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

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Presentation on theme: "Modelling Microtubule Dynamics at Super-Resolution Summer Project Plan Nils Gustafsson Supervised By: Dr Lewis Griffin Dr Thomas Surrey."— Presentation transcript:

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 2/11

3 Microtubules and the Cytoskeleton 3/11 Multiple Cellular Functions Mechanical Stability Scaffold Structures Force Generation Cargo Transport Cell Migration Cell Differentiation Cell Division Drug Targets Vinca Alkaloids Taxanes Fig. (top right) taken from Molecular Cell Biology 4 th ed, Lodish Fig. (bottom right) taken from Torsten Wittmann homepage, UCSF Microtubules (green) DNA (blue) EB1 (yellow)

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). 4/11 Fig. (bottom left) taken from Molecular Cell Biology 4 th ed, Lodish

5 Dynamic Instability 5/11 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 6/11 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 7/11

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. 8/11 Fig. (bottom left) modified from Maurer, Cade, Bohner et. 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: states per frame, noise, movement, labelling densities, magnification…… 9/11 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 10/11 Fig. (left) modified from Gardner et. al. Cell, 2011 Fig. (right) modified from Maurer, Cade, Bohner et. 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 MaurerPrevious Group Member Dr Christian Duellberg Scientific Officer Dr Jayant Asthana Research Fellow Dr Todd Fallesen Research Fellow Dr Franck Fourniol Research Fellow Dr Johanna Roostalu Research Fellow Dr Einat Schnur Research Fellow Dr Hella Baumann Graduate Student Mr Jonathon Hannabuss Graduate Student Ms Rupam Jha Graduate Student Mr Gergo Bohner Diploma Student CoMPLEX, UCL Dr Lewis Griffin Ms Stephanie Reynolds 11/11


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