is a broad term that refers to the mental processes and activities related to acquiring, processing, storing, and using information. Cognitive abilities can vary among individuals, and factors such as genetics, environment, and experiences can influence cognition117,117,118. Cognitive decline (CD) refers to a gradual reduction in cognitive abilities over time. This decline can affect various aspects of cognition, including learning, memory, and decision-making119. It is often associated with aging, and conditions such as neurodegenerative diseases (e.g., Alzheimer's disease, dementia), but it can also result from other factors such as brain injuries, and medications119–121. Subjective cognitive decline (SCD) occurs when the frequency of confusion and memory loss are self-reported to increase. It has been considered as one of the earliest forms of more severe cognitive disorders such as dementia122. Of note, a reduction of the entorhinal cortex and medial temporal lobe volume, including the hippocampus, amygdala and temporal horn has been found in SCD123–126. While subjective cognitive decline (SCD) is acknowledged as an early warning sign for cognitive disorders, there is growing interest in understanding the contribution of genetic factors, such as the Met66 polymorphism, to shaping cognitive outcomes. Initial clinical investigations focused on the impact of the Met66 variant on hippocampal learning and episodic memory. It appeared that Met66 carriers exhibited poorer 19 episodic memory, and abnormal hippocampal activation (e.g., fMRI)81. As interest in the polymorphism grew, subsequent studies discovered that human Met66 carriers had reduced hippocampal activation (e.g., episodic-declarative memory tasks), performance (e.g., delayed recall) and volume (e.g., structural MRI)85,86,127,128. The prefrontal cortex of Met66 carriers displayed reduced scores in prefrontal cognition, visual and working memory tasks (e.g., Wisconsin card sorting test) and decreased grey matter volume85,118,129. By recognizing SCD as a potential early-detection strategy for the onset of Alzheimer’s disease (AD), unraveling the genetic blueprint of cognition and cognitive decline through studies on the Met66 polymorphism may aid in the enhancement of detection and mitigation efforts for AD and other neurodegenerative diseases. 1.6 Molecular effects of Met66 The molecular mechanism underlying the altered clinical manifestations of Met66 carriers has garnered interest and is mainly studied in vitro cell culture systems130. It has been established that the role of the BDNF pro-domain is to act as a folding and trafficking chaperone for the cleaved, mature BDNF (mBDNF). It is of no surprise, then, that an SNP in the pro-domain decreases its binding affinity to mBDNF by forming a more stable complex, compare to its wild-type counterpart (Val66)131. This change in affinity is likely the reason behind the three main BDNF trafficking defects that have been found in Met66 transfected neuronal experiments: 1) decreased BDNF distribution in neuronal dendrites, 2) decreased BDNF targeting to secretory granules, and 3) impaired secretion of BDNF81,132,133. Given that the Met66 polymorphism can manifest as heterozygous (Val/Met) or homozygous (Met/Met), it has been observed that Met66 can also influence the trafficking of Val66 by reducing sorting efficiency in the regulatory pathway133. The decrease in BDNF levels, a crucial regulator of 20 neuroplasticity, has the propensity to affect both morphological and synaptic signaling. This reduction in BDNF has been observed in psychiatric conditions discussed earlier (e.g., major depression). Consequently, these conditions often exhibit morphological and synaptic signaling defects, reflecting the impact of decreased BDNF levels on neuronal structure and function134. 1.6.1 Met66 SorCS2/p75NTR Complex Sortilini is a Vps10p domain protein highly enriched in the CNS. Sortilin was shown to bind the pro-domain of NGF, acting as a cell-surface coreceptor with p75NTR to mediate proNGF-induced cell death135. Given the sequence homology across the neurotrophic family, particularly between NGF and BDNF, and given that sortilins function as a Golgi trafficking protein, Chen et al., 2005 investigated how sortilin interacted with the BDNF pro-domain and trafficking. As expected, sortilin was found to be necessary for BDNF sorting and trafficking through the secretory pathway. It has been found that sortilin forms a high-affinity complex with proBDNF and that sortilin stabilizes proBDNF from proteolytic degradation46. Moreover, sortilin interacts specifically with the BDNF pro-domain region containing the Met66 mutation, with a lower binding affinity132. This conformational alteration is theorised to be, in part, associated with the decreased secretion of BDNF seen in mutant carriers. Considering, that the binding domain in the pro-region contains the SNP, research shifted its focus towards investigating the potential effects of the isolated pro-domain as an independent ligand, rather than solely examining alterations in mBDNF trafficking and secretion. It has been established that both the WT (Val66) and mutated (Met66) pro-domains are secreted in the hippocampus and exist primarily as disordered structures. However, the 21 Met66 pro-domain has a stronger binding affinity to SorCS2. The distinct interaction between Met66 and Val66 with SorCS2 can result in differential activity downstream of p75NTR 101. 1.6.2 Met66 and LTD/LTP Notably, Met66 knock-in mice exhibited a decrease in synaptic plasticity by decreased neurotransmission and selectively reduced NMDA receptor-dependant LTD in the hippocampus, medial prefrontal cortex and the central amygdala136. However, in the dorsal striatum, the polymorphism enhances glutamatergic transmission but decreases LTD and lowers the population spike amplitude137. On the other hand, transgenic mice deficient in BDNF have shown a reduction in LTP that is rescued with the endogenous addition of BDNF138. Whether the mutant pro-domain acts independently as a ligand for SorCS2, functions solely as a chaperone protein for mBDNF, or operates through both mechanisms to decrease LTD is unknown. 1.6.3 Met66 and Synaptogenesis The Met66 pro-domain, compare to Val66, was found to induce disassembly of mature mushroom spines, via SorCS2/p75NTR, and eliminate hippocampal synapses139. Mushroom spines have been associated with mature synapses of increased strength, that are stabilized by post synaptic density 95 (PSD-95) scaffolding proteins14. It is of no surprise, then, that the overall PSD-95 density was also reduced by Met66 application in vitro139. However, some aspects of Met66 biological activity have proven controversial, with some claiming the wild-type (Val) pro-domain is capable of decreasing dendritic spine density140. This controversy is 22 investigated in this thesis by examining the effects of both Val66 and Met66 on synaptic density. 1.6.4 Met66 and Neuronal Arborization Neural arborization refers to the complexity of dendritic and axonal extensions essential for synaptic connections between neurons. Disrupted arborization, such the number of branchpoints, have been reported in neurodevelopmental disorders141. Notably, studies involving Met66 knock-in mice revealed a reduction in the complexity of dendritic arborization within the hippocampus85,142. While these findings provide support for the alterations induced by Met66 in synaptogenesis, they do not conclusively establish whether the Met66 pro-domain functions as an independent ligand through SorCS2/p75NTR to initiate branching changes or if its effects are contingent upon changes in BDNF levels. Clarifying the specific mechanisms underlying the influence of Met66 on synaptic and branching dynamics may shed light on its implications in neurobiological processes. 1.7 Neuronal Growth Cones During development a neuron begins to grow neurites, which are branch like processed that extend from the neuronal soma. One of these processes forms a growth cone, a triangular thorny processes, which later develops into the axonal portion of a synapse143. A growth cone is able to interact with its environment, responding to chemical or mechanical cues that guide the neurons to the right location and create a synapse144(p38). Specifically, a growth cone will respond by selectively stabilizing, and destabilizing actin and microtubule cytoskeletons to allow for growth in the preferred direction145. If a repulsive signal is identified the filopodia 23 and lamellipodia in the growth cone will collapse resulting in a retraction146(p6). The growth and retraction process allows for the formation of neuronal networks143,145. 1.7.1 Effect of Met66 on Growth Cones Neurotrophic factors, such as BDNF or NGF can interact with receptors on the growth cone’s surface, triggering an intracellular cascade that modulates the cytoskeletal dynamics147,148. Alterations, such as a SNP in neurotrophins, can influence the synaptic network organization, which can increase the occurrence and progression of neuropsychiatric disorders143,145. Anastasia et al., used a growth-cone retraction assay to assess the bioactivity of Met66 and Val66 as an isolated ligand. It was discovered that Met66 could induce growth-cone retraction, unlike Val66, but only on p75NTR containing hippocampal rat neurons101. 1.8 Promising Preliminary Evidence Dr. Julien Gibon hypothesized that Met66 has biological properties on neuronal activity that are lacking in Val66. To test this, he performed experiments on cortical pyramidal neurons using electrophysiological recording. Interestingly, Met66 was able to inhibit a form of neuronal activity called persistent firing. Persistent firing is the continuous neurotransmission of a neuron even when the initial stimulus is no longer present and is thought to be a mechanism behind working memory. Working memory being the ability to maintain a thought in the brain long-enough until the respective task has been completed149. Additionally, Met66 reduced mini excitatory post-synaptic current (mEPSC) frequency in a SorCS2- and p75NTR-dependant manner. mEPSC is the spontaneous postsynaptic current that occur at excitatory synapses when a synaptic vesicle releases neurotransmitter into the synaptic cleft150. Taken together, these data 24 suggest that Met66 induces LTD, perhaps by altering neurotransmitter release, causing morphological changes at the synapse, or causing disruptions in signalling pathways, in a SorCS2/p75NTR dependant manner. The decrease in mEPSC frequency could be due to the direct inhibition of neurotransmitter release or to a disruption in synaptic structure. Considering that the signalling pathway of Met66 via SorCS2/p75NTR is relatively unknown, the aim of this thesis was to uncover the mechanism by which Met66 inhibits persistent firing and reduces mEPSC. 1.9 Hypothesis and Objectives This thesis investigates the effect of the pro-domain variant, Met66 and hypothesizes that the Met66 variant induces LTD of synapses. To test this hypothesis, I have outlined several objectives. First, I explore the effect of both Met66 and Val66 variants on calcium flux in neurons stimulated by carbachol, where I expect only Met66 to decrease calcium flux. Secondly, I investigate the influence of Met66, in comparison to Val66, on synaptic morphology using a comprehensive approach. This involves conducting a growth cone assay to assess changes to the pre-synaptic compartment, evaluating dendritic arborization to understand structural changes to the post-synaptic compartment, and measuring synaptic density to quantify alterations in overall synaptic connections. I hypothesized that Met66 would induce growth cone collapse, impact dendritic arborization and decrease synaptic density. Lastly, I seek to examine the impact of Met66 on the signaling pathway activated by BDNF/TrkB. This involved assessing the phosphorylation levels of key signaling molecules to elucidate any disruptions caused by the Met66 variant. Considering that Met66 complexes, with SorCS2/p75NTR, and p75NTR has been shown to interfere with TrkB signaling, I expected to see a decrease in both baseline and BDNF/TrkB induced protein activation. 25 Through these objectives, I aimed to gain a deeper understanding of how the Met66 variant influences synaptic plasticity and contributes to neurological disorders. 26 Chapter 2: Molecular effect of Met66 on Neuronal Activity 2.1 Synopsis Approximately 20% of the global population is affected by anxiety and depression, making these mental illnesses highly prevalent worldwide151,152. Notably, nearly half of those diagnosed with depression also experience symptoms of anxiety153,154. Moreover, cognitive impairments often accompany anxiety and depression, reaching a severity that can mimic dementia155,156. The intricate interplay of these conditions involves various brain regions, with the hippocampus emerging as a key player in both structural and functional abnormalities157–160. The alterations in hippocampal structure and function, stemming from disruptions in neuronal communication, appear to contribute significantly to cognitive decline by diminishing synaptic plasticity. Synaptic plasticity, crucial for the brain's ability to adapt and change the synaptic strength, and can be regulated by neurotrophins161. This family encompasses; Neurotrophic Growth Factor (NGF), Brain Derived Neurotrophic Factor (BDNF), neurotrophin-3 (NT-3), and neurotrophin-4/5 (NT-4/5). These factors play pivotal roles in the development, maintenance, and survival of neurons within the nervous system149,162–164. In this thesis, our focus is on a single nucleotide polymorphism (SNP) in the pro-domain of the BDNF gene. The SNP constitutes a change from valine to methionine, present in approximately 25% of the human population, and has been clinically associated with an elevated risk for anxiety, depression, and cognitive dysfunction compared to those with wild-type Val6680,101. Further investigations have revealed that Met66 carriers also exhibit a decrease in hippocampal volume, suggesting the potential impact of this genetic variation on brain structure and function86,108. 27 While traditionally considered as a mere folding chaperone or mBDNF trafficking protein post-cleavage, recent revelations expose the pro-domain's independent physiological responses165,166. Notably, in vitro studies demonstrated that Met66 impedes synaptic plasticity, specifically affecting long-term depression (LTD) by downregulating the activity and expression of essential synaptic receptors167. Synaptic plasticity, partially regulated by the balance between LTD and long-term potentiation (LTP), is essential for the strength, density, and adaptability of synapses168. LTP and LTD are highly influenced by changes in calcium flux within neurons. In LTP, the induction phase involves an influx of calcium. This elevated calcium concentration leads to the activation of signaling pathways that enhance synaptic strength by upregulating receptors on the postsynaptic membrane. Conversely, LTD is associated with a more prolonged and moderate increase in calcium levels. During LTD induction, calcium dynamics play a pivotal role in signaling cascades that result in the weakening of synaptic connection by reducing downregulating receptors on the post-synaptic membrane24,169. However, the molecular mechanism behind how Met66 can impair LTD is unknown. As alterations in calcium dynamics are a key component of LTD, our first objective aimed to evaluate the effect of Met66 on calcium flux in cortical neurons, hypothesizing that this variant is capable of disrupting calcium signaling. There is a clear effect of the BDNF pro-domain in the mechanisms underlying neuronal synaptic dynamics but whether the Met66 SNP truly alters the effect attributed to the BDNF pro-domain (Val66) is still a debated topic and in vitro assessments of comparing both pro-domains have come to conflicting conclusions101,130,139,166,170. 