Spatial and Stochastic Modeling of TrkB Mediated Signaling Pathways Involved in Long Term Potentation in the Dendritic Spine Christine Seeliger Wolfson College University of Cambridge A thesis submitted for the degree of Doctor of Philosophy 1 January 2014 Spatial and Stochastic Modeling of TrkB Mediated Signaling Pathways Involved in Long Term Potentiation in the Dendritic Spine - Summary - Christine Seeliger Long Term Potentiation (LTP) is thought to be one of the main molecular mechanisms underlying the processes of memory and learning in the brain. One of the most studied mechanisms is the synaptic potentiation mediated by glutamate and its receptors resulting in conductance changes of the post- synaptic membrane. Brain-derived neurotrophic factor and its receptor TrkB, first identified as an important growth factor for neuronal survival and growth, appears to be a crucial modulator of LTP at glutamatergic synapses. The small size of the synapses and their highly structured spatial appearance gives rise to signaling properties that have to be accounted for by using stochastic and spatial simulation methods. This thesis implements a computational model and its stochastic evaluation to explicitly study the influence of the spatial location of signaling components on the signal output itself as defined by its duration, amplitude and spatial extent. Furthermore, a geometrically accurate model of the spine is developed together with a biochemical representation of the TrkB signaling pathway and its influence on membrane conductance changes. This work focuses on the interactions of the involved kinases and phosphatases and their dynamic behavior in time and space. An extension of the simulation environment Smoldyn is proposed to allow explicit modeling of the molecular behavior based on the membrane environment to account for different submembrane compartments such as the synaptic membrane. The influence of different spatial and biochemical modifications of the TrkB signaling pathways and the different levels of integration down to its influence on membrane receptor trafficking are addressed. The results demonstrate the importance of the spa- tial layout of the signaling systems for the created signal and the possibilities of fine-tuning it based on spatial properties. To my family Elke, Friedrich Wilhelm, Martin and Ulrich Seeliger Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. This thesis does not exceed the specified length limit of 60.000 words as defined by the Biology Degree Committee. This thesis has been typeset in 12pt font using Latex according to the speci- fications defined by the Board of Graduate Studies and the Biology Degree Committee. Acknowledgements Many thanks to my supervisor Dr. Nicolas LeNovere for the opportunity to work and write my PhD thesis in his lab and my TAC members to join in for the yearly discussion of intermediate results: Dr. Julio Saez-Rodriguez, Dr. Carsten Schulz and Dr. Llewellyn Roderick. Along with this, I’d like to thank all fellow CompNeurians, especially Melanie Stefan, Jean-Baptiste Petit, Lu Li, Michele Mattioni, Benedetta Frida Baldi and Massimo Lai. The shared laughter, flying animals and other lab equipment and sometimes advise and discussions were very valuable especially during the first phases of this journey. Massive thanks and hugs for keeping me sane during times of intense rowing and work and sharing the odd bowl of midnight porridge every now and then to my flatmates Nenad Bartonicek and Sander Timmer - keeping the Wiggle Mansion Spirit high! The same for my PhD twin and buddy in crime - Benedetta Frida Baldi. Without our endless discussions in the smoking corner from PhD related topics to general life issues, I would have probably tried to run away. Oh... wait... Zagreb was an awesome experience and probably made the otherwise daunting period of writing up and excellent adventure in itself as part of our amazing trio including Nenad. Thanks to the EBI PreDoc community for pub nights, PhD lunches, trips and all things social and in general being an awesome bunch as much as all the people I have rowed with during my time in Cambridge as a member of Wolfson College Boatclub (WCBC) and Cambridge University Women’s Boatclub (CUWBC). Special thanks to the Friends of WCBC and Wolfson College for supporting my rowing ventures also financially and welcoming me back to college rowing every year for May Bumps. Kudos to all my proofreaders Nenad Bartonicek, Melanie Stefan, Michele Mattioni, Benedetta Frida Baldi, Dr. Nicolas LeNovere and John Coadwell that spend time reading this manuscript and provided valuable feedback on structure, figures, legends and last but not least the English language. Special thanks to Nenad Bartonicek for being the only person except for John