Modelling Microtubule Dynamics at Super-Resolution

1. Modelling Microtubule Dynamics at Super-Resolution Summer Project Plan Nils Gustafsson Supervised By: Dr Lewis Griffin Dr Thomas Surrey

2. Summary • Microtubules • Microtubules and the Cytoskeleton • Dynamic Instability of Microtubules • In Vitro Microtubule Experiments • Analysis of In Vitro Experiments • Validation of In Vitro Experiments • Ground Truth Simulations • Simulating Experimental Data • Modelling Microtubule Dynamics

3. Microtubules and the Cytoskeleton Multiple Cellular Functions • Mechanical Stability • Scaffold Structures • Force Generation • Cargo Transport • Cell Migration • Cell Differentiation • Cell Division Drug Targets • Vinca Alkaloids • Taxanes Microtubules (green) DNA (blue) EB1 (yellow) Fig. (top right) taken from Molecular Cell Biology 4thed, Lodish Fig. (bottom right) taken from TorstenWittmann homepage, UCSF

4. Dynamic Instability • Microtubule (+)end tracking proteins (green) reveal rapid growth and shrinkage episodes in live cells. • Fine control of microtubule dynamics by microtubule associated proteins (MAPs). Fig. (bottom left) taken from Molecular Cell Biology 4thed, Lodish

5. Dynamic Instability Fig. taken from C. Conde & A. Caceres, Nature reviews Neuroscience, 2009

6. In Vitro Microtubule Experiments • Stabilised GMPCPP seeds are bound to a cover slip • Fluorescently tagged tubulin subunits are introduced via micro-fluidics • Microtubules are nucleated at the seeds • Imaged by TIRF microscopy as they grow Fig. (bottom left) taken from C Duellberg’s PhD Thesis Fig. (bottom right) taken from The Dixit Lab research webpage, Washington University

7. Analysis of In Vitro Experiments • Custom analysis software tracks end positions • Using convolved model fitting • Sub-pixel precision alignment of frames allows averaged intensity profiles to be produced • Multiple channels can be analysed including MAP structures

8. Validation of In Vitro Experiment Analysis • Simple simulations have previously been used to determine resolution of taper lengths • We would like to be able to determine accuracy of tracking of dynamic characteristics of microtubule growth – such as growth fluctuations. Fig. (bottom left) modified from Maurer, Cade, Bohneret. al. Current Biology, 2014

9. Simulating Experimental Data • Monte-Carlo Simulation of the 1D model defines a state sequence used to reconstruct microscope images • Considerations: 200-2000 states per frame, noise, movement, labelling densities, magnification…… Fig. (center left) modified from Gardner et. al. Cell, 2011

10. Modelling of Microtubule Dynamics • Accurate quantification of experiment leads to improved models • Models should include: • Growth velocities and fluctuations • Interaction with MAPs • Catastrophe/rescue frequencies Fig. (left) modified from Gardner et. al. Cell, 2011 Fig. (right) modified from Maurer, Cade, Bohneret. al. Current Biology, 2014

11. Acknowledgements Microtubule Cytoskeleton Lab, Cancer Research UK • Dr Thomas Surrey  Laboratory Head • Dr Nicholas Cade   Principal Scientific Officer • Dr Iris Lueke   Senior Scientific Officer • Ms Claire Thomas   Senior Scientific Officer • Dr Sebastian Maurer Previous Group Member • Dr Christian Duellberg   Scientific Officer • Dr JayantAsthana   Research Fellow • Dr Todd Fallesen   Research Fellow • Dr Franck Fourniol   Research Fellow • Dr Johanna Roostalu   Research Fellow • Dr EinatSchnur    Research Fellow • Dr Hella Baumann   Graduate Student • Mr Jonathon Hannabuss   Graduate Student • Ms RupamJha   Graduate Student • Mr GergoBohner   Diploma Student CoMPLEX, UCL • Dr Lewis Griffin • Ms Stephanie Reynolds