28 Considering the effect Met66 has on LTD impairment, there may be morphological alterations at the synapse. Two independent research laboratories have investigated the impact of Met66 on synaptic morphology and function. Focusing on the pre-synaptic compartment, an initial study determined that the Met66 variant, but not the wild-type Val66 variant, can acutely alter axonal morphology by inducing growth cone collapse101. Concurrent with this data, in the post-synaptic compartment, the effect on dendritic morphology and fear circuitry, a form of learning and memory retrieval was investigated. The report found that Met66, when compared to Val66, disassembled dendritic spines and reduced synaptic density in hippocampal neurons139. However, another study claims that Val66 can also alter spine morphology140. To address this knowledge gap, our second objective sought to thoroughly examine and characterize the impact of Met66, in comparison to Val66, on synaptic morphology by employing a growth cone collapse assay, assessing dendritic arborization, and measuring synaptic density. Considering Met66's observed impairment of LTD, we hypothesized that Met66, not Val66, can alter synaptic morphology by inducing growth cone collapse, diminishing dendritic arborization, and reducing synaptic density in hippocampal neurons. Building upon our hypothesis of Met66's negative impact on synaptic morphology, underlying the impairment seen in LTD, we delved into its mechanistic role as a ligand for the sortilin-related Vps10p domain-containing receptor 2 (SorCS2). SorCS2 is a member of the VPs10p-domain receptor family, responsible for protein transport and signal transduction within cells171. Research indicates that Met66 alters its binding affinity to mBDNF by forming a more stable complex compared to its wild-type counterpart (Val66). This stable complex formation leads to reduced BDNF trafficking and secretion131. Notably, when Met66 binds to SorCS2, it acts as a co-receptor with p75NTR, forming a ternary complex172. The downstream 29 effects of p75NTR activation are generally associated with neuronal dysfunctions, degeneration, and acute dysregulation of synaptic functions which opposed BDNF/TrkB signaling173,174. Despite this understanding, the specific functional implications of Met66 on LTD, whether it acts solely as an independent ligand or is influenced by defective BDNF trafficking, remain unclear. Knock-in mice expressing Met66 instead of Va66 have not yielded conclusive evidence to rule out these potential scenarios. To achieve this, our final objective was to investigate the signaling pathway activated by Val66 versus Met66 and BDNF. As mentioned earlier, BDNF activates TrkB to initiate intracellular signaling cascades such as the MAPK and PLCγ pathways. These pathways involve downstream signaling intermediates like ERK and PLCγ, which play critical roles in various mechanisms of LTD. For instance, ERK, a member of the MAPK family, is involved in actin remodeling and neurite outgrowth, while PLCγ contributes to calcium regulation and neurotransmitter release. Our study aimed to characterize the impact of Met66 on ERK and PLCγ activation and to assess its disruptive effects on BDNF/TrkB signaling by measuring the level of phosphorylation. We hypothesized that Met66 will disrupt normal BDNF signalling, as well as decrease baseline PLCγ and ERK activity. 2.2 Methods 2.2.1 Animal Ethics All procedures were approved by the UBC Animal Care Committee. The appropriate certifications provided by the Canadian Council on Animal Care and the UBC animal care program have been attained by all team members. For colony maintenance, wild-type (WT) C57BL6 mice were housed in a 12-hour dark/light cycle, as either single housed breeding 30 males or 2-3 virgin or non-virgin females in a single cage. To set up a timed pregnancy (TP) 1-2 females were housed with 1 male for one night and male and female embryos were combined for use in cell cultures. 2.2.2 Cell cultures 2.2.2.1 Preparing Dishes for Primary Hippocampal and Cortical Cell Cultures To generate primary cultures of embryonic E14 wild-type (C57B16) cortical neurons, either 14mm glass coverslips or 6 well plates were washed for 24hr with 70% filtered methanol on a shaker table at 4°C. Then, the dishes were washed once with sterile H20, left to dry, and coated with 0.5g/l of poly-D-lysine in borate buffer (100mM, PH 8.5) and placed in the incubator at 37°C (21% O2, 5% CO2) 2 hrs prior to plating. Once the dissection was finished, under sterile conditions, the dishes were washed once with H20 and left to dry before seeding. To generate a primary culture of embryonic E17 wild-type (C57B16) hippocampal neurons, dishes containing either a 14mm glass coverslip or 35mm polymer (Ibidi, Germany) treated slip were washed for 24hr with 70% filtered methanol on the shaker table at 4°C. Then the dishes were washed once with sterile H20, left to dry and then coated with 0.5g/l of poly-L-lysine in borate buffer (100mM, PH 8.5) and placed in the incubator at 37°C (21% O2, 5% CO2) 2hrs prior to plating. Once the dissection was finished, under sterile conditions, the dishes were washed once with H20 and left to dry before seeding. 2.2.2.2 Dissection of wildtype C57BL6 Mice with embryo To produce primary neuronal cultures, embryonic day (E) E14 embryos were used for cortical neuron cultures and E17 embryos were used for hippocampal neurons. Pregnant 31 C57BL female mice were given a single one-time dose of tribromoethanol (250 mg/kg), also known as avertin, injected intraperitoneally (5 ml/kg) to induce deep anesthesia prior to euthanasia by cervical dislocation. Deep anaesthesia was confirmed by a lack of withdrawal response after forceps-mediated paw pinch. Embryos were extracted and placed on ice in 15ml HBSS. The embryonic brains were then separated, meninges were removed, and the hemispheres were severed. Here either the entire cortex was removed, or the hippocampus was carefully carved out and placed in 100µl HBSS on ice. Once all the hippocampi were extracted, the HBSS was removed. To start the dissociation process 400μl HEPES-buffered sterile saline (HBSS), 2.5g/l trypsin and, 3mg/l DNAse was added to the hippocampi and then placed in the warm bath (37oC) for 15min. Every 5 min the microcentrifuge tube was tapped without suspending the tissue. Thereafter, the supernatant was carefully removed, and cells were resuspended with 400μl pre-warmed DMEM complete (10% FBS 1% P/S) and broken down into individual cells by repetitive aspiration using 3 sterile fire-polished Pasteur pipettes, each with a decreasing diameter. The solution was then passed through a 40μm sterile filter to remove larger cell clumps and debris. The cortices required only mechanical dissociation with fire-polished pasture pipettes as described with the hippocampi. The dissociated cell solution was cell-counted to attain experiment-specific cell densities: For short-term growth cone and arborization 3,500 cells/200µl was pipetted onto a glass cover slip, long-term synaptic colocalization required 35,000cells/500µl on a plastic polymer dish and protein analysis used 100,000/1ml in a 6 well plate. They were then left to settle for 2hrs in the incubator at 37°C. The DMEM media was removed and replaced with the following appropriate neurobasal media for the respective experiment. 32 For short-term (3-4 Days in vitro (DIV)) hippocampal neurons, 2ml neurobasal complete (2% B-27, 1% Penicillin/Streptomycin (P/S), 1% 500uM L-Glutamine) was added and then placed back in the incubator until ready for experimental use. For long-term (DIV17) hippocampal neurons, 2ml neurobasal complete (2% B-27, 1% P/S, 1% 500uM L-Glutamine) was added, then on DIV7 of incubation, 1ml neurobasal complete growth media (2% B- 27, 1% P/S, 1% 500uM L-Glutamine, 4μM cytosine-1-β-D-arabinofuranoside, 1mM Pyruvate) was added. They were incubated for 17 days, with media changes every 7 days (exchange of 1ml) to allow for the grow of neuronal processes before experimental use. For short-term (Div.7) cortical neurons, 2ml neurobasal complete (2% B-27, 1% P/S, 1% 500uM L-Glutamine) was added and then placed back in the incubator until ready for experimental use. 2.2.3 Calcium Imaging 2.2.3.1 Preparing Cell Culture Dishes for Calcium Imaging E14 cortical neurons were incubated for 4-7 days to allow for the grow of neuronal processes before experimental use. Upon retrieval of the incubated dish, the neurobasal media was removed and washed with a Tyrode solution containing (in mM): 140 NaCl, 5 KCl, 2 CaCl2, 1 MgCl2, 10 HEPES, 10 glucose. The pH was adjusted to 7.4 with NaOH. After the first two washes, 1ml of Tyrode solution was added to the dish and then 100ml was suspended in a pipette and mixed with Fluo4 (1.8mM) via the aspiration method in its tube. This mixed solution was added back to the dish and incubated in the cell culture incubator under 95% 33 O2/5% CO2 at 37°C for 10 minutes allowing the Fluo4 indicator to be hydrolyzed and thus trapped in the cells. Two more washes with Tyrode were applied to the dish and cells were incubated for an additional 20 minutes under the same conditions to allow the removal of extracellular Fluo4 and allow complete hydrolysis of intracellular fluo4. 2.2.3.2 Perform Fluo4 Calcium Imaging of Neurons using Zeiss Axioscope A final two Tyrode washes were completed and 1ml Tyrode solution was added to the dish. The dish was placed on the stage of the Axioscope. Using the 20X magnification objective lens the subjective cells were located with the fine focus. The position was then locked, and the calcium flux was recorded via live fluorescent imaging at an image per second. A baseline of 50 seconds was established during which the cells were recorded without any disturbance. After 50 seconds the appropriate volume of carbachol solution was added to produce a final concentration of 50µM and recorded for another 150 seconds (2.5min.). After a total recording time of 200 seconds, the data was saved onto its respective file. 2.2.3.3 Analyzing Data Obtained via ImageJ and Excel ImageJ was used to analyze image stacks recorded during the experiment for analysis and cell fluorescence quantification. Three data points were selected in areas without cells to represent the background and the rest of the data points were applied to the cells present in the frame which averaged between 40-50 cells. This data was imported to Excel to be converted into an appropriate graph. The mean background was calculated for each image and then subtracted from each cell data point. This information allowed for the normalization of the data to be calculated by dividing the isolated cell data by the mean baseline. 34 2.2.4 Growth Cone Collapse Cells were grown for 3 days on glass cover slips with poly-D-lysine as described previously. The cells were plated at a low density to produce isolated neurons. They were treated on DIV3 with either neurobasal, 50ng/ml Val66, 50ng/ml Met66, 50ng/ml proNGF, or 50ng/ml ProBDNF for 1hr. After a respective treatment, cells were fixed for 15 minutes at room temperature in a 4% paraformaldehyde solution, permeabilized for 20 minutes with 0.2% Triton X-100, 1% BSA in phosphate buffered saline (PBS), washed 3 times with PBS, blocked for 1h in 0.02% Triton X-100, 1% BSA in PBS and then incubated overnight with the primary antibody (Chicken anti-MAP-2) diluted in 0.02% Triton X-100, 1% BSA in PBS. The next day the dishes were warmed to room temperature, washed 3 times with PBS, then incubated with secondary antibody (anti-chicken Alexa 633) in 0.02% Triton X-100, 2.5% BSA, 5% goat serum in PBS for 1hr. After 3 more washes with PBS, phalloidin (1% BSA in PBS) was added and incubated at room temperature for 30min. The dishes were washed 2 more times with PBS and then DAPI diluted in 1% BSA in PBS was added for 2min at room temperature. It was then washed 3 more times with PBS, and 2-3 drops of fluoroshield was added. Images were taken with a 40x magnification objective lens on a confocal Leica microscope. Per condition, approximately 25 neurons were imaged. To assess growth cone area, the longest MAP-2 branch was identified and the point at which the phalloidin stain faded into the MAP2 staining was considered the end of the growth cone. A square was dragged over this area and duplicated and the MAP2 and phalloidin channels were then split. Using only the phalloidin channel, the threshold was adjusted to remove any background signal. Then the area of the adjusted threshold was measured in µm2 and recorded. The mean of all growth-cone 35 areas per condition was normalized to the control (neurobasal condition) to evaluate any differences. 2.2.5 Neuronal Arborization Cells were grown for 3-4 days on glass coverslips coated with poly-L-lysine as described previously. They were treated on DIV 1 with either neurobasal, 50ng/ml Val66, 50ng/ml Met66, 50ng/ml proNGF, or 50ng/ml ProBDNF, 50ng/ml BDNF and then allowed to grow to DIV 3-4. Cells were then fixed for 15 minutes at room temperature in a 4% paraformaldehyde solution, permeabilized for 20 minutes with 0.2% Triton X-100, 1% BSA in phosphate buffered saline (PBS), washed 3 times with PBS, blocked for 1h in 0.02% Triton X-100, 1% BSA in PBS and then incubated overnight with the primary antibody (rabbit anti-BIII tubulin) diluted in 0.02% Triton X-100, 1% BSA in PBS. The next day the dishes were warmed up to room temperature, washed 3 times with PBS, then incubated with secondary antibody (anti-rabbit 488) in 0.02% Triton X-100, 2.5% BSA, 5% goat serum in PBS for 1hr. It was washed a further 3 times and then DAPI diluted in 1% BSA in PBS was added for 2min. It was then washed 3 more times with PBS. If no other fluorescent markers were added, then 2 drops of anti-fading media (fluoroshield) were added and kept at 4°C until imaging. Using the Zeiss Axioscope (Zen 2.0), a 20x magnification objective lens was used to take a tile image of each condition, the tile was stitched and then saved to a hard drive for analysis using the automated ImageJ plugin AutoneuriteJ. To use the autoneuriteJ plugin in ImageJ the image DAPI and BIII-tubulin channels were split. The naming of the images was important for the program to identify which images belonged together (ex: 20x H1_BDNF_01_DAPI_C=1). There were 3 parts to the program that require parameters to be outlined. 36 Table 1: Part I Parameters - image pre-treatment for enhancing the segmentation efficiency of the neurons. Original pixel size manually reset from 0.645 microns to 0.645 microns Original pixel size 0.645 microns Image scaling factor 0.645 Quantification pixel size 1 micron Minimal area for a neuron (in pixels) 400 Nucleus diameter (in pixels) 15 Filter size for neuron segmentation Median blur (pxl)=1 and Gaussian blur (pxl)=45 Table 2: Part II Parameters - Pre-processing of segmented images to create stacks of individual neurons and their skeleton. min Primary Neurite Tree size (in pixels) 15 min Neurons area (in pixels) 500 min Total Skeleton size (in pixels) 50 min Primary Neurite Tree size (in pixels) 15 Table 3: Part III Parameters - Measurement of neuritic length and classification. minimal size of Axons (in pixels) 100 minimal size of Neurites (in pixels) 15 Axonal size ratio 1.5 minimal size of Axons (in pixels) 100 Once part III was completed, the program provides a folder containing the measurements of mean primary neurite length and mean primary neurite number. 2.2.6 PSD95/SYN-1 colocalization Cells were grown for 17 days on 35mm polymer Ibidi treated cover slips coated with poly-L-lysine as described previously. Cells were treated on DIV16 with the following conditions: neurobasal, 50ng/ml BDNF, 50ng/ml Val66, 50ng/ml Met66, 50ng/ml proNGF, 50ng/ml proBDNF and left for 24hr in the incubator at 37°C. After a respective treatment, cells were fixed for 15 minutes at room temperature in a 4% paraformaldehyde solution, permeabilized for 20 minutes with 0.2% Triton X-100, 1% BSA in phosphate buffered saline (PBS), washed 3 times with PBS, blocked for 1h in 0.02% Triton X-100, 1% BSA in PBS and 37 then incubated overnight with the primary antibody (rabbit anti-PSD95, chicken anti-MAP-2, mouse anti-synapsin-1) diluted in 0.02% Triton X-100, 1% BSA in PBS. The next day the dishes were warmed up to room temperature, washed 3 times with PBS, then incubated with secondary antibody (anti-rabbit Alexa 488, anti-chicken Alexa 633, anti-mouse Alexa 546) in 0.02% Triton X-100, 2.5% BSA, 5% goat serum in PBS for 1hr. If no other fluorescent markers were added, then 2 drops of anti-fading media (fluoroshield) were added and kept at 4°C until imaging. Images were taken on a confocal Leica microscope at 63x with the power for both PSD95 (488 nM) and syn-1 (546 nM) set at 8% to reduce background puncta and MAP2 (633 nM) set at 18% for every dish. The grain and offset were used to adjust to differences in staining between dishes. For each condition 5-6 images were analyzed. The images were analysed using the RG2B_colocalization (JAVA) plugin for ImageJ as follows. The images were an RGB composite saved as a jpeg file. The image was calibrated to the microscope scale bar. Then cell bodies were deleted, and the image saved as a tiff file. This image was split into either the MAP2 channel or the Syn-1 and PSD95 channels. The MAP2 channel was used to determine the MAP2 length by converting it into a binary image (skeletonized) and measuring the total area. The SYN-1 channel + PSD95 channel were run through the RGB2 colocalization plugin. The threshold was adjusted for brightness to select only colocalized particles and minimize background overlap. Then all co-localized particles were counted (2-infinity pixel ^2) and the final number recorded. Then to determine the final colocalized particles/μm of dendritic branching, the total number of colocalized particles was divided by the skeletonized area measured of the MAP2 stain. 