who made it through the entire manuscript and providing additional supervision along the way. However, without the support of my family at home I would have never made it. My eternal gratitude and love is with them and most of all my parents Elke and Friedrich Wilhelm that stood by my side especially during the hard, non-PhD related events during my early months in Cambridge, always supporting my decisions and wanting the best for me and my life. Contents Declaration iii Contents vii List of Figures xi List of Tables xv List of symbols xix 1 Introduction1 1 The molecular basis of learning and memory . .3 1.1 The glutamatergic synapse . .4 1.2 Synaptic plasticity . .7 1.3 Growth factor signaling in long term potentiation . 10 2 Computational modeling in biology . 14 2.1 Different modeling approaches . 16 2.1.1 Deterministic versus stochastic approaches . 16 2.1.2 Single compartment versus spatial approaches 18 2.2 Examples of different simulation environments . 20 2.2.1 The COmplex PAthway SImulator - COPASI 20 2.2.2 The Virtual Cell - VCell . 21 2.2.3 Smoldyn . 22 2.3 Modeling long-term potentiation in the dendritic spine 23 2.3.1 Choosing a modeling framework for growth factor signaling in the dendritic spine . 25 3 Objectives . 26 2 Significance of the kinase and phosphatase localization on the formation of lipid signaling domains in dendritic spines 29 1 Introduction . 29 1.1 Objectives . 31 2 Methods . 31 2.1 Modeling and simulation . 31 2.2 Modeling reactions and parameters . 32 2.3 Geometry and diffusion . 33 2.4 Analysis . 33 2.4.1 Time course analysis . 34 2.4.2 Spatial analysis . 35 3 Results . 37 3.1 Model parameters . 37 3.2 Simulation setup . 39 3.3 Technical constraints . 41 3.3.1 The surface partitioning influences the simu- lation results . 41 3.3.2 Surface interaction during surface diffusion appears to be leaky . 45 3.3.3 Summary . 46 3.4 Development of membrane PIP3 levels over time de- pends on the spatial scenario . 47 3.4.1 Circular spatial setups can focus the signal to the PSD . 47 3.4.2 The magnitude of the PIP3 signal and the PSD/Total PIP3 ratio are the major parame- ters influenced by changes in the spatial scenario 51 3.4.3 Spatial scenarios with r(PI3K) < r(PTEN) are most efficient in focusing the signal to the PSD 53 3.4.4 The maximum steady state PIP3 levels at the PSD depend on the radii of the circles and the average distance between PI3K and PTEN molecules . 55 3.4.5 The overall reaction speed is similar between different spatial scenarios . 58 3.4.6 Statistical testing for complete spatial ran- domness (CSR) identifies scenarios producing signaling peaks . 59 3.4.7 Analysis of the pair correlation function veri- fies previous CSR results . 62 3.4.8 The diameter of the signaling peak increases with r(PTEN) and r(PI3K) . 63 3.4.9 Summary . 65 4 Discussion . 66 3 TrkB signaling in long-term potentiation 69 1 Introduction . 69 2 Methods . 74 3 Results . 75 3.1 Model setup . 75 3.2 The onset of TrkB signaling is characterized by the com- petition of PI3K and PLCγ for their common substrate PIP2 . 85 3.3 AMPAR potentiation depends on the upstream signal- ing outcome . 89 3.4 The special diffusion environment of the PSD could increase signaling efficiency . 94 3.5 Partial inhibition of PLCγ results in a more reliable activation of both AMPAR potentiation pathways . 96 4 Summary . 99 5 Discussion . 99 4 Extending Smoldyn to allow surface dependent diffusion 103 1 Introduction . 103 2 Smoldyn supporting surface dependent diffusion: Smoldyn V2.21_M . 104 2.1 Testing . 105 2.1.1 Diffusion . 105 2.1.2 Reactions . 109 2.2 Modeling AMPAR trapping . 113 2.2.1 Different macroscopic diffusion environments can mimic scaffold binding . 113 2.2.2 Different diffusive environments enhance re- ceptor trapping at the synapse . 115 3 Discussion . 117 5 Conclusions 119 List of Publications 127 Appendix 129 List of Figures 1 Examples of micrographs showing the cellular nature of the nervous system and dendritic spines . .2 2 The morphology of the neuronal synapse . .5 3 Synaptic transmission and NMDAR dependent Long Term Potentiation . .7 4 AMPAR trafficking at the postsynaptic side . .9 5 TrkB Receptor Signaling at the postsynaptic site . 13 6 Illustration of different simulation result types . 34 7 Biochemical and spatial illustration of the implemented signal- ing system . 37 8 Spatial Simulation Scenarios . 40 9 The surface tessellation influences the simulation results . 42 10 Reducing the valence of edges enables random diffusion . 44 11 Surface interaction during surface diffusion is leaky . 46 12 Arranging PI3K molecules on an inner ring surrounded by PTEN creates a focused PIP3 signal at the PSD . 48 13 A transient center signaling peak might form in beginning of simulating spatial setups without PTEN .