Modelling Microtubule Dynamics at Super-Resolution

Summer Project PlanNils Gustafsson

Supervised By:

Dr Lewis Griffin

Dr Thomas Surrey

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

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Microtubules and the Cytoskeleton

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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, LodishFig. (bottom right) taken from Torsten Wittmann homepage, UCSF

Microtubules (green) DNA (blue)EB1 (yellow)

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).

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

Dynamic Instability

5/11Fig. taken from C. Conde & A. Caceres, Nature reviews Neuroscience, 2009

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

6/11Fig. (bottom left) taken from C Duellberg’s PhD ThesisFig. (bottom right) taken from The Dixit Lab research webpage, Washington University

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

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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.

8/11Fig. (bottom left) modified from Maurer, Cade, Bohner et. al. Current Biology, 2014

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……

9/11Fig. (center left) modified from Gardner et. al. Cell, 2011

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

10/11Fig. (left) modified from Gardner et. al. Cell, 2011Fig. (right) modified from Maurer, Cade, Bohner et. al. Current Biology, 2014

AcknowledgementsMicrotubule 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 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

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