38 2.2.7 Protein Level Quantification 2.2.7.1 Protein Analysis in Hippocampus DIV17 hippocampal cells were incubated for 24hrs with either neurobasal, BDNF (50ng/ml), VAL66 pro-domain (50ng/ml), or MET66 pro-domain (50ng/ml). Primary antibodies used: Rat PSD95 anti-mouse, Rabbit Synapsin-1 anti-rabbit, Actin anti-mouse. Secondary antibodies used: HRP anti-Rabbit, HRP anti-mouse. 2.2.7.2 Protein analysis in CTX DIV7 cortical neurons were incubated for 1hr with either neurobasal, BDNF (50ng/ml), VAL66 pro-domain (50ng/ml), MET66 pro-domain (50ng/ml), VAL66 pro-domain + BDNF (50ng/ml), or MET66 pro-domain + BDNF (50ng/ml). Primary antibodies used: #527, Total recombinant protein within human Phospholipase C gamma 1 aa 690-852, Invitrogen, 1/1000 #528, Phosphorylated Phospholipase C Tyr783, cell signaling, 1/1000, #29 Total p42 MAP Kinase 3A7 synthetic peptide (extracellular signal-regulated kinases-ERK), NEB/CST, 1/1000 , # 30 Phosphorylated extracellular signal-regulated kinase ½ (Thr202/Tyr204), NEB/CST, 1/1000, #1 Actin clone C4 , Fisher Scientific, 1/1000, Secondary Antibodies used: HRP anti Rabbit, HRP anti-mouse. 2.2.7.3 Lysate SDS-PAGE (Western Blot) Samples were collected from 6 well plates and lysed with 80µl per well with Lammeli sample buffer (20% SDS, 1M DTT, 1M Tris PH6.8, bromophenol blue, Glycerol, H20). After boiling the samples for 5min, 10µl of sample was loaded into a 10% acrylamide gel for SDS-PAGE. The separated proteins were transferred onto nitrocellulose membrane and then washed 39 briefly with TBS-T (0.1% tween-20 TBS). The membrane was blocked for 1hr in blocking solution (5% milk powder in TBS-T). It was then incubated at 4oC overnight with the appropriate primary antibody. The next day the membrane was washed for 1hr in TBS-T at room temperature, then incubated with the respective secondary antibody for 1hr. The secondary antibody solution was removed, and the membrane was washed in TBS-T for 1hr. The membrane was then incubated with 1ml ECL reagent detection reagent (0.5ml 20x luminol/enhancer, 0.5ml 20x peroxide) for 1min and imaged on the ChemiDoc (Biorad). Image Lab was used to perform densitometry measures and compare the relative amount of a specific protein for a given experimental sample. 2.2.8 Statistical Analysis 2.2.8.1 Determining Sample Size A sample size calculation is an important step in the development of an experimental protocol. It is a method to control for statistical power while optimizing the use of resources and maintaining an ethic practice when involving animals. For example, if a statistical test result as non-significant this can be due to two factors. Either the null hypothesis is correct, and there is no effect, or the hypothesis is true, but the experiment was not powerful enough to detect the deviations from the null hypothesis. To maintain statistical power one can use the following equations or G-power a free general power analysis program175 . There are many types of equations to calculate sample size and choosing the correct one is determined by your experimental set-up. It can be based off preliminary experiments where the group mean is measured: S - Standard deviation obtained from previous study, or pilot study 40 d - accuracy of estimate or how close to the true mean Z a/2 -1.96 for alpha 0.05 𝑁 = 𝑍!"" 𝑠"𝑑" Or it can be done with the experiment in question176: r - n1/n2 – the ratio of sample size σ - pooled standard deviation d - difference of means of 2 groups Z1-β - 0.84 for power 0.80 Zα/2 -1.96 for alpha 0.05 𝑁 = (𝑟 + 1)(𝑍!" + 𝑍#$%)"𝜎"𝑟𝑑" 2.2.8.2 Statistical Tests The statistical test where chosen based on the design and aim of each experiment and is described in the figure legend. For the analysis of the Growth Cone experiment, the arborization experiment, and the synaptic colocalization/puncta experiment a Holm-Šídák corrected Multiple Unpaired T-test statistical analysis was used. The multiple T-test is used when comparing the mean of two unmatched groups and can compare multiple groups at once. In this case the two groups evaluated were Control (Neurobasal) to Treatment group. The statistical significance was defined as as p ≤ α ≤ .05, where N is defined as a biological repeat in all experiments. The multiple unpaired T-test was corrected using the Holm-Šídák method, which controls for type I error (False positives) that can arise with multiple comparisons177,178. With regards to the BDNF signaling experiment, a One-Way ANOVA 41 Bonferroni’s Multiple comparison test was used. A One-Way ANOVA compares the mean of three or more unmatched groups, in this case comparing NB, Val66, Met66, BDNF, Val66 + BDNF, and Met66 + BDNF groups to each other. Since every mean was compared to every other mean, unlike in the previous experiments, the Bonferroni’s Multiple comparison test was used179. In the PC12 studies, a Two-Way ANOVA Turkey multiple comparison test, was used as there where two independent variables present where testing the relationship between treatment conditions (Control vs Treatment) and PC12 P75NTR KO cell line (WT vs KO). The Turkey multiple comparison test is recommended when comparing every mean to every other mean as done with an ANOVA180. The statistical significance was defined as p ≤ α ≤ .05, where N is defined as a biological repeat in all experiments. 2.3 Results 2.3.1 Calcium Signaling Synaptic plasticity (LTP and LTD) and neuronal firing activity rely on complex flux of calcium in the pre- and the post-synaptic compartment. Bursts of neuronal activity can induce the influx of calcium, which can accumulate in the pre-synaptic compartment. An increase in the calcium concentration at the synapse can increase the amplitude of neurotransmitter release, leading to stronger synaptic connections and continual signal propagation2. The homeostatic buffering between calcium influx and efflux contributes to the plastic activity of synaptic strengthening and weakening associated with LTP and LTD respectively2. Numerous studies have shown that mature neurotrophins impact calcium flux, regulate synaptic plasticity and neuronal firing. However, only a few have explored the impact of the BDNF pro-domain 42 on synaptic plasticity, with mixed results. Mizui et al., showed that the WT BDNF pro-domain (Val66) but not the SNP (Met66) could modulate synaptic plasticity by enhancing hippocampal long-term Depression (LTD)181. However, another study by Hao et al., demonstrated that mice carrying the Met66 allele displayed impaired (LTD), a process heavily reliant on changes in Ca2+ flux167. Nevertheless, the ongoing debate regarding the impact of Val66 and Met66 on synaptic plasticity persists, and our comprehension of the underlying mechanisms remains rudimentary. Notably, preliminary evidence by Dr. Julien Gibon, demonstrated that Met66 could inhibit PF and reduce mEPSC frequency. PF is a Ca2+ - dependent mechanism requiring the activation of voltage-gated calcium channels (VGCC)149. In parallel, mEPSC’s represent spontaneous post-synaptic currents evoked by neurotransmitter release150. The influx of Ca2+ triggered by VGCC activation can instigate diverse downstream effects, including the initiation of Ca2+-dependent signaling pathways that modulate neuronal activity and neurotransmitter release. In this study, we aimed to elucidate the physiological impact of Met66 and Val66 on Ca2+ flux in cortical neurons, particularly when stimulated with carbachol (CCH), a cholinergic agonist. Carbachol, through binding to muscarinic receptors induces depolarization. This event initiates a downstream cascade that leads to an elevation in cytosolic Ca2+ levels and, at least in part, modulates the balance between LTD/LTP182–184. Building on studies that have identified Met66 behaving aberrantly compared to the wildtype Val66, we hypothesized that only Met66, when compared to Val66, disrupt calcium flux in neurons when stimulated by carbachol. 43 To evaluate alterations in Ca2+ flux, we utilized the Fluo4 Ca2+ sensor. A rise in Fluo4 fluorescence is an indicator of increased Ca2+ in the cell soma. To evaluate the impact of the pro-domain Val66 or Met66 on carbachol-induced calcium flux, neurons were first treated 20 minutes with vehicle (water-CTRL), 10ng/ml Val66 or 10ng/ml Met66. Following this pre-treatment, neurons were maintained in 2mM Ca2+ plus their respective conditions and CCH (50µM) was applied while Fluo4 fluorescence was measured. Figure 3A presents the fluorescence variation curves for three conditions: control (CTRL), 20 minutes pre-treatment with 10ng/ml Val66, and 20 minutes pre-treatment with 10ng/ml Met66. Across all conditions, there was a consistent increase in fluo4 levels upon stimulation with Carbachol (applied at t=55 sec), followed by a gradual reduction over time. When examining the peak response, no significant differences were observed between the conditions, suggesting that the presence or absence of Val66 or the Met66 pro-domain did not alter the influx of calcium into the cell soma (Fig. 3B). Further analysis involved comparing the area under the curve (A.U.C) between conditions to assess changes in fluorescent intensity over time. Interestingly, there was a significant decrease in A.U.C in the presence of both the Val66 (p<0.0001) and Met66 pro-domain (p<0.0001) compared to the control. This result suggests that the Val66 and Met66 pro-domains have an impact on the regulation of calcium levels, either affecting the influx, efflux or upstream signaling cascade of Ca2+ dynamics in the cell (Figure 3C). These findings do not support the hypothesis that only Met66, when compared to Val66, disrupts calcium flux in neurons stimulated by carbachol. 44 Fig. 3 Effect of the Val66 and Met66 on Cch-induced calcium flux in E13 cortical neurons. Calcium imaging performed on E13 cortical neurons differentiated for 4 to 7 days before calcium imaging; control-CTRL (black), 20ng/ml MET66 (blue), and 20ng/ml VAL66 (red) on (A) Fluorescence (Fluo4) variation curves induced by Carbachol (50 µM) applied t=55 s (black bar) in the presence of 2 mM Ca2+ Tyrode solution, presented as the mean of all repeats per condition, normalized to baseline fluorescent intensity. (B) The maximal amplitude of the peak for each curve is presented in the box plots, control-CTRL (black), 20ng/ml VAL66 (red) and, 20ng/ml MET66 (blue), (n= Mouse), One-Way ANOVA-Dunnett's multiple comparisons test. (C) The area under each curve (A.U.C) has been calculated per condition, control-CTRL (black), 20ng/ml VAL66 (red) , and 20ng/ml MET66 (blue) and is presented as a mean ± SEM of the total number of cortical cells in each condition; Val66 to CTRL (**** p < 0.0001) or Met66 to CTRL (**** p < 0.0001), One-Way ANOVA-Dunnett's multiple comparisons test. 2.3.2 Growth Cone Collapse 2.3.2.1 Impact of MET66 and VAL66 Variants on Growth Cone Collapse Our previous experiment showed that the Val66 and Met66 have the same impact on Ca2+ flux in neurons in response to carbachol. Thus, it could not explain why Met66 can influence synaptic firing patterns while Val66 does not. Considering that the pro-domains do not influence the peak calcium response but influence the overall cytoplasmic Ca2+ concentration (A.U.C), it is possible that the pro-domains may be modulating other aspects of Ca2+ signaling rather than the acute magnitude of the response, such as altering the kinetics, duration, or spatial aspects of calcium dynamics within the neuron10. This raises the possibility that, even if both variants have a similar impact on Ca2+, the aberrant behavior of Met66 may 45 manifest further downstream or elsewhere in the signaling cascade, such as in synaptic plasticity. Growth cone collapse is a complex cellular response associated with cytoskeletal rearrangements and membrane dynamics. Observing growth cone collapse can be indicative of alterations in neuronal morphology and cytoskeletal dynamics. These changes may, in turn, reflect alterations in the molecular processes associated with LTD and LTP, as well as actin rearrangements. They contribute to the interconnected regulation of growth cone collapse and synaptic plasticity10,185. Of note, reports have demonstrated that pro-BDNF, pro-NGF, and Met66 induce growth cone retraction in cultured neurons101. Our hypothesis posits that the Met66 variant, when compared to Val66, has the potential to induce growth cone collapse. If Met66 is found to acutely induce growth cone collapse, it could be considered a plausible mechanism through which Met66 may induce LTD of synapses185. To investigate this, the growth cone area of DIV. 3-4 hippocampal neurons was assessed following a 1-hour treatment with the following conditions: neurobasal media (NB), 50ng/ml cleavage-resistant pro-BDNF, 50ng/ml pro-NGF, 50ng/ml Met66, or 50ng/ml Val66. Neurons were fixed with 4% PFA and stained with phalloidin (Green), MAP-2 (Red) and DAPI (Blue) (Fig.4A). The experiment was conducted in a single-blinded manner to ensure unbiased observations when imaging and analyzing growth cones. Approximately 25 growth cones were imaged per condition in each repetition, and then the area of the growth cone was measured on the phalloidin channel. Utilizing a Holm-Šídák corrected multiple unpaired T-test for statistical analysis, the investigation into growth cone areas between the control group (NB) and treated positive controls (proNGF, proBDNF) revealed no significant reduction. The assessment of 46 Met66 and Val66 conditions showed high variability and statistical analysis demonstrated no significant reduction in growth cone area across in any of the conditions (p > 0.05; Fig. 4B). Contrary to our findings, literature has shown that pro-BDNF, pro-NGF, and Met66 all induce growth cone collapse. However, it's important to note that these effects were observed primarily in p75NTR positive cells, a factor that was not controlled for in our experiment72,167,186,187. These findings do not support the hypothesis that Met66 induces growth cone collapse in hippocampal neurons. Fig. 4 Impact of Val66 and Met66 on Growth Cone Collapse in DIV. 3/4 Hippocampal Neurons. (A) Representative images of neuronal growth cones following 1h treatment with either Neurobasal, 50ng/ml ProBDNF, 50ng/ml proNGF, 50ng/ml MET66 or, 50ng/ml VAL66. Neurons were fixed with 4% PFA and stained with Phalloidin (Green), MAP-2 (Red) and DAPI (Blue). (B) Quantification of mean growth cone area (µm2). Data was normalized to neurobasal condition of each repeat and presented as a mean +/- SEM (Holm-Šídák corrected Multiple Unpaired T-test statistical analysis, n = 3 animals per condition, 20-30 growth cones were evaluated per condition; NB vs proBDNF p 0.623838, NB vs proNGF p 0.967033, NB vs Met66 p 0.967033, NB vs Val66 p 0.901433). Conditions were blinded from imager and data analyzer. Expanded 47 2.3.3 Neural Arborization 2.3.3.1 Impact of Val66 and Met66 Variants on hippocampal neuronal arborization With no substantial impact observed on growth cone morphology (axon) for both Met66 and Val66, our attention turned to investigating another critical morphological aspect pertinent to LTD/LTP—neuronal arborization (dendrites). This shift in focus redirects our exploration from the influence of pro-domains on axon morphology to their potential effects on dendritic morphology, both crucial components of a synapse. Given that carriers of the Met66 allele display developmental disorders (e.g., Developmental dyslexia), have smaller hippocampal volumes, and decreased dendritic complexity, suggests that the Met66 allele may be involved in the alteration of neuronal arborization108,188. Neuronal arborization encompasses the intricate branching patterns and structural transformations that unfold during the developmental and maintenance journey of a neuron. Changes in neuronal arborization are often considered adaptive responses to alterations in synaptic activity (e.g., LTP/LTD). Notably, increased LTD and lower BDNF levels have both been associated with a decrease in neuronal arborization2,90,189,190. Despite these associations, our understanding of the specific mechanisms by which the Met66 allele influences arborization remains rudimentary. It is unclear whether Met66 independently induces alterations in arborization or if its effects are mediated through changes in BDNF trafficking. In light of this, our study aimed to investigate the impact of both the Val66 and Met66 pro-domain on hippocampal neuronal arborization. We hypothesize that Met66 has the potential to induce LTD of synapses by decreasing neuronal arborization. 48 To evaluate changes to neural arborization, the mean primary neurite length and number of DIV4 hippocampal neurons was assessed following a 2.5-day treatment, initiated on DIV1. The following conditions were used: neurobasal media (NB), 50ng/ml BDNF, 50ng/ml NGF, 50ng/ml cleavage resistant proBDNF, 50ng/ml proNGF, 50ng/ml Met66, or 50ng/ml Val66 (Fig.5A). Once fixed and stained with anti-beta III Tubulin, a 120-tile image was taken using the Zeiss Axioscope of each coverslip and analyzed with the autoneuritJ image J plugin to reduce bias. Five replicates, per condition, were analyzed ranging between 455 and 624 evaluated neurons. Despite variations in treatment including NB (baseline control), BDNF and NGF (positive controls), and proBDNF (negative control), there were no significant differences observed in neurite length or neurite number between the test groups (Val66, Met66) and controls. It is noteworthy that within each condition, variability among replicates was apparent. The observed variability suggests the potential need for an increased number of repetitions to mitigate variance. However, given that more than 455 neurons were analyzed per condition, this seems less likely. Alternatively, it may indicate a sensitivity issue within the automated analysis program, affecting its ability to detect neurotrophic-induced arborization changes accurately. Contrary to our initial hypothesis, which posits that Met66 induces LTD of synapse by impeding neuronal arborization, these findings reveal that neither Met66 nor Val66 significantly influences the development of neural branch patterns. 49 Fig.5 Val66 and Met66’s effect on hippocampal neuronal arbor maturation. (A) Representative images of the primary neurite length and number following treatment with either Neurobasal, 50ng/ml BDNF, 50ng/ml NGF, 50ng/ml ProBDNF, 50ng/ml MET66 or, 50ng/ml VAL66 at 1 DIV, and dendrite morphology was examined at 4 DIV. Neurons were fixed with 4% PFA and stained with B-III Tubulin and DAPI. (B) Quantification of the percent change of Normalized Mean Primary Neurite number (C) Percent change of Normalized Mean Primary Neurite Length. Positive numbers signify a percentage increase, while negative numbers indicate a percentage decrease compared to the baseline (NB). Data was normalized to neurobasal condition of each repeat and presented as a mean +/- SEM. Holm-Šídák corrected Multiple Unpaired T-test statistical analysis, n = 3 animals per condition, ranging between 455 and 624 evaluated neurons, % Number; n.s. ( NB vs BDNF p 0.114939, NB vs NGF p 612305, NB vs ProBDNF p 0.942190, NB vs Met66 p 0.838722, NB vs Val66 p0.612305), % length; n.s., (NB vs BDNF p 0.524400, NB vs NGF p 0.746601, NB vs ProBDNF p 0.665279, NB vs Met66 p 0.182964, NB vs Val66 p 0.949233). 50 2.3.4 PSD-95 and Synapsin-1 colocalization Given that neither Met66 nor Val66 significantly influences the development of neural branch patterns, our attention shifted to another potential mechanism through which Met66 may induce long-term depression (LTD): alterations to the synapse. In the synaptic context, Val66 was initially linked to a reduction in dendritic spine density140. However, subsequent research has challenged this association, uncovering that it is specifically Met66, as opposed to Val66, that possesses the ability to disassemble dendritic spines139. The ongoing debate regarding whether Met66 or Val66 is the pro-domain variant associated with adverse effects on synaptic morphology remains inconclusive. To bridge this gap, we investigated the potential impact of Met66 and Val66 on synaptic morphology. Synaptic formation relies on the proximity of the pre-synaptic compartment (axon) to the post-synaptic compartment (dendritic spine). This spatial relationship between synaptic structures is essential for effective neuronal communication and the activity-dependent transmission necessary for LTP/LTD191. To pinpoint the precise locations of both pre- and post-synaptic compartments, we selected two key synaptic markers. Synapsin-1 (SYN-1; presynaptic) is an anchoring protein for synaptic vesicles and postsynaptic density-95 (PSD-95; postsynaptic) is a well-known scaffolding protein important for organizing post-synaptic components192,193. Utilizing triple-label fluorescence immunocytochemistry and confocal microscopy, we aimed to assess alterations in individual SYN-1 and PSD-95 puncta, along with examining the colocalization of PSD-95 and SYN-1, relative to MAP2 levels. Colocalized PSD-95 and SYN-1 particles are indicative of potential synaptic connections, were the pre- and post- compartment are in such proximity that the fluorescent markers overlap194. To control for 51 background signals of both protein antibodies and fluorescent markers, conditions without; primary antibody or secondary antibodies, were imaged and compared to an image containing both markers. In both instances where one of the antibody steps was omitted, no fluorescence was observed, affirming the functionality of the immunocytochemistry protocol employed (Fig.6A). To ensure the proper formation of synapse the hippocampal neurons were allowed to mature until DIV17. Neurons were treated on DIV16 for 24hs with either Neurobasal (NB), 50ng/ml BDNF, 50ng/ml pro-BDNF, or 50ng/ml pro-NGF, 50ng/ml VAL66, or 50ng/ml MET66. Neurons were fixed with 4% PFA and triple stained with PSD-95-488 (Green), SYN-1-546 (Red), MAP2-633 (Blue), arrows indicate colocalized particles (Fig.6 B). Using the RGB2 colocalization plugin on ImageJ, colocalized particles were quantified and normalized to the MAP2 staining (e.g., total dendritic length) of each image and then to each replicates control (NB). Numerous studies, including ours, have shown that BDNF increases synaptic strength and formation of synapses. In 4 out of 6 technical repeats, BDNF showed a significant increase in the number of colocalized particles per µm of dendritic branching (p < 0.05; Fig.6C). Notably, only datasets in which BDNF showed a significant increase in the number of colocalized particles were included for further analysis. This observation aligns with existing literature suggesting that BDNF has the potential to enhance colocalization between PSD-95 and Syn-1 in neurons139,195. This means that, BDNF, by promoting increased colocalization of synaptic markers like PSD-95 and Synapsin-1, may contribute to heightened synaptic density. This enhanced synaptic density, in turn, can facilitate more efficient synaptic communication between neurons (e.g., 52 synaptic strengthening) which coincides with BDNF’s ability to enhance LTP and neuronal firing. In contrast, VAL66 displayed substantial variability, introducing challenges in discerning effects. On the other hand, while Met66 did not reach statistical significance, 3 out of 4 repeats displayed a decrease in the number of colocalized particles per µm of dendrite compared to NB (Fig.6 C). Considering that colocalized particles were reduced in the Met66 condition, we wanted to identify if the decrease in colocalized particles was due to a reduction in either the pre- or the post- synaptic marker. To delve deeper, we quantified and normalized the total PSD-95 puncta and SYN-1 puncta to MAP2 (µm). To ensure that the observed changes are specific to neurotrophic influence rather than experimental variability, repetitions were required to demonstrate an increase in either PSD-95 or SYN-1 puncta under the BDNF condition (positive control), in comparison to the baseline control (NB). While a statistical significance was not observed between conditions, it is interesting to highlight that Met66 consistently showed a reduction in PSD-95 puncta across all three repetitions compared to NB, whereas Val66 led to an increase in PSD-95 puncta in two out of three repeats (p > 0.05; Fig.6D). Conversely, both Met66 and Val66 demonstrated a significant decrease in SYN-1 puncta compared to NB (p < 0.05; Fig.6E). This suggests that there is no functional difference between the Val66 and Met66 pro-domain as both variants exert a disruptive effect on the presynaptic (axon) compartment. This observation is consistent with existing literature indicating that the BDNF pro-domain has been implicated in inducing axonal growth cone collapse via p75NTR-dependent mechanisms and confirmed to be localized within presynaptic vesicles of mature neurons101,131. However, a functional divergence may 53 exist in the post-synaptic compartment, where Met66 may exert a synaptic deconstructive effect while Val66 exhibits a constructive effect. However, the lack of statistical significance prevents a definitive conclusion about these observed differences between Val66 and Met66. Consequently, this data does not support our hypothesis that only Met66 induces LTD of synapses by altering synaptic morphology. 54 Fig.6 Met66 or Val66 demonstrate no significant alteration in the count of individual puncta or colocalized puncta of PSD-95 and SYN-1 in hippocampal neurons. (A) Immunocytochemistry controls. Images depict conditions with either no primary antibody (MAP-2, PSD-95, SYN-1) or no secondary antibody (Alexa 633-Blue, Alexa 546-Red, Alexa 488-Green). (B) Representative images of individual SYN-1 and PSD-95 puncta, and PSD-95/SYN-1 colocalization 24hr after treatment with either Neurobasal 55 (NB), 50ng/ml BDNF, 50ng/ml MET66, or 50ng/ml VAL66 in DIV.17 hippocampal neurons. Neurons were fixed with 4% PFA and stained with PSD-95 (Green), SYN-1 (Red), MAP2 (Blue), arrows indicate colocalized particles. (C) Quantification of PSD-95/SYN-1 colocalization. Data are expressed in a ratio of # of colocalized particle/total dendritic length (µm) and normalized to neurobasal within each repeat. Graphically, data is presented as a mean +/- SEM (Holm-Šídák corrected Multiple Unpaired T-test, n = 4 mice per condition; NB vs. BDNF p 0.024523, NB vs. Met66 p 0.173960, NB vs Val66 p 0.979294) (D) Quantification of individual and PSD-95 puncta. Data was normalized to neurobasal (NB) control within each replicate and presented as a mean +/- SEM (Holm-Šídák corrected Multiple Unpaired T-test, n = 3 mice per condition; NB vs. BDNF p 0.124708, NB vs. Met66 p 0.124708, NB vs Val66 p 0.885918). (E) Quantification of individual SYN-1 puncta. Data was normalized to neurobasal (NB) control within each replicate and presented as a mean +/- SEM (Holm-Šídák corrected Multiple Unpaired T-test, n = 3 mice per condition: NB vs. BDNF p 0.204109, NB vs. Met66 p 0.004490, NB vs Val66 p 0.049526) 2.3.5 Synaptic Markers PSD-95 and Synapsin-1 2.3.5.1 Changes to SYN-1 and PSD-95 Protein Levels While we previously explored the quantity of synapses through the identification of colocalization and puncta quantification, it's important to note that this method may not accurately represent the protein levels within each synapse. Therefore, we aimed to further investigate changes to synaptic structure and morphology, particularly focusing on quantifying the protein levels of PSD-95 and SYN-1. Elevated levels of PSD-95 have been associated with changes in the morphology of post-synaptic dendritic spines, notably adopting a mushroom shape (mature synapses). The presence of this mushroom-shaped morphology is correlated with heightened synaptic strength, potentially due to an increased surface area. Moreover, this specific spine morphology has been observed to increase in association with LTP196. In contrast, SYN-1 is more directly linked to pre-synaptic vesicle dynamics. An increase in SYN-1 levels can modulate the availability and release of neurotransmitters into the synapse, directly impacting synaptic transmission strength. This influence on neurotransmission can contribute to structural 56 modifications in dendritic spines, potentially leading to a shift towards a mushroom-shaped morphology197. As presented in Figure 6, hippocampal neurons were allowed to mature until DIV.17 to allow for the formation of mature synapses. They were treated on DIV16 with either Neurobasal, 50ng/ml BDNF, 50ng/ml VAL66 or, 50ng/ml MET66. Following a 24-hour incubation period, PSD-95 protein levels did not exhibit noticeable alterations in the BDNF condition. For the Val66 variant, 2 out of the 3 experimental repetitions showed PSD-95 levels above the NB threshold. In contrast, the Met66 variant exhibited a significant decrease in PSD-95 levels across all 3 repetitions (p < 0.05; Fig. 7B). Consistently, BDNF did not show notable effects on SYN-1 protein levels. However, with both the Val66 and Met66 variants, in 2 out of the 3 experimental repetitions, SYN-1 levels were above the NB condition SYN-1 protein level threshold (n.s.; Fig. 7C). These results demonstrate that the Met66 pro-domain does not have a significant effect on the regulation of post- synaptic protein (SYN-1) levels, yet it trends to selectively decreasing the post-synaptic PSD95 levels. This result aligns with literature showing that Met66 can disassemble dendritic spines in hippocampal neurons (mice)139. This data supports our hypothesis that Met66 can induce LTD by decreasing synaptic protein levels to induce changes in synaptic morphology. However, a notable limitation of the study is the lack of statistical significance for the BDNF positive control, which may be attributed to the low number of repetitions. 57 Fig.7 Effect of Val66 and Met66 Variants on SYN-1 and PSD95 Levels. (A) Representative Western blot of PSD-95 and Synapsin-1 protein levels 24hr after treatment with either Neurobasal, 50ng/ml BDNF, 50ng/ml VAL66 or, 50ng/ml MET66 in DIV.17 hippocampal neurons. PSD-95 and SYN-1 expression was normalized to actin to control for protein loading. (B) Quantification of Western blotting data in (A) by densitometry. Data are expressed in a ratio of PSD-95/Actin and presented as a mean +/- SEM (Holm-Šídák corrected Multiple Unpaired T-test, n = 3 mice per condition: NB vs. BDNF p 0.661882, NB vs Val66 p 0. 661882, NB vs. Met66 p 0.04219) (C) Data are expressed in a ratio of SYN-1/Actin rand presented as a mean +/- SEM (Holm-Šídák corrected Multiple Unpaired T-test, n = 3 mice per condition; NB vs. BDNF p 0.880573, NB vs Val66 p 0.741042, NB vs. Met66 p 0.741042) 2.3.6 Molecular Signaling in Cortical Neurons Various mechanisms can influence the induction of LTD/LTP. Our primary focus has been on examining alterations at the synapse, encompassing morphological changes such as synaptic density (colocalization of PSD-95 and SYN-1), identifying the targeted synaptic compartment (pre-/post) and modifications to synaptic marker protein levels (SYN-1/PSD-95). These changes can be indicative of synaptic strengthening and alterations in synaptic spine morphologies, including the formation of mushroom-shaped spines198. However, since the impact of Met66 and Val66 on synaptic morphology, as indicated by changes in SYN-1 and PSD-95, did not reach statistical significance, we redirected our research approach. Recognizing that LTD is not solely reliant on morphological alterations of synapses but also involves alterations in synaptic signaling, which consequently contribute to 58 modifications in synaptic morphology, we redirected our attention to a more focused exploration of synaptic signaling.20,26,199. It has been established that TrkB and p75NTR pathways function in opposition, with mBDNF/TrkB facilitating LTP and ProBDNF/p75NTR promoting LTD in the hippocampus37. Interestingly, the presence of p75NTR can influence the binding affinity and signaling outcomes of TrkB68. Both Val66 and Met66, with Met66 exhibiting a higher affinity, can bind the SorCS2/p75NTR complex, inducing p75NTR signaling and potential cross-talk with BDNF/TrkB signaling139. On the other hand, Met66 can also bind mBDNF, changing protein stabilization, and thereby attenuating the ability of BDNF to inhibit hippocampal LTD131. The influence of Met66 and Val66 on synaptic BDNF/TrkB signaling, and consequently induce alterations in LTD, remains unknown. Considering that Met66 can bind either mBDNF or SorCS2/P75NTR, influencing BDNF-induced LTP/LTD signaling, we proposed that Met66 may attenuate the signaling outcomes of mBDNF/TrkB. To address this, we examined two mBDNF/TrkB synaptic signaling pathways; PLCγ and ERK. Phosphorylation of PLCγ modulates neurotransmitter release and intracellular calcium dynamics, while phosphorylated ERK is known for its involvement in initiating protein synthesis in dendrites and is crucial for LTP in the hippocampus200,201. Cortical neurons cultured for 7 days in vitro (DIV) were subjected to a 1-hour treatment with various conditions, including neurobasal (NB), 50ng/ml BDNF, 50ng/ml VAL66, 50ng/ml MET66, 50ng/ml Val66 + BDNF, or 50ng/ml MET66 + BDNF. NB, P75NTR, and BDNF served as controls (Fig.8A). The aim of this experiment was to determine, 1) if the BDNF pro-domains affect mBDNF/TrkB signaling 2) Identify the signaling pathway altered. Notably, 59 BDNF, serving as a positive control of mBDNF/TrkB signaling, significantly elevated the phosphorylation levels of both PLCγ and ERK (p = 0.0093, p = 0.0043). Val66 and Met66 variants without BDNF in the condition were used as controls to confirm that the pro-domains did not independently exert an effect on the PLCγ and ERK pathways. In the presence of BDNF, neither Val66 nor Met66 significantly altered BDNF/TrkB phosphorylation of PLCγ and ERK (Fig. 8B-C). This observation suggests that the pro-domains, specifically MET66, do not exert an influence on PLCγ and ERK activation. Consequently, these findings do not align with the hypothesis proposing that MET66 induces long-term depression of synapses through alterations in synaptic signaling. Fig.8 The impact of Met66 on molecular signaling in cortical neurons 7 DIV. (A) Representative Western blot of Phosphorylated PLCγ (P- PLCγ), Total PLCγ (T- PLCγ) Phosphorylated ERK (P-ERK), Total ERK (T-ERK), and p75NTR protein levels 1hr after treatment with either Neurobasal, 50ng/ml BDNF, 50ng/ml VAL66, 50ng/ml MET66, 50ng/ml Val66 + BDNF, or 50ng/ml MET66 + BDNF in DIV.7 cortical neurons. PLCγ and ERK protein level expression was normalized to actin to control for protein loading. (B) Quantification of P- PLCγ and (C) P-ERK levels by densitometry. Data are expressed in a ratio of (P- PLCγ /T- PLCγ)/Actin and (P-ERK/T-ERK)/Actin respectfully and presented as a mean +/- SEM (One-Way ANOVA statistical analysis, n = 3 (PLCγ) n = 4 (ERK) animals per condition; yes., p 0.0.0093, p 0.0043 respectfully, Bonferroni’s Multiple comparison test, NB vs. BDNF, (PLCγ) p 0.0379, (ERK) p 0.0310) 60 2.4 Discussion Clinically, the Met66 variant has been associated with an increased risk for anxiety, depression, and cognitive decline, accompanied by structural changes such as a decrease in hippocampal volume size80,86,101,108. The alteration of whole brain structures typically results from disruptions in neuronal communication, following the "use it or lose it" principle202. However, the molecular mechanisms underlying the ability of Met66 to induce these structural and clinical changes remain inconclusive. Currently, three different ideas about the Met66 pro-domain exist: 1) Met66 can act as an independent ligand to disrupt certain cellular processes101; 2) Met66 function is not physiologically different from its WT variant Val666140; 3) the main effect of MET66 is to reduce BDNF levels, resulting in Met66 carriers displaying the clinical effects associated with a decrease in BDNF levels81. To address this gap of knowledge, this thesis aimed to investigate the impact of the Met66 variant on neuronal activity. The context of the study was built upon preliminary research by Dr. Julien Gibon, demonstrating that Met66 reduces synaptic transmission in the entorhinal cortex whereas Val66 had no effect. Such firing lags have been associated with synapse weakening, particularly in the form of LTD203. Considering Met66's established role in synaptic plasticity—such as reducing hippocampal volume and inducing signaling defects that contribute to synapse weakening—we hypothesized that Met66, when compared to Val66, may induce LTD of a synapse. LTD can manifest in numerous ways, including reduced synaptic transmission efficiency, decreased synaptic vesicle release, and alterations in pre- or post-synaptic structure, ultimately resulting in the decrease or loss of synaptic connections25,168,204. Therefore, our primary objective was to elucidate the mechanism by which Met66 may induce LTD. To 61 achieve this, we first focused on investigating a key regulator of vesicle binding and neurotransmitter release, namely calcium ions (Ca2+)8. Prolonged calcium elevation in the presynaptic terminal can lead to changes in the probability of neurotransmitter release, resulting in alterations in synaptic efficacy and changes in the signal transmission rate8,10. Since only Met66 appeared to influence the firing rate of neurons, we hypothesized that only Met66, when compared to Val66, disrupts Ca2+ flux in neurons stimulated by carbachol. Interestingly, we found no difference between the peak Ca2+ response of Met66 or Val66 compared to control. However, when the overall cytoplasmic Ca2+ concentration (A.U.C) was analyzed, both Val66 and Met66 reduced the A.U.C when compared to control. This result suggests that the Val66 and Met66 pro-domains have an impact on the regulation of Ca2+ levels, either affecting the influx, efflux or upstream signaling cascade of Ca2+ dynamics in the cell. However, given that both BDNF pro-domains affected the Ca2+ load, how only Met66 was able to influence synaptic activity was not explained. These data do not support the hypothesis that the Met66 mutation results in disrupting Ca2+ flux in neurons stimulated by carbachol and the mechanism by which Met66 may induce LTD is not provided by this observation. Nevertheless, it underscores that the role of the BDNF pro-domain extends beyond its function as a protein folding and trafficking chaperone for proBDNF and mBDNF101,131,205. Indeed, these data show that the pro-domain exhibits independent effects distinct from mBDNF and full length proBDNF counterparts. Expanding our investigation into the potential mechanisms driving Met66-induced LTD, we redirected our focus to explore the relationship between Met66 and axonal morphology. It has been well established that Ca2+ plays an important role in axonal 62 development and guidance186. Given that both pro-domains affect Ca2+ dynamics but fail to explain how Met66 alone can lead to changes in neuronal activity, we hypothesized that Met66 may exert divergent effects on LTD at a different level of synaptic function. Specifically, alterations in axon morphology could represent a distinct mechanism through which Met66 influences LTD. For instance, an increase in the inter-event interval (I.E.I) entails a delay in neurotransmitter release from the pre-synaptic compartment, namely the axon206. The formation of the pre-synaptic compartment is intricately linked to axonal morphology. Changes in the morphology of the pre-synaptic compartment can influence the organization of active zones (e.g. region of neurotransmitter release), spatial distribution, proximity to the post-synaptic compartment, and the presence of proteins essential for neurotransmitter release72,207. To investigate the impact of Met66 on axonal morphology, we assessed its effect on growth cone collapse in hippocampal neurons. The ability for the brain to remain plastic depends on cytoskeletal rearrangements through the emergence, path finding and retraction of neural processes208. Growth cone assays provide a model for assessing the influence of Met66 on cytoskeletal rearrangements and membrane dynamics. ProNGF and proBDNF were selected as positive controls due to their known ability to induce growth cone collapse72,101. However, neither Met66, Val66, nor the pro-neurotrophin controls induced growth cone collapse, contrary to prior literature indicating that proNGF, proBDNF, and Met66 can induce this phenomenon. However, it's important to note that these effects were observed primarily in p75NTR positive cells, a factor that was not controlled for in our experiment72,167,186,187. Hence, our findings may reflect the lack of screening for the presence of the p75NTR receptor during the analysis of the growth cone collapse assay. 63 It is well known that P75NTR is not expressed evenly throughout a population of primary neurons, therefore screening for p75NTR expression becomes necessary in experiments involving it’s signaling cascades101,209. As such, proNGF and proBDNF directly bind to P75NTR, while Met66 binds the SorCS2 receptor to form a ternary complex with P75NTR27,101. Consequently, our results might have been influenced by certain neurons exhibiting relatively low P75NTR expression, potentially obscuring the effects of the P75NTR-dependent pro-domains. That being said, we conducted the experiment without screening for p75NTR to better mimic the physiological conditions within the brain, where both p75NTR-positive and negative cells coexist. This would suggest that even if Met66 has an aberrant effect on growth cone collapse through p75NTR, as mentioned in previous literature, other systems are involved to mitigate or counter this effect. Consequently, it becomes less plausible to attribute the clinical effects observed in Met66 carriers solely to the p75NTR signaling mechanism. With no substantial evidence of Met66's functional divergence in either Ca2+ dynamics or growth cone collapse, we redirected our attention to the second integral component of a synapse: the post-synaptic (dendritic) compartment. This brings us to the third research objective which was to assess the effect of Met66 and Val66 on neural arborization and the development of neural branch patterns. Neuronal arborization, derived from the latin term “Arbor”, meaning tree, refers to the intricate branch patterns and structural transformations resembling the structure of a tree. This dynamic process unfolds during development and continuously adjusts to environmental factors during its maintenance phase. Changes in neuronal arborization are often considered adaptive responses to alterations in synaptic activity (e.g., LTP/LTD). Not only do defects to 64 neuronal arborization directly decrease the quality and quantity of synaptic connections, but they also lead to various clinical manifestations such as cognitive impairment and developmental disorders. Notably, increased LTD and lower BDNF levels have both been associated with a decrease in neuronal arborization2,90,189,190. Given that carriers of the Met66 allele have increased incidence of developmental disorders (e.g., developmental dyslexia), have smaller hippocampal volumes, and decreased dendritic complexity, it is plausible then that Met66 may impede neuronal arborization, thereby contributing to LTD of synapses108,188. However, in my analyses, neither the primary dendritic length nor primary neurite number significantly decreased in the presence of the Val66 or Met66 pro-domains or the proBDNF peptide, compared to the control, nor increased in the NGF or BDNF conditions. Of note, both BDNF and NGF are known to increase dendritic complexity, which suggests a potential sensitivity issue within our experimental setup210. Two aspects of the experiment could be improved: the tile images and the analysis process. Specifically, the images were captured using a 120x tile format on the Zeiss Axioscope, where 120 pictures were taken and stitched together to create one large image. However, this stitching process occasionally resulted in certain neurites being cut off at the edges of images or not perfectly aligned. This could introduce errors, leading to variations in neurite length measurements and potentially explaining the high variability observed in the results. Additionally, the automated analysis program (AutoNeuriteJ) sometimes struggled to differentiate between clustered neurons. However, it is important to note that these issues, while significant for identifying subtle changes induced by neurotrophins, are consistent across all conditions tested allowing for a comparative analysis. 65 Given the absence of observed effects on axonal and dendritic morphology associated with Met66, the next aspect of LTD to explore was alterations to the entire synapse. This encompasses changes in synaptic density and protein composition that may contribute to the induction of long-term depression (LTD) mediated by Met66. The controversy between the effect of Val66 and Met66 is most prominent in the synaptic context. Initially, Val66 was linked to a reduction in dendritic spine density140. However, subsequent research has challenged this association, uncovering that it is specifically Met66, as opposed to Val66, that possesses the ability to disassemble dendritic spines, specifically Met66, as opposed to Val66, that possesses the ability to disassemble dendritic spines139. The formation of a synapse relies on the proximity of the pre-synaptic compartment (axon) to the post-synaptic compartment (dendritic spine), and the strength of this connection is activity-dependent, as seen in LTP and LTD. Notably, the lack of neuronal activity can result in LTD and reduced synapse formation211,212. Therefore, if Met66 is capable of disassembling dendritic spines, it may induce LTD of synapse by decreasing synaptic density. To precisely locate both pre- and post-synaptic compartments, we chose two key synaptic markers: synapsin-1 (SYN-1) for the presynaptic compartment and postsynaptic density-95 (PSD-95) for the postsynaptic compartment. When these markers are in close proximity, they appear to overlap, as the gap between synapses is typically only about 20–40nm213. It is well-established that BDNF can increase synaptic density by modulating synaptic transmission214. Our data corroborates this understanding, as we observed a significant increase in the amount of colocalized particles compared to the control when treated with BDNF. However, neither Met66 nor Val66 significantly altered the number of synapses. This discrepancy suggests that the changes induced by the pro-domain variants may not lead to a 66 reduction in synaptic density but rather to alterations in synaptic transmission by weakening certain aspects of the synapse. Thus, while BDNF promotes synapse formation, the effects of Met66 and Val66 may primarily involve modulating synaptic function rather than synaptic density. Therefore, to identify what aspect of the synapse may be affected we quantified the individual puncta number of PSD-95 and SYN-1. Interestingly, PSD-95 puncta number was unaffected, yet SYN-1 was significantly decreased in both the Val66 and Met66 condition suggesting that the effect of Val66 and Met66 on synapse function is localized to the pre-synaptic compartment. This observation is consistent with existing literature indicating that the BDNF pro-domain is localized in the pre-synaptic compartment and can affect the actin organization of axons101,131. However, it does not support the notion that either Met66 or Val66 significantly affects dendritic spines. Considering that both variants exerted a disruptive effect on the presynaptic (axon) compartment, suggests there is no functional divergence between the variants. This finding does not support our hypothesis that only Met66 induces LTD of synapses by altering synaptic morphology. However, upon analyzing the protein levels of PSD-95 and SYN-1 instead of puncta number, we observed that only Met66 reduces PSD-95 total protein levels, while neither Val66 nor Met66 have an effect on SYN-1 levels. The discrepancy between the results obtained with protein levels and puncta number could be attributed to the nature of the measurement. While a puncta represents one synaptic compartment, it does not account for the concentration of the protein within that compartment. Therefore, these results suggest that Met66 has a differential effect, reducing the post-synaptic PSD-95 protein levels without eliminating a synapse. PSD-95 protein levels have been correlated with different dendritic spine morphologies, where higher PSD-95 levels in a synaptic compartment are associated with mushroom-shaped spines 67 induced by long-term potentiation (LTP), while a decrease is linked to filopodia-like spines characteristic of LTD196,211,215. On the other hand, the fact that SYN-1 protein levels were unaffected, while the puncta number decreased, suggests that the loss of pre-synaptic compartments could potentially be balanced by an increase in SYN-1 protein. This observation may reflect the complex dynamics of synaptic plasticity, where compensatory mechanisms may come into play to maintain overall synaptic integrity despite alterations in synaptic structure. Synaptic signaling plays a crucial role in mediating morphological alterations of a synapse, thereby aiding our understanding of the functional capacity of BDNF pro-domains in the process of LTD25. To understand the underlying mechanisms driving the observed changes to synapse morphology and function, we examined the activation states of specific proteins involved in synaptic transmission and plasticity; phosphorylated forms of signaling molecule PLCγ and ERK200,201. Currently, our investigation has focused on the effect of acute extracellular effects of the pro-domains, however, in reality, mBDNF and the pro-domain variants exist simultaneously. Previously it has been determined that the WT BDNF pro-domain, when pre-incubated with BDNF, attenuates the ability of BDNF to inhibit LTD, suggesting that the pro-domain may be inducing LTD by attenuating the outcomes of mBDNF/TrkB signaling131. Both Val66 and Met66, with Met66 exhibiting a higher affinity, can bind the SorCS2/p75NTR complex, inducing p75NTR signaling and potential cross-talk with BDNF/TrkB signaling139. The influence of Met66 and Val66 on synaptic BDNF/TrkB signaling, and consequently induce alterations in LTD, remains unknown. Therefore, we examined if the BDNF pro-domains affect mBDNF/TrkB signaling. It is well known that mBDNF can activate (phosphorylate) ERK and PLCγ through binding its receptor, 68 TrkB, and thus served as a functional control39. In the presence of BDNF, neither Val66 or Met66 altered BDNF/TrkB phosphorylation of PLCγ and ERK when compared to the BDNF control. Neither Val66 and Met66 variants decreased the phosphorylation levels of PLCγ and ERK levels compared to NB controls, confirming that the pro-domains did not independently excerpt an effect on these signaling pathways. Consequently, these findings do not align with the hypothesis proposing that MET66 induces long-term depression of synapses through alterations in synaptic signaling. This result suggests that the observed effects of Met66 and Val66 on synaptic function may not mediated through the canonical mBDNF/TrkB signaling pathway involving ERK and PLCγ. This implies that Met66 may exert its effects through an alternative signaling pathway. For example, NMDA Receptor (Glutamate receptor) is involved in the signaling of the Rac/Rho pathway, where it has been found that Met66 can decrease the activation of Rac-1 which leads to dendritic spine remodeling139,216. This association is plausible, as SorCS2 is involved in NMDA trafficking and can directly interact with GluN2B, a key NMDA subunit involved in synaptic strengthening217,218. However, it is important to note that the p75NTR expression in DIV7 neurons is relatively low. This is important to consider when looking at the signaling interaction between p75NTR and TrkB as the ratio of p75NTR/TrkB can influence the binding affinity and signaling outcomes of mBDNF/TrkB. This suggests that higher levels of p75NTR may be necessary, such as during chronic inflammation (e.g. Alzheimer’s) or traumatic brain injury, to create the appropriate environment for Met66 to form the SorCS2 complex and affect TrkB signaling219,220. 69 2.5 Chapter Summary In conclusion, our study aimed to uncover the underlying mechanisms through which the Met66 mutation influences synaptic activity and potentially contributes to clinical risk factors associated with neurological disorders. Contrary to our initial hypothesis, our findings revealed that Met66 does not induce LTD of synapses through changes in Ca2+ dynamics, developmental morphology, or synaptic density. However, both Val66 and Met66 affected the pre-synaptic compartment (resulting in decreased SYN-1 levels), while Met66 distinctively affected the post-synaptic compartment (leading to decreased PSD-95 levels) irrespective of BDNF levels. This suggests a potential role of the pro-domains in synapse weakening, highlighting Met66's distinct effect on the post-synaptic compartment. This in turn could lead to a compounding effect on synapse weakening. In the presence of both Val66 and Met66, the pre- and post- synaptic compartment may be weakened, thus affecting both aspects of neurotransmission (neurotransmitter release, receptor availability). Some clear limitations of this study were the high variability between repeats, analytical methods employed, and difficulty maintaining viable primary cell cultures. Future research should investigate if there is a compounding effect of Met66 and Val66, on synapse function, and identify alternative mechanisms at the pre- and post- synaptic compartment by which Met66 may be inducing the changes to neuronal activity. While our findings do not support Met66-induced LTD, they underscore the complex nature of synaptic plasticity. However, there is a clear role the pro-peptide plays in the homeostatic mechanism of synaptic plasticity, but if Met66 truly has aberrant properties, it will need to be elucidated in future research. 70 Chapter 3: Characterizing p75NTR CRISPR KO PC12 Cells 3.1 Synopsis The origins of PC12 cells trace back to the pioneering work of Dr. Lloyd A. Greene, who isolated and characterized these cells in the late 1970’s. Initially derived from a pheochromocytoma (tumor) of the rat adrenal medulla, these cells exhibit neuronal characteristics. Clonal cell lines which express neuronal properties are useful model systems for studying the nervous system at the single cell and molecular level. PC12 cells stand out among established cell lines derived from human and murine neuroblastomas, as well as rat central nervous system tumors, due to their distinct responsiveness to the neurotrophin NGF. Notably, PC12 cells exhibit a unique trait: in response to NGF, they undergo a shift from an adrenergic to a cholinergic neurotransmitter phenotype, coupled with increased neurite outgrowth—a characteristic observed in sympathetic neurons. PC12 cells, with their notable ability to undergo neural differentiation in response to NGF, emerge as a valuable and cost-effective tool for modeling neurons and gaining insight into the world of neurotrophic signaling. This capacity not only bypasses ethical considerations associated with animal research but also ensures a consistent and well-characterized cellular phenotype221. With regard to neurotrophic signalling, PC12 cells can be utilized in three key aspects: 1) exploring the development and differentiation of neurons, 2) elucidating the signal transduction of NGF through its receptor TrkA, and 3) examining the world of cross-talk and co-receptor relationships within the neurotrophic signaling network222. PC12 cells express TrkA, p75NTR and SorCS2 receptors yet lack the expression of TrkB (BDNF receptor)222. Despite this, owing to the substantial homology within the neurotrophic family, studying NGF signaling in PC12 cells can offer valuable insights into 71 mechanisms associated with other Trk receptor action, contributing to a broader understanding of neurotrophic signaling pathways. The TrkA receptor is located on the cell surface and when bound by NGF, it undergoes phosphorylation. This in turn activates three signalling cascades 1) PI3K 2) MEK/ERK 3) PLCγ223. The PI3K pathway is involved with cell survival, growth, and proliferation, while MEK/ERK is associated with cell differentiation, proliferation, and survival. PLCγ is responsible for the generation of intracellular messengers, specifically inositol trisphosphate (IP3) and diacylglycerol (DAG), which play roles in Ca2+ signaling and activation of protein kinase C (PKC)35,224. There are multiple docking sites on the TrkA receptor; Tyr-490 in the juxtamembrane region, leads to the activation of ERK and PI3K pathways, while Tyr-790 in the tail of the cytoplasmic domain, is thought to be involved with PLCγ activation225. However, TrkA signalling can be influenced by the co-expression of p75NTR in the cell226. Fig. 9 Schematic of P75NTR acting as a co-receptor to TrkA to either increase or decrease NGF induced TrkA signaling through the PI3K, Ras, or PLCγ pathway227. Created with BioRender.com. 72 The p75NTR receptor belongs to the tumor necrosis factor superfamily (TNFR). Its physiological role is intricate and extensive, dictated by the specific cell context and ligand binding. In this regard, some non-neurotrophic ligands for p75NTR include neurotoxic prion protein fragments (PrP), the Aβ-peptide derived from the amyloid precursor protein (APP), and the glycoprotein of the rabies virus. These ligands can induce cell death or facilitate viral entry into the central nervous system (CNS)228–230. In the context of neurotrophic signalling however, the uncleaved pro-neurotrophins, such as pro-NGF, induce cell death signals while, NGF binding of p75NTR can produce cell survival signals65,231. Adding another layer of complexity to the p75NTR signaling dynamic is the involvement of SorCS2 as a co-receptor. This co-receptor, when engaged by the cleaved pro-domain of BDNF, forms a ternary complex with p75NTR. This complex, via p75NTR, triggers a signaling cascade capable of inducing alterations in neuronal morphology139. Not only can p75NTR act as an independent receptor to ligand binding and interact with co-receptors such as SorCS2, but it itself has been found to act as a co-receptor to TrkA. Indeed, this relationship is dependant of the ratio of co-expression levels but has been found to be involved in multiple processes. Nevertheless, when p75NTR is co-expressed with TrkA, the binding affinity, at the NGF binding sites, increase and enhances NGF mediated TrkA activation65. Despite these findings, numerous questions remain to be explored. These include, but are not limited to, unraveling the molecular mechanisms behind the association of p75NTR with TrkA, elucidating the interactions between p75NTR and SorCS2, understanding the impact of pro-domain variants on signaling pathways, and investigating the integration of neurotrophic signaling with other cellular processes, such as neurite outgrowth. 73 To address the large gaps that still exist today in neurotrophin signalling and the many roles of p75NTR, the creation of a p75NTR knockout PC12 cell line would be beneficial in advancing our understanding of neurotrophic signaling pathways. PC12 cells are renowned for their responsiveness to nerve growth factor (NGF) through TrkA activation. By targeting the p75NTR receptor, which plays a central role in neurotrophic signaling via both Trk and SorCS2 pathways, researchers can delve deeper into the intricate mechanisms governing neuronal development, function, and pathology. This novel approach promises to unlock insights not only into neurotrophin signaling but also into the diverse physiological roles of p75NTR, spanning areas such as cancer migration, neuronal development, injury, and degeneration50,66,232. In contrast to existing models like siRNA knockdown or silencing, which is a temporary and partial reduction in gene expression, the development of a PC12 p75NTR CRISPR knock out cell line offers a customized platform distinguished by complete disruption of p75NTR expression. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a gene-editing technology that allows the precise modification of genes within an organism. In the laboratory, researchers have adapted CRISPR to edit the DNA of organisms, including controversial experiments in humans, by introducing, removing, or modifying specific genes. The CRISPR system typically includes a molecular tool called Cas9 (CRISPR-associated protein 9) that acts like molecular scissors, cutting the DNA at specified locations, enabling precise genetic modifications, and thereby introduction of mutations or disruption of gene expression. With CRISPR, the genetic material itself is altered, ensuring a more comprehensive and lasting impact on the expression of the target gene. A CRISPR knockout permanently and entirely eliminates a gene's function, providing researchers with a clearer 74 understanding of the specific role of the gene product in various biological processes. This makes the development of a novel CRISPR p75NTR KO cell line an invaluable tool for research, promising more accurate and impactful investigations into the intricacies of p75NTR-related processes in various scientific disciplines. We hypothesize that the development of a PC12 p75NTR CRISPR KO cell line, characterized by complete disruption of p75NTR expression, will offer a superior and more accurate platform compared to siRNA knockdown or silencing methods. Our first objective was to develop a PC12 p75NTR CRISPR KO cell line, characterized by complete disruption of p75NTR expression, while maintaining the cell’s physiological function relevant to the NGF signalling. Subsequently, our aim was to characterize the p75NTR CRISPR KO cells, systematically assessing any physiological changes resulting from the knockout, specifically we will be looking at the NGF/TrkA pathway (ERK, PLCγ). Lastly, test the effect of the pro-domain variants, Val66 and Met66, on PLCγ and ERK signaling in the absence of p75NTR. 3.2 Methods 3.2.1 Culturing and Maintaining PC12 Cell lines The PC12 cell line was obtained from ATCC©. To thaw the PC12 cell line, the cryo-tubes were placed in a warm bath (37°C) for 5 min. Then approximately 1ml RMPI complete (10% HS, 5% FBS, 1% P/S) was added and reverse aspirated to resuspend cells. Dropwise the media was added to a 10cm polystyrene culture dish, then 10ml RPMI complete (10% HS, 5% FBS, 1% P/S) was added and place in the incubator at 37°C (21% O2, 5% CO2). When the PC12 cells were 80% confluent the RPMI media was removed and washed once with 0.35mM EDTA in PBS solution, then 4ml of 0.05% Trypsin in 0.35mM EDTA was added 75 and incubate for 5min at 37°C (21% O2, 5% CO2). Using the media already in the dish, the cells adhered to the dish were spray off and the suspended cell solution was placed in a 15ml Falcon tube. Then cell suspension was centrifuged at 1200 rpm for 3min, then the supernatant was removed and discarded, and the cells were resuspended with 5ml complete RPMI. The cells were mounted on Neubauer cell counting chamber to determine cell density needed for experimental plating or for a carry plate. The carry plates were maintained with media changes every 4-5 days or until 80% confluent. 3.2.2 CRISPR P75NTR KO PC12 Cell lines The creation of the CRISPR KO PC12 cell line outlined in this study was conducted by Svetlana Simtchouk. We extend our gratitude to her for her expertise and dedication in performing these experiments. To design p75NTR Knock-out PC12 cells the IDT custom Alt-R® CRISPR-Cas9 guide RNA tool was used to design gRNA. Table 4: The Alt-R CRISPR-Cas9 crRNA sequences. Rn.Cas9.NGFR.1.AA /AltR1/rGrArU rCrCrC rArArG rGrUrC rUrArC rGrCrC rCrCrG rUrUrU rUrArG rArGrC rUrArU rGrCrU /AltR2/ Rn.Cas9.NGFR.1.AB /AltR1/rArGrG rGrUrA rGrGrC rArCrG rGrGrU rCrCrA rCrGrG rUrUrU rUrArG rArGrC rUrArU rGrCrU /AltR2/ Rn.Cas9.NGFR.1.AC /AltR1/rGrGrG rUrUrC rArCrA rCrArC rGrGrU rCrUrG rGrUrG rUrUrU rUrArG rArGrC rUrArU rGrCrU /AltR2/ To deliver the CRISPR ribonucleoprotein, each RNA oligonucleotide (Alt-R CRISPR-Cas9 crRNA and tracer RNA) was resuspended in Nuclease Free Duplex Buffer to 100µM stock concentration. Then the crRNA and tracer were mixed in equimolar amount to create a final duplex concentration of 1µM, heated at 95°C for 5 min and cooled to room temperature. Alt-R S.p Cas9 enzyme was diluted in 1x PBS to working concentration of 1µM. The guide RNA oligo’s [1µM] and Cas9 enzyme [1µM] were incubated at room temperature for 5 min to 76 assemble the RNP complexes. To deliver the RNP complex to PC12 cells, 50µL of transfection complexes (RNP, lipofectamine RNAiMAX in PBS) were added to the wells of a 96-well tissue culture plate. Cells were diluted to 400,000 cells/mL using RPMI complete media without antibiotics. Then, 100µl of PC12 cells were added to the transfection complexes in the wells to produce a final cell density and concentration of 40,000 cells/well, 10nM RNP respectively. The plates containing the transfection complexes and PC12 cells were incubated in a cell culture incubator (37ºC, 5% CO2) for 48hr. The medium was then changed to complete RPMI with antibiotics. To validate the genome editing by CRISPR/Cas9 editing, the cells were subjected to western blot. Confluent cells from the 96 well plates were transferred into larger vessels (48, 24, 12-well plates). The cells in 12 well plates were lysed, and genome editing was verified by running a western blot to identify if NGFR/p75NTR had been knocked out successfully. 3.2.3 Single Clone isolation The method used to create single isolated clones was via an array dilution method. In a 96-well plate 100µl of complete culture medium (RPMI complete 10% HS, 5%FBS, 1%PS) was added to all wells other than the primary well (A1). Then, using a cell density of 2 x 104 cells/ ml, 200µl of cell suspension was added to well A1. To start the dilution process, 100µl of A1 cell suspension was transfer to B1 containing 100µl of culture media. This step was repeated down Column 1(C1) (1:2 dilutions) and then these wells were topped up to 200µl with complete culture medium. From here, 100µl of cell suspension was transferred horizontally from C1 to C2 and the 1:2 dilution repeated across the rows (C1-C12) using a multichannel pipette. The final volume was brought to 200µl with complete culture medium. 77 The plate was incubated at 37°C (21% O2, 5% CO2) for 3 days. Thereafter the 96 wells were examined and wells containing a single colony were noted and monitored daily. Single colonies were transfer into larger vessels (48, 24, and 12 well plates) cells in 12 well plates were lysed, and genome editing was verified by western blot. 3.2.4 Protein Analysis in PC12 WT and CRISPR p75KO PC12 cells were incubated for 30min with either RPMI complete, with or without 25ng/ml NGF. Primary antibodies used: PLCγ, ERK, #170 Total Neurotrophic tyrosine kinase receptor 1, 1/1000, Millipore #236 Phosphorylated TrkA (Try490) antibody 9141, NEB/CST, 1/1000, Actin. Secondary Antibodies used: HRP anti-Rabbit, HRP anti-mouse. 3.2.4.1 TrkA Pull-Down To collect lysates, the dishes were placed on ice, media was removed and 1ml cold NP-40 lysis buffer was added for 5min. Then, using cell scrappers, cell lysates were transferred to pre-cooled, and pre-labelled Eppendorf’s and vortexed for 10s, then spun in cold-room microfuge at 13,200rpm for 1min. Using a toothpick, the clumped DNA pellet was removed. A further 60µl cell lysate was removed as control, mixed with 60µl 2x sample buffer and boiled for 5min. In the remaining lysate, 50µl wheat germ agglutinin (WGA)-conjugates Sepharose was added, and samples were then incubated overnight rotating in the cold-room. To use the pulldown samples for western blotting, the samples were spun at 1000rpm for 30s. The NP-40 lysis buffer was removed and a further 1ml of NP-40 buffer was added and the tube inverted a few times. This was repeated 2 more times for a total of 3 washes. The samples were spun at 13,200rpm for 15s and then all traces of supernatant were removed and 50µl 2x sample buffer 78 was added and boiled for 5min. Prior to loading gel with pulldown samples, the samples were spun at 13,200 rpm for 15s, and supernatant was loaded onto gel. 3.2.4.2 Lysate SDS-PAGE (Western Blot) Samples were collected from 6 well plates and lysed with 80µl per well with Lammeli sample buffer (20% SDS, 1M DTT, 1M Tris PH6.8, bromophenol blue, Glycerol, H20). After boiling the samples for 5min, 10µl of sample was loaded into a 10% acrylamide gel for SDS-PAGE. The separated proteins were transferred onto nitrocellulose membrane and then washed briefly with TBS-T (0.1% tween-20 TBS). The membrane was blocked for 1hr in blocking solution (5% milk powder in TBS-T). It was then incubated (4oC) overnight with the appropriate primary antibody. The next day the membrane was washed for 1hr in TBS-T at room temperature, then incubated with the respective secondary antibody for 1hr. The secondary antibody solution was removed, and the membrane was washed in TBS-T for 1hr. The membrane was then incubated with 1ml ECL reagent detection reagent (0.5ml 20x luminol/enhancer, 0.5ml 20x peroxide) for 1min and imaged on the ChemiDoc (Biorad). Image Lab was used to perform densitometry measures and compare the relative amount of a specific protein for a given experimental sample. 3.3 Results 3.3.1 Neurotrophic Signaling in PC12 Cells The PC12 cell line, derived from a rat adrenal medullary tumor (pheochromocytoma), has been widely used as a model for the study of neuronal physiology233. The p75NTR receptor is a key player in neurotrophic signaling64. By utilizing a CRISPR-based approach, we engineered a novel p75KO PC12 cell line in which the p75NTR gene was specifically knocked 79 out. This creates a unique tool to understand the role of p75NTR in neurotrophic signaling. To confirm the successful knockout (KO) of P75NTR in the p75NTR KO cells both WT and p75NTR KO PC12 cells were screened for the presence of p75NTR in all subsequent experiments. 3.3.2 NGF induced TrkA phosphorylation In response to NGF treatment, PC12 cells undergo dramatic phenotypic changes. Acute exposure activates intrinsic signaling pathways associated with neuronal-like signaling and neurite development, while prolonged exposure leads to the extension of neurites and the acquisition of electrical excitability233. To commence the characterization of neurotrophic physiology in PC12 P75NTR KO cells, an acute 30-minute treatment with 50ng/ml NGF was employed to evaluate potential differences in molecular signaling pathways between PC12 WT and P75NTR KO cells. As NGF is recognized to initiate various downstream signaling cascades, including the ERK and PLCy pathways, upon binding to the TrkA receptor, our primary objective was to assess TrkA phosphorylation induced by NGF. Western blot was used to evaluate the levels of activated (phosphorylated) TrkA and verify the complete disruption of p75NTR expression (Fig.10A-B). The phosphorylation of the TrkA receptor induced by NGF was observed in both PC12 wild-type (WT) and p75NTR knockout (KO) cells. Interestingly, in the p75NTR KO PC12 cells, 2 out of 3 repetitions displayed a higher level of TrkA phosphorylation compared to the WT cells, although this difference did not reach statistical significance (p = 0.0584; Fig. 10 B). It is possible that the lack of statistical significance can be attributed to the relatively low number of repeats (3). Furthermore, the presence of p75NTR in the WT P-TrkA pulldown 80 suggests a physical interaction between the two receptors, providing an explanation for the observed higher response in TrkA phosphorylation when p75NTR is absent. Indeed, it is not surprising, as existing literature consistently supports the idea that p75NTR can function as a co-receptor for TrkA, thereby influencing the activity of NGF-induced TrkA signaling65. However, since this data did not reach statistical significance, we conclude that the p75NTR KO cells exhibit a physiological response similar to that of the WT cells concerning NGF-induced TrkA activation. Fig.10 30min NGF induced TrkA phosphorylation in PC12 WT and p75NTR KO cells. (A) Representative western blot of phosphorylated TrkA (Tyr 490), Total TrkA, and p75NTR protein levels 30min after addition of 50ng/ml NGF. Lysate control (Left) and TrkA pull-down (Right). (B) Quantification of P-TrkA levels by densitometry. Data are expressed in a ratio of (P-TrkA/T-TrkA)/Actin, and presented as a mean +/- SEM (Two-Way ANOVA statistical analysis, n = 3 (TrkA), n.s., Fishers LSD Test, WT CTRL vs. WT NGF, p 0.0584, P75NTR KO CTRL vs. P75NTR KO NGF, p 0.0584) 3.3.3 NGF induced ERK, and PLCγ phosphorylation We have established that a 50ng/ml NGF treatment for 30min induces the phosphorylation of TrkA in our PC12 p75KO cells. Now to target the intrinsic signaling P-TrkA Levels 81 pathways associated with neuronal-like signaling we focused our attention on two downstream TrkA signaling cascades; ERK and PLCy pathways. In PC12 cells, as has been observed in primary neuronal cell cultures, PLCγ plays a role in modulating intracellular Ca2+ dynamics and promoting neurite outgrowth, while ERK is recognized for its involvement in initiating protein synthesis and contributing to the differentiation of PC12 cells into a neuron-like phenotype234,235. PC12 WT and p75NTR KO PC12 cells were treated with 50ng/ml NGF for 30 minutes. Western blot was used to evaluate the levels of activated (phosphorylated) PLCy and ERK (Fig.11 A). Downstream of TrkA, NGF significantly increased the levels of phosphorylated PLCy in both WT and p75NTR KO cells compared to control (p 0.0005; Fig.11B). While phosphorylated ERK levels also exhibited an increase upon NGF induction, the change did not reach statistical significance (p 0.1830;11C). When comparing WT and p75NTR KO cells, their similar responses indicate the successful implementation of CRISPR as a tool, confirming the effective removal of the p75NTR protein while maintaining the cellular function of NGF induced TrkA, PLCγ and ERK activation. 82 Fig.11 30min NGF induced ERK, and PLCγ phosphorylation in PC12 WT and p75NTR KO cells. (A) Representative Western blot of Phosphorylated PLCγ (P-PLCγ), Total PLCγ (T-PLCγ), Phosphorylated ERK (P-ERK), Total ERK (T-ERK), and p75NTR protein levels 30min after addition of 50ng/ml NGF. PLCγ and ERK protein level expression was normalized to actin to control for protein loading. P75NTR protein expression was used to verify successful p75NTR CRISPR KO. (B) Quantification of P-PLCγ and (C) ERK levels by densitometry. Data are expressed in a ratio of (P-PLCγ/T-PLCγ)/Actin, and (P-ERK/T-ERK)/Actin respectfully and presented as a mean +/- SEM (Two-Way ANOVA statistical analysis, n = 7 (PLCγ), yes., Bonferroni’s multiple comparison test, WT CTRL vs. WT NGF, p 0.0005, P75NTR KO CTRL vs. P75NTR KO NGF, p 0.0005, Two-Way ANOVA statistical analysis, n= 6 (ERK) passages per condition; n.s., Bonferroni’s multiple comparison test, WT CTRL vs. WT NGF, p 0.1830, P75NTR KO CTRL vs. P75NTR KO NGF, p 0.1830). 3.3.4 The effect of Val66 and Met66 on P75NTR and TrkA signaling Mechanistically, it has been demonstrated that Met66 exhibits a 23% higher affinity for binding to the SorCS2 receptor compared to Val6617. Notably, prior experiments have confirmed the interaction between p75NTR and the SorCS2 receptor, leading to the formation of a receptor complex on the cell surface that induces signaling18. Despite the absence of the 83 BDNF TrkB receptor in PC12 cells, understanding the interplay between NGF/TrkA and SorCS2/p75NTR signalling serves as a transferable model of neurotrophic signaling. The relationship between P75NTR and TrkA is complex and encompasses the dual role of p75NTR as a co-receptor for TrkA and crosstalk with downstream TrkA signals236–239. Given that Met66 binds SorCS2 with high affinity, forming a complex with p75NTR, two potential scenarios arise: 1) there could be a reduction in the availability of p75NTR to act as a co-receptor for NGF/TrkA signaling, or 2) downstream signaling of the Met66/SorCS2/P75NTR complex might interfere with NGF/TrkA signaling101,139. In either scenario, our objective is to comprehend the influence of Met66 on the phosphorylation of TrkA downstream signaling proteins, specifically PLCγ and ERK. We hypothesize that the interaction of Met66 with SorCS2/p75NTR will alter NGF/TrkA signaling, potentially leading to a decrease in the phosphorylation of both PLCγ and ERK. To address this question, we employed our novel PC12 P75NTR CRISPR KO cell line. This approach allows us to delve into the specific role of p75NTR in the overall mechanism and can raises further questions regarding the potential influence of SorCS2 in the signaling cascade. Briefly, cells were subjected to various treatments: RPMI complete used as a baseline control (0), 50ng/ml NGF, 50ng/ml Val66, 50ng/ml Val66 + NGF, 50ng/ml Met66, and 50ng/ml Met66 + NGF, each administered for 30 minutes. Subsequently, Western Blot analysis was conducted to assess P-PLCγ and P-Erk levels using densitometry (Fig. 12A). No significant differences in PLCγ phosphorylation levels were observed between WT and P75NTR KO cells across the baseline control (0), or Val66, and Met66 conditions, suggesting that the pro-domains do not independently induce an effect on PLCγ phosphorylation in the absence of NGF. However, the impact of NGF on PLCγ 84 phosphorylation appeared more pronounced in P75NTR KO cells, especially in the presence of Met66 (Met66 + NGF), although it did not reach statistical significance (Fig. 12B). Shifting our focus to the ERK signaling pathway, no discernible differences were noted between PC12 WT and P75NTR KO cells in the baseline control (0), Val66, and Met66 conditions, mirroring the PLCγ results. However, both the Val66 + NGF and Met66 + NGF conditions significantly elevated NGF-induced ERK phosphorylation in the p75NTR KO cells compared to WT (P < 0.05; Fig. 12C). Given that the pro-domains bind SorCS2 and both p75NTR and SorCS2 can act as co-receptors for TrkA, the heightened NGF induced TrkA signaling (ERK phosphorylation) observed in the absence of p75NTR (p75NTR KO cells), in the presence of either pro-domain, could be influenced by two potential mechanisms. First, the direct interaction between Met66, SorCS2, and TrkA may enhance TrkA signaling. Alternatively, the absence of the pro-domain/SorCS2/p75NTR complex could fail to suppress TrkA activity beyond normal levels, resulting in increased TrkA signaling. Nonetheless, it is crucial to highlight that the NGF conditions in both the WT and p75NTR KO cells did not reach statistical significance when compared to the baseline control (0); therefore, the significance achieved in the other NGF conditions should be interpreted with caution. 85 Fig.12 The effect of Val66 and Met66, phosphorylation of PLCγ and ERK via p75NTR. (A) Representative Western blot of Phosphorylated PLCγ (P-PLCγ), Total PLCγ (T-PLCγ), Phosphorylated ERK (P-ERK), Total ERK (T-ERK), 30min after addition of RPMI complete (Ctrl), 50ng/ml NGF, 50ng/ml Val66, 50ng/ml Val66 + NGF (Val66 +), 50ng/ml Met66, and 50ng/ml Met66 + NGF (Met66+). PLCγ and ERK protein level expression was normalized to actin to control for protein loading. (B) Quantification of P-PLCγ and (C) ERK levels by densitometry. Data are expressed in a ratio of (P-PLCγ/T-PLCγ)/Actin, and (P-ERK/T-ERK)/Actin respectfully and presented as a mean +/- SEM (Two-Way ANOVA statistical analysis, n = 3 (PLCγ), passages per condition; n.s. p > 0.005, Turkey multiple comparison test, Two-Way ANOVA statistical analysis, n= 3 (ERK) passages per condition; p < 0.05, Turkey multiple comparison test, (Val +) WT vs KO p 0.0056, (Met +) p 0.0417). 3.4 Discussion PC12 cells, with their notable ability to undergo neural differentiation in response to NGF, emerge as a valuable and cost-effective tool for modeling neurons and gaining insight into the world of neurotrophic signaling. The NGF signaling system is a complex process, the changes in signaling outcomes are highly dependent on receptor dynamics. Notably, the 86 relationship between co-receptor function (P75NTR-TrkA, SorCS2/p75NTR-TrkA, SorCS2-TrkA) determines the signaling outcome. The investigation into the NGF signaling system has been researched extensively, however, it’s been conducted in varying cellular systems. This results in variability between research groups and demonstrates one of the major pitfalls in the field of understanding NGF signaling system. To overcome this pitfall, we aimed to design a stable P75NTR KO cell line and use it to test the following 1) The signaling relationship between P75NTR and NGF-induced TrkA activation, and 2) The signalling effects of the BDNF pro-domain variants (Met66 and Val66). This novel cell line not only bypasses certain ethical considerations associated with animal research but also ensures a consistent and standardized cellular model system revolving around p75NTR signaling221. To develop a PC12 CRISPR P75NTR KO cell line, our initial objective was to confirm the complete disruption of p75NTR expression. Notably, our CRISPR/Cas9-based approach successfully abolished p75NTR expression in the PC12 P75NTR KO cell line, which remained stable throughout each passage. This laid the groundwork for all subsequent experiments. Having established that our P75NTR KO cell line is not expressing P75NTR, our second objective was to characterize our new cell line by systematically assessing any physiological changes resulting from either the disruption of p75NTR expression or the CRISPR/Cas9 based approach itself. To initiate signalling, NGF must first bind to the TrkA receptor located on the cell membrane. Therefore, we first looked at NGF-induced Trk-A phosphorylation (activation) in 87 both WT and p75NTR KO cells. For all experiments WT cells are the PC12 parental cells that were subjected to CRISPR KO cells to produce the p75NTR KO cells. Interestingly, when p75NTR KO PC12 cells were compared to WT PC12 cells there appeared to be higher levels of phosphorylated Trk-A in the p75NTR KO cell lines. However, the levels of phosphorylation did not reach statistical significance due to a low number of repeats and higher variability in the NGF response observed within each technical repeat. Testa and colleagues have demonstrated a similar result, showing that in the absence of p75NTR, there is an increase in phosphorylated TrkA levels upon treatment with NGF. Interestingly, this affect appears to be NGF concentration-dependant, where p75NTR plays a dual role in NGF signaling: 1) at low (5ng/ml) NGF concentration, p75NTR increases the affinity of NGF to TrkA, thereby increasing TrkA signaling 2) at high (100ng/ml) concentrations, p75NTR decreases the TrkA signaling, by an unknown mechanism240. Therefore, in our experimental setup with 50ng/ml NGF concentration (high concentration), the absence of p75NTR would likely result in an increase in TrkA signaling, consistent with our observed findings. The presence of the p75NTR receptor in the WT P-TrkA pulldown suggests a physical interaction between the TrkA and P75NTR receptor. This may explain the varying levels of activated P-TrkA being dependant on the concentration of p75NTR present in proximity to TrkA. This finding aligns with existing literature demonstrating that p75NTR can function as a co-receptor for Trk-A and depending on multiple factors such as ratio, proximity, and the cellular microenvironment, p75NTR can influence NGF-induced TrkA signaling65. Nevertheless, having confirmed that there was no significant difference between the p75KO PC12 cells and WT PC12 cells regarding TrkA activation, we moved forwards to evaluate two 88 distinct TrkA signaling pathways known to be activated by NGF: The ERK and PLCγ pathways. NGF significantly induced the phosphorylation of PLCγ, without significantly altering the effect between WT and p75NTR KO PC12 cell lines. This indicates that the absence of p75NTR did not notably affect the activation of the PLCγ pathway by NGF, suggesting that the CRISPR p75NTR KO method effectively maintained the integrity of the PLCγ pathway. However, although NGF did increase the phosphorylation of ERK, it did not reach statistical significance. This can be seen by the large variability between each repeat in the levels, pertaining to 1-500 fold increase, which clearly limits the interpretation of these results. Visually, the data indicated that in the absence of P75NTR there was an increase in the phosphorylation of ERK, however, this result proved to be inconsistent between repeats. It does suggest however, that P75NTR can affect the ERK/Trk-A signalling pathway but needs to be further investigated to confirm. Finally, having established that there was no statistically significant physiological difference between the PC12 WT and the CRISPR PC12 P75NTR KO cell lines, we utilized these cells as a tool to address the signalling effects of the BDNF pro-domain variants (Met66 and Val66), believed to be P75NTR dependant. Since PC12 cells are carriers of the SorCS2 receptor and we have seen evidence in our cell line that TrkA and P75NTR physically interact, our investigation aimed to assess how the Met66 and Val66 variants, by binding SorCS2, might modulate the interaction between P75NTR and TrkA, consequently impacting NGF-TrkA signaling: ERK and PLCγ phosphorylation. Given that the aberrant effects of Met66 are attributed to its conformational change, resulting in increased binding affinity to SorCS2, before complexing with P75NTR, two 89 potential scenarios arise: 1) there could be a reduction in the availability of p75NTR to act as a co-receptor for NGF/TrkA signaling, or 2) downstream signaling of the Met66/SorCS2/P75NTR complex might interfere with NGF/TrkA signaling101,139. Therefore, we hypothesize that the interaction of Met66 with SorCS2/p75NTR will alter NGF/TrkA signaling, potentially leading to a decrease in the phosphorylation of both PLCγ and ERK. Notably, the presence of Met66 and Val66 variants did not induce significant alterations in the levels of PLCγ phosphorylation, regardless of the presence or absence of NGF, observed in both WT and p75NTR KO cell lines. This suggests that these variants do not appear to disrupt the TrkA-PLCγ signaling pathway. On the other hand, in cells lacking p75NTR and treated with NGF, both Met66 and Val66 increased ERK phosphorylation. One possibility to explain this result is that the pro-domain/SorCS2/p75NTRcomplex (WT condition) normally suppresses TrkA activity. Alternatively, in absence of P75NTR, the direct interaction between Met66, SorCS2, and TrkA, may enhance NGF-TrkA signaling. To address this, subsequent studies should involve creating a double KO cell line (P75NTR, SorCS2) to establish whether the effect of the BDNF pro-domain variants on p-ERK levels is due to SorCS2 direct binding to TrkA in the absence of P75NTR. 3.5 Chapter Summary In conclusion, our study involved the design and characterization of a p75NTR KO PC12 cell line, followed by an investigation into the effects of the Met66/Val66 variants on NGF/TrkA signaling. Contrary to our initial hypothesis, our findings revealed that the presence of these variants resulted in increased activation of the TrkA-Erk signaling pathway in the 90 absence of p75NTR. This unexpected observation suggests that the pro-domains, in the presence of p75NTR, either induce an inhibitory response to TrkA-ERK signaling by forming the pro-domain/SorCS2/p75NTR complex or in the absence of p75NTR, induce TrkA-ERK signaling by direct interaction of SorCS2 and TrkA. Some clear limitations of this data were the low number of repeats and high variability between repeats. Future research could use this preliminary data to continue characterizing the P75NTR KO cell line, understand the dual role of p75NTR in a NGF dose-dependent manner, and create a double KO cell line (P75NTR, SorCS2) to establish whether the effect of the BDNF pro-domain variants on p-ERK levels is due to SorCS2 direct binding to TrkA in the absence of P75NTR. 91 Chapter 4.0: Conclusion 4.1 Limitations of Study: One of the primary limitations of our study was the low sample size, which reduced the statistical power of our analysis. Detecting subtle but significant effects of the Met66 or Val66 variants on neuronal activity requires a larger sample size, particularly because the predicted effect size is small176. Additionally, there was high variability between repeats, which could have been caused by factors such as maintaining viable cell cultures. Specifically, maintaining primary hippocampal and cortical neuron cultures to a mature age (past 14 days) posed a significant challenge. Variability in culture health, particularly regarding synaptic integrity, could have introduced inconsistencies in our results241,242. Moreover, the experimental methods employed, could also be responsible for introducing some variability. Both Western blotting and immunocytochemistry also presented specific challenges. Western blotting, as a semi-quantitative measure of protein expression, is sensitive to sample preparation and handling, which can introduce variability while Immunocytochemistry reliance on antibody specificity and the potential for non-specific binding could have influenced our findings243–245. Aside from the assays themselves, differences within neuronal populations even if all the cells are of the targeted subtype, variations in the expression levels of receptors like p75NTR can affect the measured response and introduce variability101. Aside from the limitations that primary cell cultures can introduce into an experiment, a cell line such as the PC12 p75NTR KO cell lines, could introduce certain challenges. The knockout process itself may introduce compensatory mechanisms or off-target effects that could influence the results. Furthermore, the KO cell lines might not fully replicate the in vivo environment, limiting the generalizability of the findings246. 92 Overall, these limitations highlight the complexity of studying molecular mechanisms in neuroscience, particularly in the neurotrophic field, where detecting subtle changes is challenging. They underscore the importance of optimizing experimental conditions and methodologies to enhance the reliability and reproducibility of findings. Future research should aim to address these limitations by increasing sample sizes, improving culture techniques, and refining analytical methods to account for their sensitivities. 4.2 The effect of Met66 In conclusion, our study aimed to uncover the mechanisms through which the Met66 mutation influences synaptic activity. Contrary to our initial hypotheses, we found that Met66 does not induce LTD of synapses through changes in Ca2+ dynamics, developmental morphology, or synaptic density. However, both Val66 and Met66 decreased SYN-1 levels in the pre-synaptic compartment, while Met66 uniquely decreased PSD-95 levels in the post-synaptic compartment, irrespective of BDNF levels. These results suggest a potential role of pro-domains in synapse weakening, highlighting Met66's distinct effects on synaptic compartments, which may affect neurotransmission. To further explore these findings, we designed and characterized a p75NTR KO PC12 cell line to investigate the effects of Met66/Val66 variants on NGF/TrkA signaling. Unexpectedly, our results showed that these variants increased TrkA-Erk signaling pathway activation in the absence of p75NTR. This suggests that pro-domains might inhibit TrkA-Erk signaling by forming a pro-domain/SorCS2/p75NTR complex or induce signaling through direct interaction between SorCS2 and TrkA when p75NTR is absent. 93 Despite some limitations, such as the low number of repeats, high variability between repeats, analytical methods employed, and difficulty maintaining viable primary cell cultures, our findings provide valuable insights. Future research should further characterize the p75NTR KO cell line, explore the dual role of p75NTR in an NGF dose-dependent manner, and create a double KO cell line (p75NTR, SorCS2) to determine whether the effects of BDNF pro-domain variants on p-ERK levels are due to SorCS2 binding to TrkA in the absence of p75NTR. Additionally, investigating the compounding effects of Met66 and Val66 on synapse function and identifying alternative mechanisms by which Met66 induces changes in neuronal activity will be crucial. While our findings do not support Met66-induced LTD, they underscore the complex nature of synaptic plasticity and the role of pro-peptides in homeostatic mechanisms. Elucidating the potentially aberrant properties of Met66 will require further research. 94 References 1. Turrigiano GG, Nelson SB. Homeostatic plasticity in the developing nervous system. Nat Rev Neurosci. 2004;5(2):97-107. doi:10.1038/nrn1327 2. Citri A, Malenka RC. 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Figure S 2 Raw Data Box Plot: Impact of Val66 and Met66 on Growth Cone Collapse in DIV. 3/4 Hippocampal Neurons. 115 NB (4)BDNF (4)MET66 (4)VAL66 (4)0123Fold Change of Colocalized puncta/dendritic lengthNB BDNF NGFproBDNF MET66 VAL66 01234 Primary Neurite NumberNB BDNF NGFproBDNF MET66 VAL66 102030Primary Neurite Length (µm)Figure S 3 Raw Data Means: Val66 and Met66’s effect on hippocampal neuronal arbor maturation. Figure S 4 Raw Data Means: Met66 or Val66 demonstrate no significant alteration of colocalized puncta of PSD-95 and SYN-1 in DIV. 17 hippocampal neurons. 116 NB (3)BDNF (3)MET66 (3)VAL66 (3)012345Syn-1 Puncta NumberNB (3)BDNF (3)MET66 (3)VAL66 (3)012345PSD95 Puncta NumebrFigure S 6 Raw Data Means: Met66 or Val66 demonstrate no significant alteration in the count of individual puncta PSD-95 and SYN-1 in DIV. 17 hippocampal neurons. Figure S 5 Raw Data Box Plot: Met66 or Val66 demonstrate no significant alteration of colocalized puncta of PSD-95 and SYN-1 in DIV. 17 hippocampal neurons. 117 NBBDNFVAL66MET660.00.51.01.52.02.5SYN-1 LevelsNBBDNFVAL66MET660.00.51.01.52.0 PSD95 levelsFigure S 8 Raw Data: Effect of Val66 and Met66 Variants on SYN-1 and PSD-95 Levels. Figure S 7 Raw Data Box Plot: Met66 or Val66 demonstrate no significant alteration in the count of individual puncta PSD-95 and SYN-1 in DIV. 17 hippocampal neurons. 118 NBBDNF VALMET Val+Met+012345P-PLCy LevelsNBBDNF VALMET Val+Met+0.00.51.01.5261014 P-ERK LevelsFigure S 9 Raw Data: The impact of Met66 on molecular signaling in Div.7 Cortical Neurons. 119 Appendix B: Detailed Analysis Protocols Growth Cone Analysis: 1. Open ImageJ/Fiji https://imagej.net/downloads 2. Click> File Open [now open the image you want to analyze. 3. The image will now appear black…don’t panic it there a. Click>Image>stacks>z-stacks b. Set to max intensity and click ok 4. Set Scale & Set measurements a. Drag a straight line over the scale bar and let it rest there [best is if you zoom in to improve accuracy] b. Analyze>set scale c. Change the known distance to the distance shown in the bottom right corner [note: convert nm to m ex: 25000nm>25 m] i. You will also have to write microns into the unit of length which will appear as inches d. Hit Global (this will apply the setting to all future images opened so we don’t have to do this again) e. Now to set what we want to measure Analyze>set measurements>area 120 5. Pressing control and either + or – will allow you to zoom in or out of the image a. Zoom in on the tip of the axon (generally the longest structure-polarized) b. Drag a square over the region where the green region meets the red c. Right click> duplicate [add title of dish and # of GC)> ok 6. At this point Save the image as a JPEG (File>Save as> JPEG [Remember to Name them] 7. Image> color>split channels [note it will show you the channel color in the name description at the top of the image-drag it until you see “(green)” a. The green channel will correspond to phalloidin (what we are interested in) b. The red channel will correspond Map2 8. Working on only the green channel a. Press simultaneously -Command>shift>T b. Using the Threshold panel remove any red dots from background while maximizing the red signal on the structure of interest [do not hit apply] 121 9. Hit Edit>selection>create selection [this will highlight the region of interest] 10. Hit Command>T a. This will put it into the ROI Manager (Region Of Interest) b. Now hit measure and you will receive a measurement for the area of the region highlighted. Put this value into an excel sheet and label GC # vs condition 11. Once everything has been analyzed in a condition add all the JPEGS into a word document with a short name to identify them [xxxxx GC#1] EX: [xxxxx GC#1] 122 Colocalized Particle Analysis: (Colocalized particle / µm measurement) Immunocytochemistry (ICC): PSD-95 488 Green SYN-1 546 Red MAP-2 633 Blue 4%PFA PH 7.5 Imaging: Power for channels 8% PSD95, 8% SYN-1, 18% MAP-2 keep consistent throughout set Analysis: Threshold~100 but will vary per rep. Keep consistent through all images from one rep (5x per condition) unless there is a clear abnormality in background on an image then you can manually adjust. Copy plugin RG2B_colocalization (JAVA) (shared on SLACK) to plugins in ImageJ folder Your images need to have green and red channel, composite and RGB, saved as jpeg. Open image Trace scale bar on image>analyze>set scale>global Circle and remove (press delete) cell body---SAVE Duplicate picture (right click on the pictureà duplicate) 123 One image will serve to determine the MAP2 length and one image will serve to determine colocalized particles. For MAP2, on 1 of the two image: Image à color à split channel. Keep only the MAP2 channel Processà Binary à make binary ProcessàSkeletonize Edit>selection>create selection 124 Analyze à set measurement AREA Analyzeà Measure Write down Area : here for instance 1048576 Using the scale determine the value in um Use line to trace Analyzeà measure For that picture: 25um = 147 (area) So 1048576 (area) = 178329 um That is the total length of neurites in your image One image will serve to determine colocalized particles. Select the other image (from the duplicate) Plugins à compile and runà RG2B_Colocalization (not the one with .class) à open OK 125 The image in black and white is the colocalization data. Select that image Imageàadjustàcolor thresholdà set a value for brightness, for this example I set 150 / 255 Close the color threshold tab AnalyzeàAnalyze particle Size: 2.0 OK Table with all the colocalized particles: 126 For this example: 542 particles. Final calculus: Total area = 178329 um Total number of colocalized particles = 542 In this image we have 542/178329 = 0,0030 colocalized particles / um
Thesis/Dissertation
eng
Biochemistry and Molecular Biology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Barker, Philip A.
Gibon, Julien
The effect of the brain derived neurotrophic factor pro-domain variants, val66 and met66, on neuronal activity
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